diff --git a/.gitignore b/.gitignore
index aa4abd3..15613ea 100644
--- a/.gitignore
+++ b/.gitignore
@@ -52,6 +52,7 @@ coverage.xml
 .hypothesis/
 .pytest_cache/
 cover/
+.test-logs/
 
 # Translations
 *.mo
diff --git a/packages/markitdown/pyproject.toml b/packages/markitdown/pyproject.toml
index 8ca9b11..701a461 100644
--- a/packages/markitdown/pyproject.toml
+++ b/packages/markitdown/pyproject.toml
@@ -41,19 +41,20 @@ all = [
   "openpyxl",
   "xlrd",
   "lxml",
-  "pdfminer.six>=20251107",
+  "pdfminer.six>=20251230",
+  "pdfplumber>=0.11.9",
   "olefile",
   "pydub",
   "SpeechRecognition",
   "youtube-transcript-api~=1.0.0",
   "azure-ai-documentintelligence",
-  "azure-identity"
+  "azure-identity",
 ]
 pptx = ["python-pptx"]
 docx = ["mammoth~=1.11.0", "lxml"]
 xlsx = ["pandas", "openpyxl"]
 xls = ["pandas", "xlrd"]
-pdf = ["pdfminer.six"]
+pdf = ["pdfminer.six>=20251230", "pdfplumber>=0.11.9"]
 outlook = ["olefile"]
 audio-transcription = ["pydub", "SpeechRecognition"]
 youtube-transcription = ["youtube-transcript-api"]
diff --git a/packages/markitdown/src/markitdown/converters/_pdf_converter.py b/packages/markitdown/src/markitdown/converters/_pdf_converter.py
index 63162d5..b692f16 100644
--- a/packages/markitdown/src/markitdown/converters/_pdf_converter.py
+++ b/packages/markitdown/src/markitdown/converters/_pdf_converter.py
@@ -1,22 +1,18 @@
 import sys
 import io
-
 from typing import BinaryIO, Any
 
-
 from .._base_converter import DocumentConverter, DocumentConverterResult
 from .._stream_info import StreamInfo
 from .._exceptions import MissingDependencyException, MISSING_DEPENDENCY_MESSAGE
 
-
-# Try loading optional (but in this case, required) dependencies
-# Save reporting of any exceptions for later
+# Load dependencies
 _dependency_exc_info = None
 try:
     import pdfminer
     import pdfminer.high_level
+    import pdfplumber
 except ImportError:
-    # Preserve the error and stack trace for later
     _dependency_exc_info = sys.exc_info()
 
 
@@ -28,16 +24,374 @@ ACCEPTED_MIME_TYPE_PREFIXES = [
 ACCEPTED_FILE_EXTENSIONS = [".pdf"]
 
 
+def _to_markdown_table(table: list[list[str]], include_separator: bool = True) -> str:
+    """Convert a 2D list (rows/columns) into a nicely aligned Markdown table.
+
+    Args:
+        table: 2D list of cell values
+        include_separator: If True, include header separator row (standard markdown).
+                          If False, output simple pipe-separated rows.
+    """
+    if not table:
+        return ""
+
+    # Normalize None → ""
+    table = [[cell if cell is not None else "" for cell in row] for row in table]
+
+    # Filter out empty rows
+    table = [row for row in table if any(cell.strip() for cell in row)]
+
+    if not table:
+        return ""
+
+    # Column widths
+    col_widths = [max(len(str(cell)) for cell in col) for col in zip(*table)]
+
+    def fmt_row(row: list[str]) -> str:
+        return (
+            "|"
+            + "|".join(str(cell).ljust(width) for cell, width in zip(row, col_widths))
+            + "|"
+        )
+
+    if include_separator:
+        header, *rows = table
+        md = [fmt_row(header)]
+        md.append("|" + "|".join("-" * w for w in col_widths) + "|")
+        for row in rows:
+            md.append(fmt_row(row))
+    else:
+        md = [fmt_row(row) for row in table]
+
+    return "\n".join(md)
+
+
+def _extract_form_content_from_words(page: Any) -> str | None:
+    """
+    Extract form-style content from a PDF page by analyzing word positions.
+    This handles borderless forms/tables where words are aligned in columns.
+
+    Returns markdown with proper table formatting:
+    - Tables have pipe-separated columns with header separator rows
+    - Non-table content is rendered as plain text
+
+    Returns None if the page doesn't appear to be a form-style document,
+    indicating that pdfminer should be used instead for better text spacing.
+    """
+    words = page.extract_words(keep_blank_chars=True, x_tolerance=3, y_tolerance=3)
+    if not words:
+        return None
+
+    # Group words by their Y position (rows)
+    y_tolerance = 5
+    rows_by_y: dict[float, list[dict]] = {}
+    for word in words:
+        y_key = round(word["top"] / y_tolerance) * y_tolerance
+        if y_key not in rows_by_y:
+            rows_by_y[y_key] = []
+        rows_by_y[y_key].append(word)
+
+    # Sort rows by Y position
+    sorted_y_keys = sorted(rows_by_y.keys())
+    page_width = page.width if hasattr(page, "width") else 612
+
+    # First pass: analyze each row
+    row_info: list[dict] = []
+    for y_key in sorted_y_keys:
+        row_words = sorted(rows_by_y[y_key], key=lambda w: w["x0"])
+        if not row_words:
+            continue
+
+        first_x0 = row_words[0]["x0"]
+        last_x1 = row_words[-1]["x1"]
+        line_width = last_x1 - first_x0
+        combined_text = " ".join(w["text"] for w in row_words)
+
+        # Count distinct x-position groups (columns)
+        x_positions = [w["x0"] for w in row_words]
+        x_groups: list[float] = []
+        for x in sorted(x_positions):
+            if not x_groups or x - x_groups[-1] > 50:
+                x_groups.append(x)
+
+        # Determine row type
+        is_paragraph = line_width > page_width * 0.55 and len(combined_text) > 60
+
+        row_info.append(
+            {
+                "y_key": y_key,
+                "words": row_words,
+                "text": combined_text,
+                "x_groups": x_groups,
+                "is_paragraph": is_paragraph,
+                "num_columns": len(x_groups),
+            }
+        )
+
+    # Collect ALL x-positions from rows with 3+ columns (table-like rows)
+    # This gives us the global column structure
+    all_table_x_positions: list[float] = []
+    for info in row_info:
+        if info["num_columns"] >= 3 and not info["is_paragraph"]:
+            all_table_x_positions.extend(info["x_groups"])
+
+    if not all_table_x_positions:
+        return None
+
+    # Compute global column boundaries
+    all_table_x_positions.sort()
+    global_columns: list[float] = []
+    for x in all_table_x_positions:
+        if not global_columns or x - global_columns[-1] > 30:
+            global_columns.append(x)
+
+    # Too many columns suggests dense text, not a form
+    if len(global_columns) > 8:
+        return None
+
+    # Now classify each row as table row or not
+    # A row is a table row if it has words that align with 2+ of the global columns
+    for info in row_info:
+        if info["is_paragraph"]:
+            info["is_table_row"] = False
+            continue
+
+        # Count how many global columns this row's words align with
+        aligned_columns: set[int] = set()
+        for word in info["words"]:
+            word_x = word["x0"]
+            for col_idx, col_x in enumerate(global_columns):
+                if abs(word_x - col_x) < 40:
+                    aligned_columns.add(col_idx)
+                    break
+
+        # If row uses 2+ of the established columns, it's a table row
+        info["is_table_row"] = len(aligned_columns) >= 2
+
+    # Find table regions (consecutive table rows)
+    table_regions: list[tuple[int, int]] = []  # (start_idx, end_idx)
+    i = 0
+    while i < len(row_info):
+        if row_info[i]["is_table_row"]:
+            start_idx = i
+            while i < len(row_info) and row_info[i]["is_table_row"]:
+                i += 1
+            end_idx = i
+            table_regions.append((start_idx, end_idx))
+        else:
+            i += 1
+
+    # Check if enough rows are table rows (at least 20%)
+    total_table_rows = sum(end - start for start, end in table_regions)
+    if len(row_info) > 0 and total_table_rows / len(row_info) < 0.2:
+        return None
+
+    # Build output - collect table data first, then format with proper column widths
+    result_lines: list[str] = []
+    num_cols = len(global_columns)
+
+    # Helper function to extract cells from a row
+    def extract_cells(info: dict) -> list[str]:
+        cells: list[str] = ["" for _ in range(num_cols)]
+        for word in info["words"]:
+            word_x = word["x0"]
+            # Find the correct column using boundary ranges
+            assigned_col = num_cols - 1  # Default to last column
+            for col_idx in range(num_cols - 1):
+                col_end = global_columns[col_idx + 1]
+                if word_x < col_end - 20:
+                    assigned_col = col_idx
+                    break
+            if cells[assigned_col]:
+                cells[assigned_col] += " " + word["text"]
+            else:
+                cells[assigned_col] = word["text"]
+        return cells
+
+    # Process rows, collecting table data for proper formatting
+    idx = 0
+    while idx < len(row_info):
+        info = row_info[idx]
+
+        # Check if this row starts a table region
+        table_region = None
+        for start, end in table_regions:
+            if idx == start:
+                table_region = (start, end)
+                break
+
+        if table_region:
+            start, end = table_region
+            # Collect all rows in this table
+            table_data: list[list[str]] = []
+            for table_idx in range(start, end):
+                cells = extract_cells(row_info[table_idx])
+                table_data.append(cells)
+
+            # Calculate column widths for this table
+            if table_data:
+                col_widths = [
+                    max(len(row[col]) for row in table_data) for col in range(num_cols)
+                ]
+                # Ensure minimum width of 3 for separator dashes
+                col_widths = [max(w, 3) for w in col_widths]
+
+                # Format header row
+                header = table_data[0]
+                header_str = (
+                    "| "
+                    + " | ".join(
+                        cell.ljust(col_widths[i]) for i, cell in enumerate(header)
+                    )
+                    + " |"
+                )
+                result_lines.append(header_str)
+
+                # Format separator row
+                separator = (
+                    "| "
+                    + " | ".join("-" * col_widths[i] for i in range(num_cols))
+                    + " |"
+                )
+                result_lines.append(separator)
+
+                # Format data rows
+                for row in table_data[1:]:
+                    row_str = (
+                        "| "
+                        + " | ".join(
+                            cell.ljust(col_widths[i]) for i, cell in enumerate(row)
+                        )
+                        + " |"
+                    )
+                    result_lines.append(row_str)
+
+            idx = end  # Skip to end of table region
+        else:
+            # Check if we're inside a table region (not at start)
+            in_table = False
+            for start, end in table_regions:
+                if start < idx < end:
+                    in_table = True
+                    break
+
+            if not in_table:
+                # Non-table content
+                result_lines.append(info["text"])
+            idx += 1
+
+    return "\n".join(result_lines)
+
+
+def _extract_tables_from_words(page: Any) -> list[list[list[str]]]:
+    """
+    Extract tables from a PDF page by analyzing word positions.
+    This handles borderless tables where words are aligned in columns.
+
+    This function is designed for structured tabular data (like invoices),
+    not for multi-column text layouts in scientific documents.
+    """
+    words = page.extract_words(keep_blank_chars=True, x_tolerance=3, y_tolerance=3)
+    if not words:
+        return []
+
+    # Group words by their Y position (rows)
+    y_tolerance = 5
+    rows_by_y: dict[float, list[dict]] = {}
+    for word in words:
+        y_key = round(word["top"] / y_tolerance) * y_tolerance
+        if y_key not in rows_by_y:
+            rows_by_y[y_key] = []
+        rows_by_y[y_key].append(word)
+
+    # Sort rows by Y position
+    sorted_y_keys = sorted(rows_by_y.keys())
+
+    # Find potential column boundaries by analyzing x positions across all rows
+    all_x_positions = []
+    for words_in_row in rows_by_y.values():
+        for word in words_in_row:
+            all_x_positions.append(word["x0"])
+
+    if not all_x_positions:
+        return []
+
+    # Cluster x positions to find column starts
+    all_x_positions.sort()
+    x_tolerance_col = 20
+    column_starts: list[float] = []
+    for x in all_x_positions:
+        if not column_starts or x - column_starts[-1] > x_tolerance_col:
+            column_starts.append(x)
+
+    # Need at least 3 columns but not too many (likely text layout, not table)
+    if len(column_starts) < 3 or len(column_starts) > 10:
+        return []
+
+    # Find rows that span multiple columns (potential table rows)
+    table_rows = []
+    for y_key in sorted_y_keys:
+        words_in_row = sorted(rows_by_y[y_key], key=lambda w: w["x0"])
+
+        # Assign words to columns
+        row_data = [""] * len(column_starts)
+        for word in words_in_row:
+            # Find the closest column
+            best_col = 0
+            min_dist = float("inf")
+            for i, col_x in enumerate(column_starts):
+                dist = abs(word["x0"] - col_x)
+                if dist < min_dist:
+                    min_dist = dist
+                    best_col = i
+
+            if row_data[best_col]:
+                row_data[best_col] += " " + word["text"]
+            else:
+                row_data[best_col] = word["text"]
+
+        # Only include rows that have content in multiple columns
+        non_empty = sum(1 for cell in row_data if cell.strip())
+        if non_empty >= 2:
+            table_rows.append(row_data)
+
+    # Validate table quality - tables should have:
+    # 1. Enough rows (at least 3 including header)
+    # 2. Short cell content (tables have concise data, not paragraphs)
+    # 3. Consistent structure across rows
+    if len(table_rows) < 3:
+        return []
+
+    # Check if cells contain short, structured data (not long text)
+    long_cell_count = 0
+    total_cell_count = 0
+    for row in table_rows:
+        for cell in row:
+            if cell.strip():
+                total_cell_count += 1
+                # If cell has more than 30 chars, it's likely prose text
+                if len(cell.strip()) > 30:
+                    long_cell_count += 1
+
+    # If more than 30% of cells are long, this is probably not a table
+    if total_cell_count > 0 and long_cell_count / total_cell_count > 0.3:
+        return []
+
+    return [table_rows]
+
+
 class PdfConverter(DocumentConverter):
     """
-    Converts PDFs to Markdown. Most style information is ignored, so the results are essentially plain-text.
+    Converts PDFs to Markdown.
+    Supports extracting tables into aligned Markdown format (via pdfplumber).
+    Falls back to pdfminer if pdfplumber is missing or fails.
     """
 
     def accepts(
         self,
         file_stream: BinaryIO,
         stream_info: StreamInfo,
-        **kwargs: Any,  # Options to pass to the converter
+        **kwargs: Any,
     ) -> bool:
         mimetype = (stream_info.mimetype or "").lower()
         extension = (stream_info.extension or "").lower()
@@ -55,9 +409,8 @@ class PdfConverter(DocumentConverter):
         self,
         file_stream: BinaryIO,
         stream_info: StreamInfo,
-        **kwargs: Any,  # Options to pass to the converter
+        **kwargs: Any,
     ) -> DocumentConverterResult:
-        # Check the dependencies
         if _dependency_exc_info is not None:
             raise MissingDependencyException(
                 MISSING_DEPENDENCY_MESSAGE.format(
@@ -65,13 +418,55 @@ class PdfConverter(DocumentConverter):
                     extension=".pdf",
                     feature="pdf",
                 )
-            ) from _dependency_exc_info[
-                1
-            ].with_traceback(  # type: ignore[union-attr]
+            ) from _dependency_exc_info[1].with_traceback(
                 _dependency_exc_info[2]
-            )
+            )  # type: ignore[union-attr]
 
-        assert isinstance(file_stream, io.IOBase)  # for mypy
-        return DocumentConverterResult(
-            markdown=pdfminer.high_level.extract_text(file_stream),
-        )
+        assert isinstance(file_stream, io.IOBase)
+
+        markdown_chunks: list[str] = []
+
+        # Read file stream into BytesIO for compatibility with pdfplumber
+        pdf_bytes = io.BytesIO(file_stream.read())
+
+        try:
+            # Track how many pages are form-style vs plain text
+            form_pages = 0
+            plain_pages = 0
+
+            with pdfplumber.open(pdf_bytes) as pdf:
+                for page in pdf.pages:
+                    # Try form-style word position extraction
+                    page_content = _extract_form_content_from_words(page)
+
+                    # If extraction returns None, this page is not form-style
+                    if page_content is None:
+                        plain_pages += 1
+                        # Extract text using pdfplumber's basic extraction for this page
+                        text = page.extract_text()
+                        if text and text.strip():
+                            markdown_chunks.append(text.strip())
+                    else:
+                        form_pages += 1
+                        if page_content.strip():
+                            markdown_chunks.append(page_content)
+
+            # If most pages are plain text, use pdfminer for better text handling
+            if plain_pages > form_pages and plain_pages > 0:
+                pdf_bytes.seek(0)
+                markdown = pdfminer.high_level.extract_text(pdf_bytes)
+            else:
+                # Build markdown from chunks
+                markdown = "\n\n".join(markdown_chunks).strip()
+
+        except Exception:
+            # Fallback if pdfplumber fails
+            pdf_bytes.seek(0)
+            markdown = pdfminer.high_level.extract_text(pdf_bytes)
+
+        # Fallback if still empty
+        if not markdown:
+            pdf_bytes.seek(0)
+            markdown = pdfminer.high_level.extract_text(pdf_bytes)
+
+        return DocumentConverterResult(markdown=markdown)
diff --git a/packages/markitdown/tests/test_files/MEDRPT-2024-PAT-3847_medical_report_scan.pdf b/packages/markitdown/tests/test_files/MEDRPT-2024-PAT-3847_medical_report_scan.pdf
new file mode 100644
index 0000000..30e1960
Binary files /dev/null and b/packages/markitdown/tests/test_files/MEDRPT-2024-PAT-3847_medical_report_scan.pdf differ
diff --git a/packages/markitdown/tests/test_files/RECEIPT-2024-TXN-98765_retail_purchase.pdf b/packages/markitdown/tests/test_files/RECEIPT-2024-TXN-98765_retail_purchase.pdf
new file mode 100644
index 0000000..34842dc
--- /dev/null
+++ b/packages/markitdown/tests/test_files/RECEIPT-2024-TXN-98765_retail_purchase.pdf
@@ -0,0 +1,97 @@
+%PDF-1.4
+%“Œ‹ž ReportLab Generated PDF document http://www.reportlab.com
+1 0 obj
+<<
+/F1 2 0 R /F2 3 0 R /F3 4 0 R /F4 5 0 R
+>>
+endobj
+2 0 obj
+<<
+/BaseFont /Helvetica /Encoding /WinAnsiEncoding /Name /F1 /Subtype /Type1 /Type /Font
+>>
+endobj
+3 0 obj
+<<
+/BaseFont /Helvetica-Bold /Encoding /WinAnsiEncoding /Name /F2 /Subtype /Type1 /Type /Font
+>>
+endobj
+4 0 obj
+<<
+/BaseFont /Courier /Encoding /WinAnsiEncoding /Name /F3 /Subtype /Type1 /Type /Font
+>>
+endobj
+5 0 obj
+<<
+/BaseFont /Courier-Bold /Encoding /WinAnsiEncoding /Name /F4 /Subtype /Type1 /Type /Font
+>>
+endobj
+6 0 obj
+<<
+/BitsPerComponent 8 /ColorSpace /DeviceRGB /Filter [ /ASCII85Decode /FlateDecode ] /Height 70 /Length 4491 /Subtype /Image 
+  /Type /XObject /Width 200
+>>
+stream
+Gb"/lq,^Nc)M\9OkX:DBZ5YT>'!op&`0lHCEL`PXM2DFT$QuCdPsfSJ4#%$gW49i\1e&eZ\Acg:2bhaPc+^Q$/Shs#,1&Qu>83CBh729[%A$M]]Z8KL]Cu-OpO.1`\pCPboa2!3#sCC+4Yg#.W)"\K&i)doY5WCH.J-G0E$]%J"BRoZ88okcKEP@C7S%JEA:t(e6:OLb-"MZ3=$fAIE$]%J"BRoZ88okcKEP@C7S%JEA:t(e6:OKV=+u3F\<8ml>&.H@]EH:@TAeD]);ilGV3,!4G2kP0XRN"#r/]G!Kqo1c9Redk1d%Hh[t82=;lMkgMFr4J2#lTY[siCuNDGT]h^te4%1fj10r$&D--;(2UPbQ(Ze:VUL"2G=%qPZVOlc,tegG*BO,:$mI%mCAJ^8q2gWSn>)Ui.KQ!A5_(Z;l?_%(Xb28AGIU0SY?bVp%B6=$P2*I!1?W8WL>aAVWc$%-nk=D8ZjE$stW]LJ-LqIj9qZoFV/lj$Uf)=b`nfl*ANkt_qpb2t'P`;D#\h6o+g'M+"j4Sf:d#_jjZdTS>mnQJm^7>(S3Bq"m(kH5i3;0`YK<5e.0$k"4XA4UX)rfXH+2OamR360'cX$&"Dp"DdSkh^Q;?+H)fBc@YMp?\]UZuQ*lgt@kDS'dARs/]`Roa+]eXm%&TJ4e[RCKq6kQ:5Zpa[hLTEE,M/UR\C]SS.K'HJL7F)F5Ts63hWCKs+aTqi3TN!,P7#o$@'a?^`M.9&=d,$WJ*\b^*N1fR$JFV.s`.W*WfCgS\9h@C2/uC<b(1#bB73rR3UmcP"%)_DZ#=)TA1KkfUBT8F;=Yoc[BR6[ZkS\Y$n/.@mf!9WK1Hj]o3[f>DiFrdD&a`iRQ\df2(Xc53$=i@@upbP,MJ@.sDgm%`^.8+5u//"Hhn%^kIb$5o\2B7%r>DD\NZ:L;otY0]:)'6l[M<&ctoM"($Q_XW1'!4OB>g/3dF]mD],eF*&&'itQ;2e$/VWZ/QmdogQ0&d7ePkDGP[PZkk8TtUWkaJYa$Q)c6I+l<preqG)K\U>pY5H])D-lHdp52<d:Isd8)X0&b+pKUugDNb2NIW.aD_PLN/i(r9N&<3?,2br'%?gT'_i;n9VUeeM#>ko&@JS]_pP&PR0@L`i*pbXB"rgcI`#'#>-Njfe@8+ZC7hHU>Qm2oCj$^ATs<7[sZ@5*,@qslQ\p1m1#p6XrGL'F^?ok?+\fDe1,#<0n78&1'&KK/85E7IuiRklZ$<tM_`dQfdI@$2&Sj]k*=&V0n1RVEA-6,(U`EJ9674P)af%Z>l=<9-YKka`e!9&oUk]3u7Y);o;!X[W(:<D3M@"gDG)[;",CR0eT^r/fRnB+ob8JM\tp9\JoC\=uqFPX9nU`?:Y,eJf!6E95r@KI_iekuY/-+j6DIrXFQW>i@m+VqQff?4r\fn@@4QXN6[dWdtV8:B`3X2:bgH!rR8-r^sf)#EN%"`F/q0Heh_C7H6l'.@I3l<Jr.Q!as3DB-9V*+/'h,_<T8?^2u*t.p$h8d%"Dd\P<5M`MEg>7W_M8qB0Sd$'o&pWH!XFNS.JRZ%[WY$N:rl5tLIb;#&1u\'nOCIB]161$bC,Uuf;ZK6dl()epY<39X_LaOAXU:WAZiYqZk5Tq+hN`O"QdZ7[jLdf^cf`?9i4T#=]JO$'0fC4#Y=^M%VOouL.PZ6/V;r+XoF1Ls*YXu`6'4?,j47_u_U=.T*IX0ed;@5JN=Qlc\gS!W?r;#%jA)NSUh\`='l:HWsF<K@<`EqO<,Ht[H.@PGU,p6$s&YbEgb;cfG9YK,6Fh]@t(EUD@78Ob6ui6[#pIBoZn<UH)N"PrIeP3Y!qa-k8bP>_rQ_q'7l3]f,=As5FN;rm6/&IWa@[9HFr3YtU'N%=ZPr)s`!!&o!IbLLsBH7VnG&"_&hSn3;Nr^mpSZk^2i_aD8<g*:f)-)1j6@3KSHbb_c1PDAXpnkGE:H3Fs0m?uXff0>H]^Oi^Wq(2*ak3>^mA^!FkG4$-Vq(BH"U+YSR;%(5j(bnT,&RrR1d]\O5_42^f/Xa:4msf,Oms&5F6()XE"p6mS/Yc\Ga&`hC/3XdsM;'cTMl(uV@DiFY5AA_VWS4T'&^D<.7.S,`B?:^&!Q[ZVaCi0^$[E#=Xt_;^\;l;M#]`$4;sLf^6$u5)gpB'7TO-@*HXbXF]H[ID>=n%&8-T:f)&:]?hm\RN5/B5sdW)PM[X@>2Jq/jQ%m%0Pk%J`<],L8cn3_`B)dE8ng`*C-";2ro.7o.B2:3d$4r#LEqr#8((eIunkG+V@25V=%+_!:Z/,UQca-*F<WEc]8T!rP(2A>g9*GW$LPXTF:ER(d"o8oX31"!B8VtcoXnY$9m&'30Um_8lI0aO.LY_m,l[3VfKlBY*[!$I#3=:"_\lGs6U"<,-kF4HFN$6[_SQpG)7_H3mnKRB'C9#q8EY(Vaqi(D&r$*Jr?OPiaP#RRYeN0)sia9W*TKT)#N9#q8EY(Vaqi(D&r$*Jr?OPiaP#k^2Zeu*-9hp_.0@)f6Em^OKjQe!N6R'K"tCBm#IB,_F0s/@WUCJX)`/6>DF6M_)Kk.s>$UZPX\r/#8I8q/RiHL2liUAA0Yf`%Ld=068s:8FSq=\;#qPO.M6gNJ<fcJ_B7NfVHbGb(Z#%=9b&C:^$<Xe!_fU:_#gd*5iB@GeEYKud7*YgG3W,jj8\q'/4@l'Y-g\)rX-m;H77/R]Zb%A!YN(tcDfkrJ&o7($5o=b[,R0&h>j\UuBER`krd-YJajg!X[eDSKG#rM875C*#IQWm+O@aOf*TU2U('gKn4DA1c#r\17+;`V`#Kgpm8RC[Ee$Ac&[r[O5Rd>4]?HeBRku2;R,jekQW/J-QCRW&^t>C\3e,:[W(TT!T:2JEND71MtHndISe*l)E$(\gO^@6Z"5Q<4O)uM0mY8/2q_>,e#m"SaP0HaXDih_2UgJZH0.io.<EHam+)Ba'CJ3$,Ve\2W\TOCDf>!]XNj5RmJj5Qb:1EKuS*^?b+;s)^?6l>JE0QrGSUpouIlZac9kX41>cja=/SDr<cA`ZGg.-dcfEr]UahTX\[1!?g.Q+Bc7gR:Jn+!PFgH?<j_Cphp%2cK2o3EmuaRlLL,1SFd.EYSt<=je7H>"[/Y4/S?T:Ij;Z5Vm!N#O9oGbTmC/.8"?)WA+NO#l!d__>E^^P^^5SPK3f#a-$jDf&=>7p3h\GbV.%e"aa`Nr8:-((uUWjP?5h<QpA5fPW)4^9]4ZVP3n=aOl2n\TH8,2g(<%d(S%%7D#]P?GegI?jC3uo^tm=sN6Bp.;hI!R:5>*[4qX1g^KT=J\eG*=-r!s:Xj;^b_=6X9pT)tmOPN+SP\Y9d?!CS[k5Z"1@+N1#RUIImf:>$etSOp!A$%9Npa7^LW;"'>&DLN*LT#=""p0WOpjXfI:C##@j@lDSU=Xe\&,@B>QE*Z4EfD\=1"h4F8$&QPkBC:BBC"p$N?^/:S9o*P:eF4j>`WT<EG,f\ln6T<>&V*-UR?1+=iZ&Y:YJ)Y_O1Q!(3MOc:&,lEK0KT>gBrM!Oo7g$R0Z=@n</A>l[op[I#4)k.C3f6pb.hq#9_d636^F1(A%Us@pB(WNXIQ#TKD-`)0%k[fj0?XEDjbhd[m6#LpLW.'sd9_sqo4)9,(HjMXDMbKZE5`!!P4XRB@/4TISu+m2&%RiFj^;=JGE6IZZZ3Iq9u;tP9Ze)spB!TH+!k0kjm?9TaEqM'"N]I#K68.sENFpG-:BpL"k5<Kf;Cll]p\0.VBgJXYV7bkGELTah(>RWGsjL14<<sE:X3JW]):L"_a3kcBH&.(2Ui6d<sTVSq6Hb2oGX:N_j+E^^?#]Brd-YC/q4&j48+1kK<)&.;T[(aqqDC]Z:"7NhLIO5&BeU-SXc>m&CBpaKs!LDjG%ZThfU"?o'^kNBIDSK`iDtti"$XI@8UFlc6'SU-*bNc0g0qZU.!3k5:g&J5%_GC<>>?gMnQALpYLh_[CK2YgZMfbcG=f9!FE+GUto#YS.Ms0oqhppBVFIgKikS73+[l77Q]oKP@6W$g?K-&@CV\IU2l9TjknpF,mi!B#31b$WjNK[_SbrBad@)rY(?tsa<O6[4Wd_rrCQDK9Fn>?noi;W9O[OS+IIT/JfXc1#&UNmnp:7_c6/aW-".*cBVjc)"DgbY/sJI7I:YTo4n^?6D*J='=Z.q\rms\C-WjI*igXS;Vfo_`Y\`_c8K6r=SE5*WPmG+p6'k&&0eDn]e<kl$//^-6n?[M0Wg:@`F!W*m'jM%_,JfY,&JA=T)'Qh]O:`+1#oOo&Q&lRj>R;8k_3L)o&mP_\+Z6EUKR,;fQ&lT(!/=AJY_cg)ZFd_iV[)$d`W(]Q<7PapAWM]!Y4qoZ_Z9e(Tts:W\F3=&Fc,Mp(`=cJUG]7+gkp\4)_AlnCa6gYn$_U<4&\@+ERR^ZIFpqbN%;:=3k=P0?fC_:0&Ug9TYUE[kI#Bq;+mc:C\/7H:]h-hq^[P:`jZ\paVNd3BCYF4eruZ)J"F0tYQ"^`hf0;~>endstream
+endobj
+7 0 obj
+<<
+/Contents 11 0 R /MediaBox [ 0 0 216 792 ] /Parent 10 0 R /Resources <<
+/Font 1 0 R /ProcSet [ /PDF /Text /ImageB /ImageC /ImageI ] /XObject <<
+/FormXob.2a351979d8c75d073b2ea4bfb74718f9 6 0 R
+>>
+>> /Rotate 0 /Trans <<
+
+>> 
+  /Type /Page
+>>
+endobj
+8 0 obj
+<<
+/PageMode /UseNone /Pages 10 0 R /Type /Catalog
+>>
+endobj
+9 0 obj
+<<
+/Author (\(anonymous\)) /CreationDate (D:20251205104951+01'00') /Creator (\(unspecified\)) /Keywords () /ModDate (D:20251205104951+01'00') /Producer (ReportLab PDF Library - www.reportlab.com) 
+  /Subject (\(unspecified\)) /Title (\(anonymous\)) /Trapped /False
+>>
+endobj
+10 0 obj
+<<
+/Count 1 /Kids [ 7 0 R ] /Type /Pages
+>>
+endobj
+11 0 obj
+<<
+/Filter [ /ASCII85Decode /FlateDecode ] /Length 1981
+>>
+stream
+GauI8D/\/e&:hOi=55KJ8;^%$X%4*F0ZR4[TQ-.JlIl=8,25emeWsH3DOUP#SK,Tt>!%\QTf-@>5)IUB4PgI,!l6hOHqp".7kqY?VEc$;f0G$C+?kE+IduY+D6B[cY<`?1&+Bf$SSWa.DI28'F?:CpG_mY"TO]hkXiFku&",h"4G/8GlCSK3UDT`3W#q'Qc;4>t6\tbspa(/l?]"D>nboQo,(,[\*-A;J=Ru^j=[Nu\:iMk7q<+PGo*gWpT4_C)j)t7Oc[5MlffWrhj!99;,0?]r3R(ns^B^I*KQ#f[([aS1g);Q.rrBep&6)sVJs=\.1^pkCa(tBfECI75_;C0LC.)*n<3;@eFZT<Brd%CYO%*fRCl_%R2PLtnF>0lg_SFKN$O.X\o%U7_58YJ,X[`p,%PUL^1]EgT]T\4*B3hOrEZA:[=ui88pZGht%klE^OC$2=@$GiMoTO<eR\C2;10r\O.%_7=c.`)*@0N>,CLh>2ZDq?"(LrLS)ajJ<DG(:N]5MPuT)E6J8.)!Ud7D>Je7M&(V1i'>Z@qg3/WJ@PpL4nr1qU$V_#jqpM+M<[H(LE:pW6uTQK`^P%Q'T&[*Y1\T_7.O:+n^Y)3+d56\hGsIrnqB85q[4L1WG#"Uo.d]Zr"jG`qiT=AU8b5]p3(N2IfnWHVO&$rnNe6[_$[o(m=2Sq-C[bbNOS,qIb?:TGYHhQjjcCe!9%*cuscgU*Eea^B?#^HtoE9p(jd_GR#E1\LTm:MVS5e]+<LZRQ]0^iZNnTs\Iq5l6H+?80%j?IX^UR28jY=Vr!:#Jf=D$QdR#4X6Q%Z^E6hq4[p#rHu/mN!PgeQCn_hEI9M3(_b.pAid<e0?KUakkhL+Sq1A+!S(V0h+OF8nn#&[1+6p+D5^<OP@s\HS\itN&+apX>;a8<=<fVm-cM(u=Q31UTuXZiRNk/X^o=e`8?ha=(l,J:AYGq&k'81mIs68U9).dPb@tBY#5s6I1(;=p-FNV8JLO6-b%6]BUEO#*P:YXQ,+2T8!GeA%OFD*^H'I<qo6Q\KGcc$9<-q;oCHo2eF[F/t'nG3p8bj]<0qUd^A*Un<D3^J]5-EeYaHZL0]dZ(aldZ?U]EL]o1@j;L=l_$._u&B5KRKtY900d3EO'mY6&5WB,D7o]o+7,#h.[N58L+)*ks!_/dIq7L<$Q/>:Ym/3(NJmP3]c2J81f'[9A229?.>nW.Y"uioK$/X(RLnTFa0nhiu#_V(M%6pL-[3&IEZO^iW'pcgSC4%cs*UfWL8=h@<SF-6Ml.SK#\%/6pL;XKVP08]+YR4.1^h^3g+iL6p2jNFKi##9N\7TS:EE')be-k57a"IMZoUV#>]Eoq_3uS@i.]*ai31P3"'$;S,Q%'"=$Vq"-_!pX<>bA]?nd=dOpZa\$"k!cpI9L2SO3gBd7]TKi)s)3F/ADnb^3N)iF')M[\Fq1\^PAl):!YpJp!B\s/2LkZr*`(o%fTO.qa?N[7\P_Dj!-3=OAO3]DtNKn-R1Hc#$?$h;RW[;B(k%DrOQ4lA(kZ`8[,.5E\H/%&9RE1k-pKk^'?Wseh?':/9RD3&&Xf\j=9;Sdd#l!b5li$Q.?@#FtJ9r"D*THt>o=+h,ei<3VCI\e<F.YjMklHmQ252@7%.$dl?FX[.5Ru_<cOnWObGU$sud3sn0Nm?VSip=&P_8=3<b5l"NFchqcT66k!jof;<?"kHRj[>Q+FB(V85-;*H\(QoM*>m2@9WKA`dV0$2F]lQ!^cKY?-F<<RYBD9:P`&#<:DJpSA0L]L_Q`8=5'6'r`p_54_;lcH+H=)4\l8B7YE#pX>K&Mf4jEn:L@C'pmu(T(NAo?onFtPTH*Mah:OJII8OF6<oMipM;1-5S+stnT,o"n]+UmpI>_OX,SeHS'86i`]nN=oW_Hjm1lb%agT!)1^3rJWom\/,?BYNjThVR,cQ'opa8Q#<G9<qeSN'GRRO*(AC(K$'<9uMACIm=MV?Mk2Q*3P"~>endstream
+endobj
+xref
+0 12
+0000000000 65535 f 
+0000000073 00000 n 
+0000000134 00000 n 
+0000000241 00000 n 
+0000000353 00000 n 
+0000000458 00000 n 
+0000000568 00000 n 
+0000005249 00000 n 
+0000005507 00000 n 
+0000005576 00000 n 
+0000005859 00000 n 
+0000005919 00000 n 
+trailer
+<<
+/ID 
+[<4800d64fefba4dd902e51197c7da4e88><4800d64fefba4dd902e51197c7da4e88>]
+% ReportLab generated PDF document -- digest (http://www.reportlab.com)
+
+/Info 9 0 R
+/Root 8 0 R
+/Size 12
+>>
+startxref
+7992
+%%EOF
diff --git a/packages/markitdown/tests/test_files/REPAIR-2022-INV-001_multipage.pdf b/packages/markitdown/tests/test_files/REPAIR-2022-INV-001_multipage.pdf
new file mode 100644
index 0000000..c795d9e
Binary files /dev/null and b/packages/markitdown/tests/test_files/REPAIR-2022-INV-001_multipage.pdf differ
diff --git a/packages/markitdown/tests/test_files/SPARSE-2024-INV-1234_borderless_table.pdf b/packages/markitdown/tests/test_files/SPARSE-2024-INV-1234_borderless_table.pdf
new file mode 100644
index 0000000..e8ba29f
--- /dev/null
+++ b/packages/markitdown/tests/test_files/SPARSE-2024-INV-1234_borderless_table.pdf
@@ -0,0 +1,115 @@
+%PDF-1.4
+%“Œ‹ž ReportLab Generated PDF document http://www.reportlab.com
+1 0 obj
+<<
+/F1 2 0 R /F2 3 0 R
+>>
+endobj
+2 0 obj
+<<
+/BaseFont /Helvetica /Encoding /WinAnsiEncoding /Name /F1 /Subtype /Type1 /Type /Font
+>>
+endobj
+3 0 obj
+<<
+/BaseFont /Helvetica-Bold /Encoding /WinAnsiEncoding /Name /F2 /Subtype /Type1 /Type /Font
+>>
+endobj
+4 0 obj
+<<
+/BitsPerComponent 8 /ColorSpace /DeviceRGB /Filter [ /ASCII85Decode /FlateDecode ] /Height 250 /Length 7324 /Subtype /Image 
+  /Type /XObject /Width 500
+>>
+stream
+Gb"0T$]J'Hh8f&`$E10oYm@(8\X0op.8VZ0?U3+-`PUA-kXC)$ZF(FS+cnSt_+UF<V*_-4?;t_QCqulN+=R)`J8MAcTJTWN;N7nc?!%nFpAO`Um)cK<Za.K:1]-tEI^1+QB4d`\rj2XfGFgU,AL.<Vzzz!2-BgUh&fBXneOl!.77`i<s"3<>mc3fWAAe?iKV_=cYIbmbE?q#A3MC5(3;*ju:&SG4>@oYJ9b]>H8cll(s_!]^Wdj#7mENY_N]/ZF]UIf(e(iIV3S9+%Xs-]`8!.2T!b144!mPH)qfI]jf[oX'bfT]RAeXM;mN(9DE.lI5\^bZHi0H?+ZtHqt&,uDj/khIt-b"Rr?#dgph@W9eT(j"qA0*Q<QComX4m'l0Lm\,23,@Pa_!5Rr5h%)rLG1LECtY_(pH8oOc@:h0.OiG'qoE?)'lKC=/c0^#V[JqGCBu=nqp>Rl=]$mBsBh^?V`!Ie^f&L=olbQVoVhn(tad)_WTfB\B\&;,P^gT6t*&(g]2WIf&N31U4Far9$:/Dr/.jL^e^fH0;m?qWi=Z:.*W<F3VZ??YjY/p!m,^g9es3<h"9t5.8JogPNh>Y[G;!G4"!hE5;^qL(1KRAX]M;r8<2<7ZSVHUe-b'Idr>?hgP7hj2Ys5<8W&k^%9Q7ho`EpY?\Un4BTdReMt&%1Rp.-K)JTA_12=1T+2r,ghtatY![sSp(h$2b#dqMVXhrZHhsK;FJNRHd%NhApV$$L+_fnYo]X]Y]6@K'>#<k+q4j!7g9P9_Y?nmn`[c]:/M&Hco?KE.*^'5gb:d4Ed7(HUql*MlHM?k+X`&X2`qfADs(s-;C"&qZB%XR3H^DHpqaPdBc'fC8KPc*p7uOJ>o(!e_G4b7\s6F%lH=^*b8(3L(0%9F0]X>A;`\q&%lN]ZL5qV]8o@Nd-j6]k$[r8a.P9s#(nPcjj^$`Jtm)Je7s8D.sV+g?CBl;=2\8'Qo"q;K8Pa$j]o]X]?0!$sKgt8uJe$n4`gJ0fU4nkJ+@)%;lhARK\W^-W0.5fij+$OKACE):K.oq<Hq8t4kKFbckiet5YrqPN7_n0^8XKd2Q4b).jA^-]'O1)5-<jcT;)fNC:W)9;l#7a_&7]("2FL#m;WU.&^HMdF'B@!0?rj4\,k#`m0<b6V7m7cD%8'__;f$6nHnV8383'<JU3);Wg\8c"Oi:-0lrq8;JXJ5$ILn,>u=9&'UO5"O+[+bgsT11F$Q"b-`B4qCUC=VU+-_@PpG+u775'#_?NFV5OYCHL$osIZ12*M@48*^,N>%mQpfe\T`0I/SqhAe^rk006%i.NXclqn/"LE:d*b?t6hFPL2,HaYS4\?KJ`Np5$6PjQHlnF!pW[N"3!eKu'V_;``m)$UTmCm!JU?bc5IVe1:8cO]X@+92++1k47TB:>_]lI+<b9XUesktceDfW\e/?EdOLe#(C'pYK,tHY&XMl=X3u<+HNmNF2VC(ZC'uSPt7O)=k>aIEm9pFu^5-5,*@=Hk_*ko^?<W@7]*)0t_;6jj\)W1M"CX%Fqc_l)1-`1OSZJ]rB\&0+X+.p!cp23d"&E]3;Lg_1Dj!CHZt6jHqZ3U@1$WHF>aR0OTF%FGc!7n%8&&e812C*G&NRkD+=%D=$YbYd7Q2H-W$H^N8S`)*c7nUIUBJQN%`h2ZHJ>Q"b-8fl!,bG)c"=7iu#bp!phWrU7W9lpBhfJ,.:[l-m7dl-ckKbAH"BV4PlY+8s]W"8L)"bA:P"I!P"$194K[56(QP91hgnC]Di2dd[%macjUNhm[N2lM`g?5M#>9NqDdh]63G*.GHGX0"g\j5Q'INp9/=i_h/a"(7;N\%e!/]1atQ+ABOU>cd.ib29n"Z](S:k%;7E%LlRM.pYL8*IpTEk8Z)7)1q1tN\"LJ5o#k[iR*h^$PN^JUfSQB-YgCChnN3]5d9<CVi%sLHZeb2GHhZscq9F2Ys%E=YGJ@q6bKJ)DoVF4sIf&L;%NM_:Z^_O^gp3kGLCQQJnW/_O4(cN;ZtL$l\)=Q3/EeXm7ZA>Zm;IL/Nn[>%_$;&EHLtm1P8lN!ga/:l@[l+#!#I4jFO<MnrUm@D[INWn+oKO]oP$fuQg+=6o!ZP`<`E&jmFujKd%Pg[m'-p34-?pfgG]!,RE-V64CV6sO"9n]p"*P8GjsWbn!.U)e\9Y(11a(1"qA<Bc#8>\T7-FdG4""#g9etN"g>W5R[s6)X]lUl>N;JkeIV^E'@&Af.tdf`br=Nr.Fb@tX.T=N-dhr;DVr0VaH.R2*Z"PFgiH9`[uP7TXKg6j"W(E_h0%>GrXGZWQ&T;"\$mDCIf,<Q7k0/[5RIi*7ZSTrj!8IiRnWUZFiZn`W2Rd4)(f($*'&'#Dh%XgMo<Mg%qj&Y9[D%L\!cBhHhVE)\S[r*.d!UtDG'q9g>9MigDR-I5tc-C(JE?uh^d12Wb)'^%3+[%d\TUS]6<oDq9OP.-PsBgkhN`?YCHN:e9YnX'ECter:?Q\Cu2gMqOcjL!.8nJ`/0O>rn+@oVG*D@n$rEYF<@1:c9(K2fW\dm@H$kCe+5^=,V@nnS#C^afDq"pI)g)u"A8rl7PO$/9*V%Y0^&X4#,"F>kQFN_TLLX!"A8rl7PO$/9*V%Y0^&X4#,"F>kQFN_TLLX!"A8rl7PO$/9*V%Y0^&X4#,"F>kQFN_TLLX!"A8rl7PO$/9*V%Y0^&X4#,"F>kQFN_TLLX!"A8rl7PO$/9*V%Y0^&X4#,"F>kQFN_TLLX!"A8rl7PO$/9*V%Y0^&X4#,"F>kQFN_TLLX!"A8rl7PO$/9*V%Y0^&X4#,"F>kQFN_TLLX!"A8rl7PO$/9*V%Y0^&X4#,"F>kQFN_TLLX!"A8rl7PO$/9*V%Y0^&X4#,"F>kQFN_TLLX!"A8rl7PO$/9*V%Y0^&X4#,"F>kQFN_TLLX!"A8rl7PO$/9*V%Y0^&X4#,"F>kQFN_TLLX!"A8rl7PO$/9*V%Y0^&X4#,"F>kQFN_TLLX!"A8rl7PO$/9*V%Y0^&X4#,"F>kQFN_TLLX!"A8rl7PO$/9*V%Y0^&X4#,"F>kQFN_TLLX!"A8rl7PO$/9*V%Y0^&X4#,"F>kQFN_TLLX!"A8rl7PO$/9*V%Y0^&X4#*?7#CY+R`0d=3`X&gqjkh3:T*bY/F"G9IRA,p7V`f(d.Q7Rm\hLGS(4aQb1n\uNc]-gCG]]+f!nhdbc&I^_:Oo_)LC>!L62f77_Ac(W7S%Ee,EnP#j'c%Rf=Ks&GF$(t)5pobiJ5>k%UQ;u#YJ0jJG^Si.X\lM[?G(O0TL">C*I@>%2d<b/?!^j/^\N<c_4VGm)8KCT[Vr?31YYk$l-j:kSioZiX3Lj#:9\7/B;tT@T/U]FW)9<^8kN-f?JVSZVi$@hI*D,^#R6i-aT/W4RdFZtARi`=.4?V.h7NDcDnVFnM:G?TkQFN_TLLX!"A8rl7PO$/9*V%Y0^&X4#,"F>kQFN_TLLX!"A8qU/bW*o[0m20@**pGb=QoMoBV0Jc^J7`J0qQbQD&[L=>HP+Cl`-U?O2r+BHl2@)9NbI,m0UWp/m(?Kj`#Q-F,e#TmS"c18'J?O(B_H#aPm4,26TFaqoXU".I=)=GHC#@**pGZ9=MIHm)TITS[KGALLmkQ4.FNgLD,D(P3q8R`P2)L@U%+aab_D4dMdh+]pLmM/85a-sm7G$tpj>@i<E*JgCMfaS&_jnqCJnJ0qQbQD&[L=>HP+Cl`-U?O2r+BHl2@)9NbI,m0UWp/m(?Kj`#Q-F,e#TmS"c18'J?O(B_H#aPm4,26TFaqoXU".I=)=GHC#@**pGZ9=MIHm)TITS[KGALLmkQ4.FNgLD,D(P3q8R`P2)L@U%+aab_D4dMdh+]pLmM/85a-sm7G$tpj>@i<E*JgCMfaS&_jnqCJnJ0qQbQD&[L=>HP+Cl`-U?O2r+BHl2@)9NbI,m0UWp/m(?Kj`#Q-F,e#TmS"c18'J?O(B_H#aPm4,26TFaqoXU".I=)=GHC#@**pGZ9=MIHm)TITS[KGALLmkQ4.FNgLD,D(P3q8R`P2)L@U%+aab_D4dMdh+]pLmM/85a-sm7G$tpj>@i<E*JgCMfaS&_jnqCJnJ0qQbQD&[L=>HP+Cl`-U?O2r+BHl2@)9NbI,m0UWp/m(?Kj`#Q-F,e#TmS"c18'J?O(B_H#aPm4,26TFaqoXU".I=)=GHC#@**pGZ9=MIHm)TITS[KGALLmkQ4.FNgLD,D(P3r_#*bI@Nu^<jTV.s+qtA4"0@0B7i!6PNQD&[L=L+i:ba>YGacc/eP>=A&If/uhdaIgSf=,YR3kl>\0?EihL@U%+adu,Lp;i@@8%Nm2R[<ic4(N[h6hs'QAFDYWkbBcLX095U*^>&InBdjrdfU\j&_S5K:qdJlfi-Gpm9@#8l.<,rZ=V5M3$n?RCl`-U?O2taWRPbA]mI3lqmL@rniJ/mKkuf]-sm7Gr#&=1<9-rAQ'LHX7dpE2*m7Bo&1e^G7(1,kPV3/4"uMJ0Ymf_%_3+gnA:#jpq*M;r5SMflb>>na//cf&[`:.f0*FqN%i5$kh]Ef_a^VP]M."HuJat9X^*n2r@*f4G>TYAt1?=@6f*MYP@*/(mng[#@.!M4icj?"C+"4<JjGS'1#mQr.an:5U.RUouGF`-g$'ng<.'GDeMfRDU#+]/DomuZ`6bXsmSRBeNQ<YL[Y;50sEn:U%SRBS4Jat9X^*n2r@*f4G>TYAt1?=@6f*MYP!rrf+NnZt`qniVgK]G44'6Ppo.f[1eZB*20+21kH*F4FO#_"-g[_jb?*O7r=f*SJdaeS0`"gYg:=Ck#E?&'tmm<-8q6h9G%A:\R#'36!68(SmlA:'lOb)e`s%Tsq/l\&8mjO&+k!ngm-X>2&^Y!WuGp,ZWI+aJ/MZ9YkM$*+KVU[+!FZFs"8AOmkJLFePSFi#Uqo&r,FJS_M'<Z.&jf-(N4H_%C`O?C)a=WlJbKN3cfd<3M3fj6&-1*hp`6Pa4=4Zf7<Z?%H4Gt6I0C\a"F7%ML+`@=7GkW36+hf7rk:KL]55;o#F\dle=<Z.&jf)`G%.RWdj3[!$VAOmkJ#NQf(%*>:1J6ZTL+aJ/MODCpQ,`f)1Eae+SR2nA4Ct>]@TL"4mbaDsh]@sfX<B\"C\ZX6FE,N@16W/5WRWJ)Hm.S&]C[,/#kMFI2`.$QeY''5P3(U%[I9U9^+5PiSrc^H0HM-Qc,=dKLY$ANCCY,^NG3i>GIf5?O6_[XVRl5-_r;"arMMd:J'.5\Tg9c(mhJ^1-[N-eM0-<9!CdC?QqtBED04,baD=Zc0G3$drYM?Ep9D$rGCY+R`0d;0@@i&4u<U2(1kuH8/4faT*kZfY$$CuN,\6IqI*R6N^Y$^Z6hIV$b?"\B-=F)'<R!tjN5.p3a]<#(\p?_VC]C.(K2!W<%UdpIe]6<SIhr>gYpdb3-VQR54_#i:)goc'jX`LY[EsJ4^_7:L?*3l-rc@*sJc7(7ur)r7=AD^Ej[?%IdT0AMhX3=JnqVN@%gU45jkFR%G*\Afi.5!7@eZ5#WH1K')a,_<L>$>YoCu)\1*Vo<!s8:ENIeCL-"'4dH_1TWAhLGS(2Lufc]J76sit5AEV0CE\kH6f9$'sb`3*-_LAGFMLk=,SESoO1J<P'lhE8a.<2Ulss]ar_s>M$W>J*Xug??kF`)fE`.Tf?*qI.2]Xj]AQfFo;%)b,VN&E0]+^]$e,P<R"eG.^P]A!9Xhl/Y!`?f["E[rL\/_S=/b+Sa5ZJR;].-g.)qd=.-/ogL0L'ZR7k;q^S'rFmASE59Ja"e#(B`6\hCkNZ:&gDdbTm^%Yi;ET'2V_@n:lfSq1MQ>G9^aiA4YX6\1qC9qteS@^?)V6:/b9R!Y\\[K>:<@KRPFm`]$mSWA_d*A1Dm:ro-XK7^4Ppq,pHh@CA#$?d9?+SP7$UuSR'::UjP&13%^%U0PrTn1U.dQ%u[pV:>0_6buOE1(pY^J89K9t27A@?PT"ZNGmqZQ'tA\5nO\B:h"FLKsSK2lO<Wc$Y(Fme&\i5(')e'_=NJcuOV]?`V2bcSA2HMHu<gROm[hKf.sc[WglG%Bg`TbcRO_&"j[^A)/^gbrbArbpW(e]2L0N2c-k4)2$AK7Y,_S&#mujh]P%rtFbIh[&6?FOb0oBoS[1=gdQ^'.-CTZtN>(7oK6Re>ZARqq?OdFi/qCm7hY!*HGTcp?g+o2a7qVZ=_C!Ec.aq_lK)UmDB1+o_-5]P'1Bd[rZVBh,.nUZjsp;o%^SsmEYWQI=Errd9oamda)`*rTNUBe[@EfnBICZZgID/R59U/++F(Yl,mDC1N;9fkfFJc::*-mNE5g7fEQ0YfWe/>1pJ:=HM%X>@p?BXl.<,rZ=V4rQe9%Nn])^^DdRthjX3iq$uc$4m?)JS\f*X[qWS[[s6Xpt8C`jj6-)PlYgYlWkDi,WS[HhlUIX(ID&`/28O$+T&*M6/>?"R$>$>ZnGNdBsp"BH>NLe5Zf=b\7Nq2a]$]7S0\`@GH2kLi1%<HDfE8/7?7IUJ=XbCth]@=BN.BPcifH;1D/rD:k,!Glqo]4MMq_I?SSO9XEEKsQ$kh<LaDbD>Ok-LeV@b@nnZY%IfgU75gZtNm7Z,_kFHfprD0"po*N>jfGj1P$49:"tR4*p;%f>?u1GOOC*$YnG)D:*E@97PJl=7+n[htC$X>DnMgRdG*;?$]#cF)Fqgi&4c:@&RPtqDu)Ep_pnWE6=Oa>Uge6DF<oCXQ>UNB.U=.N>ksBOn:iEF2o;FggTZ]H1PVecpBq*e`%R=3,rEMPUZ<AC=&W)?.2N=3jnP&^KB,)>fj,WDANO>T16Xlqlqq]rG_7h-Gbl^AN3Rt[Qb=.=o4TReNUS6%gc/6@U\0.I>*B/.p&m\gVq.Nh7IlLe>SMsM]R63Z.*d[3d8f80o[,2*\^te\;kB@Pe%kE^\jTaH*Zh^C_0gKd;(nip:.[d]q``?)rk0hn38mN<BWCn\Vl)7rgMd5-c'km"Q.G<U=sbPJHm6`4aV?(8(.:]Fs-KJG)^3S;=1D'e8tPa0p5&Y!P-3"6h9G%+P0_,802%Aj;P'-aeS0P>[s$BH#t'gCTK9:O0/S*NE(_od<.^WZ-&.j\dle=<Z.&jf)`G%.RWdj3[!$VAOmkJ#NQf(%*>:1J6ZTL+aJ/MODCpQ,`f)1EfF(RjO&*8Y-H-24Lu$D2-(TX8(RdP`[X@HkW0j<=Ck#E>mKF/Wsm+Fl[W5MPp(Ep*KY'<1*hp`"*0B$L?-a)5d%B7O?C)aa>I!9P"4+)\]-*do&r+Wf2uTT*aK$3)QO:gU[*G8A!J3_F<-HYX>2&^Xoi^(<JKS^F[3+7b)e`s%`gM.)3RMA!P-3"6h9G%+P0_,802%A^\g<TY>&X~>endstream
+endobj
+5 0 obj
+<<
+/Contents 11 0 R /MediaBox [ 0 0 612 792 ] /Parent 10 0 R /Resources <<
+/Font 1 0 R /ProcSet [ /PDF /Text /ImageB /ImageC /ImageI ] /XObject <<
+/FormXob.18f55a53584ec2293b2ede279d934b78 4 0 R
+>>
+>> /Rotate 0 /Trans <<
+
+>> 
+  /Type /Page
+>>
+endobj
+6 0 obj
+<<
+/BitsPerComponent 8 /ColorSpace /DeviceRGB /Filter [ /ASCII85Decode /FlateDecode ] /Height 100 /Length 6947 /Subtype /Image 
+  /Type /XObject /Width 350
+>>
+stream
+Gb"/lpK&'N(<?G"F@?a<'Ea4@B#U9]?JV8Ma[n696)#KR"AqHR5S6;fJ=qFU%3TM8]B]Cp^,*1H2I5,pNPp8#F$>B.;c?WRG1F(im2;q"^YVTd5nF/b&GiVMSOO.n!D"(6Je/NZ@GG-)Jfr&F;?h^q6qA1$Je0):+:(;eP^sq_&Q/gb+@Ja<#_EU2AKV7FKTq$1#SBr=JfmHP)$kg*+_;c%6A1SS+:&QW#(dsc8/V\b&=I4SOPb'h[G1Q'H1U3'`EU)_59p3SnL8@A1V@A&NH0k-Msp[=d\#^X9m=Q@Thk9a[QhOb5jI=NSgm1*?!k0qMo&L`Y!k?/5-o5@p)p*iF!o;<,B5YWBpMrA^9i=RR-&:72!os2V4?q0]2T_fBN;jb6W]=4Ck$!4@d!1`C6`'&W^_J.L2*,"h3X833<tCc$Q5%CQLEW%0cQ<+;L6+NRHTcHG'9drn+\ns/YDHFK;)2fV:%>K3I:7,fB8gZbEXOCjf,?=nFGSVBLSD[V&#leY/q>3g(PthDiNY*43fC`s2q%JB6V@2)G1Z=)31Qn]HClB)N\-nVE+dlDYjVQL4I'k@*dRk:1;F=oY'Ro57\\b)0K)90CCW:TA9u,%)k35osJR]pRKi;or84U_(`Zd\Cm6rU[]*,6([n'MorWR=e9D)1/V4cM/iRrN#]KQ\+q)Ke32EA2,$b[9tG*"II?sL)V/6'Qttro)-Recb&A]jS65@*O)=_T1*k$OotHBdbo)R'b2rpibjh<dEf^_D'.oX;2LS*T*kn`>0mhZqG),!%0_4)]"5\6L?#P"i]XS`Lg6o=Gn(Tr&GuU%01/dkT?J]Kq)4KDFK=G'1bW)/72R>RdM^.k2A*atA6XA_0'.9#"FFNY4-#o\#6^P@%Cf2:)XWLll'4:_.)O^,pT)ZOQR>6b;g^ZdKCl\,'N:dHDFA[jX,%kCme)CodW-\?=%_R2d[20n0lH"*WGLf0m/.?Rcs"9_<e8,@e*QC=p&Zpo3PbFgUF%t9>&cJ$kJbq4.2?sdV]NcAhJu]t<TfgFVU&7UYBWqMiO9\Cs;rHr2^#=jeoHtOQo;F.V:[V7&/o>$,J>#dDGT@VK:e:*drgJ6R3K%3+0[][C@mVV3r8U1E?//K?QQLa9b+<AD];d(e5f!3Fd$$t8Zs\h9rF"n&q-_#'-FOSEGRH$s,TD3?DsHD/C0j+j,1\)dSf^c5J-?PL*dM(lT/*GU6g]\4bNNd9W7i5#JsZ9b"_,c"d2Pq*$Y8msrG^IFbhmX%qrN[uNg6LO?aB@c;,mfYP+tWYpnnhKJGaWupJPfEF:sU+;FRmJ`fD/S8f821_E!;JiDQBZct)sa=sFRg*n$\T2s\\_2-M-JbU[9Yi=BGsdV:6I7"g6[]"GXQN#WE;9Q@K$$iP%/!WFR#k[i^'<'Oqp)>&,@Ve's.HW4hl^B-dAm"j)"p<`[KaFjB/gm]D2UT+`A.@h\a69sg_)d'[<)7CmYKL6"]bA:P*R#.RHeODE8]B-k80#+V/_5@-"-q5?AbHq32+[og1KYsZOO#U<>bIs3.$p4[c/H,5`DieUMb!E/\*_ZMN);5:b>Ju@8X8H7JNsGatnFDh&-j)`AJiHa&;l5gg80-)f)7.R/".R11L[*%,X+_V$@odK-gW#fklq#ok?l&`uipie84K?PSMpfnVWG^0D`GK+&N'\CuII1!$d;`gY."b$]2sPh@;8ups(LP,(Ul#kX61GARitSr7Ts%=C*nBH(d-[AqHOp7_4>$#+Oa&)1PZDSGhK4rO&@#g:GknSWKY>%QD"r`2ZS%a12t<!"43o7<@9^TD[K)/&Bmhr1T^C]74/0bN,%GQ_[ZBgc3.1Cdfg2ITm#k5fe":1;^N'U<&US`1T7-@,9Ceh$k0['2all"L3i4`7)QX@o(0on^MCjUB)#,^46C9K;Jg^^pAEQ2'0k;_/_7G8A@<L(GSt^H6N`?C_/o3,&Rnca#q/^QZWrDgFe(h&9>s6p?V2+5ZoB0?=3KSPhX2-/>J!Km>SY*NuVIShqQPeTKs5apI`'\RZU7"i4FjV/T8Ca#>I5_0/%^dO-/0cqD2FkkfgalGQPQF![Q\1IE].,"^,N/[_K>BubqX^(N#)iZfK2u;7+dED,JUK+#[[H.elo:f?1f@!YA]T.C;bPk<4!.,$&Z@a13-t.O*bK_8##aCJao+Rd](,heJTJc0\`XdM;rHuqq:VMGprO?TDRl@9/(NO%%)j+@ZW:C;U\ZFGcPcA!7&OTCK$=mDcLIOQIkMrMc6o>'-B*8pXpW%$V;Wq:qUk&Y@mV%u8Ok5ZCeO^"kP`YGA_7j3"eu6`'[N3Aljf@8qgaBa>T")Y=r<kob>nN9[?F/"^ghXZ:DosZDi">ZT'%PY,qTO$^[I"*+DS,7Hs,AZ:Lq5f_JN#L:9tMG=;d,Sghb3B0L#J6rKLGrd,,G+QC/":%kIuE6j0V\MJTt5qrS,9JnVB\)43:.lh_LfmSnZon4V@$R*-mS:EIWJ1'!PH@Jl!`Xpg.%QfXi;YU7M(1+NG2ePGU6CSP,Kl-NsF?TTZNf9^AhPa)8L5bHF45/jbu0+Mu*)!'?%f-J\q/@Ar$_r@Nf-6;CgDB]u!PnX&c_odKU`Z]R5N5-M*MjRKKr>j:"R>G<mKPq,\SKh1L(gJ_@>/eC/4_@2-E9XX)b7ik.ch=^.:Jg`F0rk]gQ^kpY:N`.E1&1JOl_6>TnPBoP)8FOOE@/"I>UYV#NQIGe`4+Yni2tY;G\ND-J_sV/1_5[`hpa4aFiKNY\sD*8Qi$,m5X@)iO*La9idI%"93qmYMP\@PK^pD=8lYt"^_RqZ^lHCq8D8&s!f"b'-^e/o0rk`Z4/1Uf'>`gb0CE=:fq2W%80?M_CXRDQm6t_Zdn]C>(?mRNUQ.)4CK"IIY!.NX00]GKB0Ur"n#g3_kfI=8)'jjto*@O7`Sg3pTmMSEE0j@2S4]iqG,I>b^-'L`AeVI9,k&,T%Wt*t#STKAQA)MmL#o!D#AXPqM4dc0#TV,<"oGJCZ5EMO'Wbbg#p0/"O?G-%]cYNA4=Y#jB6\0+j_;W&*3iBnj?MS`9QR[L&@D47qTl"/AL>!`7i?DlA4W#S#WB`mnAt2fY`EK+Z`fGCQr92!J,#\Wm#oaNK6fLIX?nqr4KRM;S]Nn4SlB[Qk0]q4d_K=iq"5#J&`UPQGs=V='Fo<m.YkEpC"KjK&X7hhLku<b"$mJBU^RAlLlaA'"<g+S5S/SS.0DjI,,>VM6&:UX&-O.Cb!6Mk#UojA&0dnY"@7j*1(XR36HVP)KEs$EKVeWGa-4>$eJ#lg6-:m5Ut2>GW#\uP(49Y@bXT^!((X#FK!6_Fm?Qt;,MU(gng)1$F^rPMP_1?drNcOkXen4&eobB0E7R-5s*:0-]9j2_QAIi1<uWlA8/XmY/b.Ti?TI0a\kI6r65+<LOQ.%`r;TG.@S1,H#5tkqdFk",c4MSggB&J3FqX;2U^Z8h.Dn^(d+:8-D*!FA%.@?c/5&POgN!IrH!S$2G3a6GRgk]B@u_sb#)E]"&SrE1VK^>s>s2rg4(l!o4Vh1DDI`!fQPRSh'Q&50T?@!>.GGM[RGM^bXphj8GoL8&bjq<?Cr7$34DroO%[<AaTC!3VB]Wr\-,/O7'>lH"Si1765M3I<r<lS8m:A@DE03Y^pZmBO,Z4Q8&1;Y\mIc2QMV?HhMh/3K!&Pk253F;;X+oK//-VlH<i9p^aK;@DZDq&0(ZHJ`TF7&,1Nk,4;*Bu-0F]JK8E$0_\2eFG/l$!Wb-sjl;?i(gXIeTm]#/TD;pG"\Op4Digh/la9F=JAQQOs9:R>Ejc*jfgb(.'Lrqf<m!Ke.&):1(])GIEmYC2CY:$\N4ln][`_kn/:T]LT;APX%&O8E@4abpZ_=%BA_K3:32ZX:"e8*6^t9uq]/k8Y*bH`AfAbI]7\IdKk1]nZ+*4%06J>"2d50'[d&ctd_4Z?+-tRidMSeYlPK#1\mEbegrA*^Qjs=eq\83BQZHj'N$?_hdgMHU$)n`/;a$nJE0(%iEi[[PHWO]J\0YN\@dW\gEXbX8]^.\?:G7,*_!XV4/pOmH8]d[o4fG\540%W?_pH.phA,-l7>g7W;3A46#5ub@3!*R=$6bZEEaIDO-ZfO>tHk`R3!=Ia7_BaU?U+pZ6h5#Up,8PIqtR.93>tN8+2cb+MqDQ<@<+n.Cs-=V<kP%tU2-O>;b#H-bnPF1:T4gaO+@!\7bG6*R/e%,h^La:Ht?KJfG3R$):>1:k6m+:mTZ;[0bqqV*H##*b<NOc4RCq2UlW`jjn`RoV)GOGp(\TW.9=]_E[W8d"6N/&8.oEBlK>`RPU'`I)=PVuXZNb);",=.fcabbih615!l"l[okf%_*4<6+(5TZ`l&]%<MWQAc%8r6\:P26pT,$QmiT%^2NHOiQ@E/U,Z%N)3QMRQr&NnJH_U\niZ1cA'2T>F?O$#fGg(VT7rK8/pa:$j5m/NTYaO91@T3T%E_LpO^3$>Lb4O/$sf`6IfEaf64^iCkEgi_g\KOo@pV/$(9k*RI;FZWYZgn<9='$/(:TPgL+Ho^B2kKZLa?i)7F;9\ff<Nl\;u`$*Ma+]#=B*nGj^+Z.N+jJ@Y)_*cXA1Tnn"@VBk6Wd569G#f1T(tV;Wql1>H]iQ+P<:/HqMHm@QF].RVj@Lm+7AZKnHP(^LU(iZ9I4]D,_#B6)9PV:)+IX9#=R!=,X70ZXj6Li8toJH`m\0.DpYSUe2b*]ln2arm"OAJS0u&V60Tpd@?XAEQ1<*K%eg)SZA\3``g\+\lpa4C8'X#"."nG7IOO"R/ZicG*XLK)c&=:^Ku:Y_ZdeA)sEGA`5.7AGl%t%FMaDn-%1@11\mG@8X0b9XIibGrk+Q85+MrJXKWoq%sQna+@+n'3<PZ$s;U'\aN)ErOfl_AO=r`">,*"[J+E1\jN\H+qaIMYdJ/UVp3-Q7q-gMDgB-'X;Qt]Wmo^Np,eK;5207?#1\mEbX0H+,*4PgT+r/C]?,N)_nac3j0PDd#Qr`-A&dZ@D=VTsTCt,cG/bZFOS6?S,:^UmaqQ6.q\Bf>aR77K0ULttcc>T+s41)N%'&2g6CkdXpu-kV?FC);O0fi:DLf38p4b)^$D.'E.u+`96QGm]44D=p):'PIVbeL:D)CVJ\DT"Hc2^fF*YcI#b]d'.Z,?@B)fg01;h2rP^OICR.YCdDWb*Dc(_K:V#_EU2AKV7FKTq$1#SBr=JfmHP)$kg*+_;c%6A1SS+:&QW#(dsc8/V\b&0YU-#XX3/JKP41;MJ&&p4"FgV3!G\(pj15S#)E,3Th.\/Y;BEitUVqH9[#MOu0!"7^f49cS()3m_-W^W6:Xp2P"."p9SDL@u@=`[?iH`E9$17Xn(e))tkU#R-A*nIt#5uS?q$YH<>LVkH6%Da(KYC6=""1,0]34S@e%"-%<I@?"g%DR1/t"ZY06_pSAk:nX2Nn^qoo.TAj3e`F@(MA!0+"TO;U0Ithjbnst.$L20.`j6Jqe5%o;Q,h2WtlB,LU2uK89<JH1t,g#h"PoZJYEBVRa3jV"S/A1_HiSVl47[KL9CSG)/VU1^.R!LDM[Zu$%@CEIkS2?A#!>@bZ[$3idk5L*.S,(p%S)Ul]s"LR';n"0nM/Q7f>--Ch9HH_BjG`C'cZ1^E'go.0V[A]pD:V[q7+SA5db`+!`)b<d4dC+>"6]TqT_X-KHj:M6_tK7cgo\(&ACq(;CF8ZV?'G<Opnb9@[UY7sIeFBi^k>u0]g7]7K\d5`$sEH#CTh8J0GM^>[Ih-!ZR]`CcRBWF\f$\=;?f.V\,We)kP`ZH:tSsI8FQR28_Q6pCK2`rm,\'H4dCc)%-T&7o!kaUFEL.ia\XQo>]7,\lYFPi0b[Eo(e4&n$q(+upVVnBRT0RI/Bh]$r`\%hG!]g"iRGPXJ:eP5*3$\T75H8*U^Wbjh>^VQiJ[TSd/)^tC,<6*7+SA5CFA9ekc$C\AO(Uh(\)/F3G:O^/uUHl1<d-?q9_"+7U^iPC?:cj>KB":o:H8/ktqYp9T#C8;2'G668kjQ-L>9WKUuWfc'W=/12o^*s(=?ZbK-?!4Gq^UaBI,.mH"0I4U(OoaoD[9?#(mAI"NaLYPrd+ctQk062'LQE[9OJQ751jELSE-r!<5Z25O?O8]FK$9Ig5;&>GUsPKm+\5BT6W]PdW+VUY>u^puLhG$IhJMIoOK8/XC^])T+,(EZsYEOF#/.8ZgM80],$g(IPh3YOS8&%/<[CItJr`J7=]bUHPk[_?h8[AXN#fW"H09(uRD?<Toj.=2jE'9,,'m3Hmii*FRtS]a7sG;Sil:FeYqCj%@`1jBA.<X6*K\u-!][j9u\p2CH8K*"G(bZiOG<i[+%&5i_PB^bu&!,h2OoFpe[W`M(Q']_Sr94Y0io^(Y?Z_t=iRsa.\XP`.84n?7ie?Wje)>s(.*J,<b'+tI^'"X-+?N('<!\9U?a;T:%<V&:BX:dZ?Xj45Y1ZU!Qp";#GIm=>E_oH1Z'?-t0@hM,N^_lJ;T,#n]j4GJ0NI=O&=@D&%Xr`je?b34SM6'^JekXLTcr8%7GL-fo$"u+E](RB_(#^gh-NDX0oBT:gS<_]"8=<QfMu`UikH;Spf$:'S=KeuK,LW2#huMr\FFK8'BYl'-PO%//H94?8_&`Bu%G.a9h(\Na\8@<k'?06N`[$,"JM@B+5:`[]<J-YTEP:n/:<O5#nEI$c-*gQoP/^8BP/atsVL+293"IDTbsm8"UKfS?rqX*Vr0L0?(W]I&b<<+GP&\'iM_\4%-luQMhI4^P&&?W90/(e]1<^8NL`c!38B,me=41Em0:)_UT$B?S]-B5!(TXGOP6=bfJfmHP)$kg*+_;c%6A1SS+:&QW#(dsc8/V\b&0YU-#XX3/JKP41;?h^q6qA1$Je0):+:(;eP^sq_&Q/gb+@Ja<#_EU2AKV7FKTq$1#SBr=JfmHP)$kg*d8C1#+:(jLJfmJ$h/skHJfk?Y?c;sEBM^@f~>endstream
+endobj
+7 0 obj
+<<
+/Contents 12 0 R /MediaBox [ 0 0 612 792 ] /Parent 10 0 R /Resources <<
+/Font 1 0 R /ProcSet [ /PDF /Text /ImageB /ImageC /ImageI ] /XObject <<
+/FormXob.bd0eb65b2aba982ca2209699f3ec766d 6 0 R
+>>
+>> /Rotate 0 /Trans <<
+
+>> 
+  /Type /Page
+>>
+endobj
+8 0 obj
+<<
+/PageMode /UseNone /Pages 10 0 R /Type /Catalog
+>>
+endobj
+9 0 obj
+<<
+/Author (\(anonymous\)) /CreationDate (D:20251205104950+01'00') /Creator (\(unspecified\)) /Keywords () /ModDate (D:20251205104950+01'00') /Producer (ReportLab PDF Library - www.reportlab.com) 
+  /Subject (\(unspecified\)) /Title (\(anonymous\)) /Trapped /False
+>>
+endobj
+10 0 obj
+<<
+/Count 2 /Kids [ 5 0 R 7 0 R ] /Type /Pages
+>>
+endobj
+11 0 obj
+<<
+/Filter [ /ASCII85Decode /FlateDecode ] /Length 1477
+>>
+stream
+GatU3;01_T&:WeDlpEj%YD:GeAR!G!!H*Y&>Y#17[ZAEDTGHm%Rp>3]mol#;#aTd.j-_UpIf=N*h3GAli8R2Ts'u@R]7:D6#nRH%'bKL]=PU`'dG+DO7YVmLaq9TY*(#K(7,ZFR1QR(HHhAHplQ-\$'0!5`OI$%-2(td`CO^[1ATGPQc2W=iA2Ln?:%+ss`H69a[h#h@i[7k+$&a#8pL!F$N5-`7:ri(bH,-3;q>N,L=pI<W>8;lsLZ,86=@7QjT(8V-l1d_.<>eVp5!2";kDtf-FX\8;^]QndArA2G_m`&'>?ltYION0X"CkS8Kj5ZKR:e2d=X=EB`+<M>,4PV&*l`3M&VisZ+Tp_.4o=)?4?jP>#ucr&mBNDjE=m-IF'M["'E;1JHh=<gl:`lElAgkZLq=(cL_17(p`!,'7<QX_Fd0fL(:Xj0!Q?r4Y^2'moq_[7U*fri!9=Df8DrTJqb"Z-?Ff--m+%WU[<"gRCFR/:@2Fmh>/btFdVE!&_0bH/K5Em'GD>CdbZVshfPdSR)/P9p4X:c$nl2.0rX9`Cr(aZh]0(r9V:#f!!B\1ordGJO-.6Z^on#!d0W>QP[N"JAr!`BI/nCIuL1!14Sm`_A\2ok@aD\3<SX@!,e[qH&*H9:j92\sW&AMGXKX<`$]=(sXQmi&JZdNYHUElITRi3$$[=:8W%:Z^P'8qlWdnh+=b1OT#$Xg$.d2At#rNRqNKU&t\W.>j%Br7!HldEX:DH1:hVA3g2fr&^#']q/TR2TjjFLahFM__PN0da4BTtUA?Eh^O?=9@FKWB/66$q43S1ib^Of%&6b9R8N%%SF1`QoH!ARU\1H/uGE&SZ+fe@=]j^-=`gEZ1a$fd7bO>#0h^kHWt&T*!(<V<1"509M8eNE]A"IW(*#+i>T([ndGo:&S8=!0d\DoRACVK2/b26AnhHoVVZ6;l$F1:a'.B$Ja13Fj[DA-Y=EGjHd20\`NK2LiqkY"21+"jF+ds;Di^_GDf#$8(C&186q7<9fq==5hkQ]#"rsD,@nc@/a1U('ShD,$=2#dRT$Nfq.#kkc'rdj7PXZ]uU4[H7m?Ed\i>mfTlT>%;MB<A@?!JAChWf*FQ\f!'M7i<JE]GB:(O6a6iKW.q?<0#S"+*ghkZhrhf+'fdMo/C8;%*5j<ao.e!3uA+U:9ob4c:N@DIJnXLE]KR2\:ZQrR'neOcIj%)SNk(@o:3cMeA3]<FL0+&Y>!5H#^4C&5USWa4$-ZB-Tb`6$I0)!bD"`7mD*SPB;t#M;1]\k2Pd7Lpn[p67!$=&k?'G/="o"FJ+*UWK=+\TA/L!$].tN61#`g^/`Y^\rk)=b"_lCKNLt:LJ1a1atfrWBN\4<YWp21q*FFl,/lO1n?BCR.OGDS+WTd0%5r3lDJOX63r*KF=2<I08B!4-n<f,5W'mdE\\d4GW`.+ON/G8!#MYO]"Xo>@Gq/A7:\$OSG_k4RYS8b5"200bJ[3G*~>endstream
+endobj
+12 0 obj
+<<
+/Filter [ /ASCII85Decode /FlateDecode ] /Length 1580
+>>
+stream
+Gat=,hfG8H&:X@\Yn+C5Zt!#[KL#9tbGBErleJk(gUW*R@$"kZ(gMM8c$t3n5Ti-2-T@V2])&e7Dmd2d7DQkaC&a1e!5GYph0T3V_KlTC3=OI\iF]duYol1b#U,i\_'jA/=a@ctBk5RYE72I!j0i^$;K>p_LK$I["R6$up`GpUY\i[&P`V\@>foEua/Q-[=RRLL&$h/"%&,_!as_^j19+3_"VE`d(YDA`=&:_"e5:KElSl'I%dUTC=mnscm><Gt_PX:U0%2k@UC>RSmOK^IO![;Jo&i:c-q[<6'j4J57BY4LO4(\\5:@"T?:f.:ghp%q=<9[eg'i;g1]EEJi[T/G?V]ZecqZdf0A<sp*kUb#B.`]X=83q?Xt%RA\8=D(X)/G2oGr7h#iRc`)"0tD/0*W+ct2,@7S(>b),Qq3[BNo<LUt8LF$a!f)gZ;s(0.?+#.Vt[W.VF,_!/1t6GbN>$%KW`G#%3'O`NQ2W#b,mi,M6J"L022'.hFBS=jF_enHO@S/Ce9E&q&4GPS3hOs[?j\k&V/;[,/P0P!$<)ADT]_f-MdI,D_ga]#%FWi*Z__DH@?e<j`QUTBkd";R]gO&8op<J.84NV.[ZDUIZtMHX'$5ZO)f]PC%TZnq1Mriuku(0K@dTf8Bula"U\\?^BL__7DG\F."6"s!0!Y%tk2;($K8>7l'JI%+2`o^cLebt$K>]#7(ML]/0Va^\;qlrhZFa'O#?nSOdRNquBeT&InS3E'\SgnVX,1>Sf_RDts'f]W=tF3itK%5#$]=U-XoRFJY5q>^qjJIO+6V6cD5<S.2k2bTR!P_4L@2Te2T.ZS(?'kM][<@=lI-K@2(9LuUf#96+ZgnAdk1$\,6SZLs_[.aTl%s<)lm<NNfA4PC&?&&+C$Qdsp>2q#:10ZUIUWt%#B==e;mEX-<lC.1*R@ItoLG-tl?)g5"-*1Mr=VBU5gN+[@j4>gXK\o44IQnY$7P3X_Yf/JLGpX%:b-`V&`\EA$gWoK!OBILNY.Elrc?<5D?tNGp_SVnX.]IQA$E]RuU\prJZd\7dT<7JC.NX&^N-$NAR-c]l<QR@f->GcJ29tg>me9s\lG$J6.?4fCTsg0Ljb^$^aj*V9I'E7h:cj\JD[+l,SNW'7^[`3?I:$B<&]+"DpZ-Vs#7eT1d%p%*cX?F;_-JQ5V8k@C5j@g<q5UnAjR+Et%?-URpHd(63B-$CO>B7AXIC&MM.)_fFq(d4<PtbDdkJm;7L#Pm)@29'-#[-[rkp2_5kd0s:r6GIH5b59o:pVl;U;8SJ%IX&o(dRGb*_HgT/Y$=,EDG[@Cg0eQ#X(dj8%'qmZk1[Ao;!80lrCA*;G%BP#P^XFI*p2?:'-&_Ciup%*p:\PXR-eVGpV8<)#DaEj'@DU')F&mV_!Wc%EN3/o6Gd\?Hf&1tmiq#<W7ZiZ5&BYhpt:XE[u-#Dc>0eBZh-afp(f-\J_*qRR$J%>WjSFG9Yd`d3L#Ki>VB"omTaj6D.&_%g*3_;hOBS6.$<#I*seGGbg3%/MS7eOA$Jh><r%s''<0:#a;)pGXq_6mAFHKY]"F&6hrM!Tsde?F3aAnK1J84oP~>endstream
+endobj
+xref
+0 13
+0000000000 65535 f 
+0000000073 00000 n 
+0000000114 00000 n 
+0000000221 00000 n 
+0000000333 00000 n 
+0000007848 00000 n 
+0000008106 00000 n 
+0000015244 00000 n 
+0000015502 00000 n 
+0000015571 00000 n 
+0000015854 00000 n 
+0000015920 00000 n 
+0000017489 00000 n 
+trailer
+<<
+/ID 
+[<43e4692dcfea9606b90854ef4511b7c6><43e4692dcfea9606b90854ef4511b7c6>]
+% ReportLab generated PDF document -- digest (http://www.reportlab.com)
+
+/Info 9 0 R
+/Root 8 0 R
+/Size 13
+>>
+startxref
+19161
+%%EOF
diff --git a/packages/markitdown/tests/test_pdf_tables.py b/packages/markitdown/tests/test_pdf_tables.py
new file mode 100644
index 0000000..92a79dd
--- /dev/null
+++ b/packages/markitdown/tests/test_pdf_tables.py
@@ -0,0 +1,871 @@
+#!/usr/bin/env python3 -m pytest
+"""Tests for PDF table extraction functionality."""
+import os
+import re
+import pytest
+
+from markitdown import MarkItDown
+
+TEST_FILES_DIR = os.path.join(os.path.dirname(__file__), "test_files")
+
+
+# --- Helper Functions ---
+def validate_strings(result, expected_strings, exclude_strings=None):
+    """Validate presence or absence of specific strings."""
+    text_content = result.text_content.replace("\\", "")
+    for string in expected_strings:
+        assert string in text_content, f"Expected string not found: {string}"
+    if exclude_strings:
+        for string in exclude_strings:
+            assert string not in text_content, f"Excluded string found: {string}"
+
+
+def validate_markdown_table(result, expected_headers, expected_data_samples):
+    """Validate that a markdown table exists with expected headers and data."""
+    text_content = result.text_content
+
+    # Check for markdown table structure (| header | header |)
+    assert "|" in text_content, "No markdown table markers found"
+
+    # Check headers are present
+    for header in expected_headers:
+        assert header in text_content, f"Expected table header not found: {header}"
+
+    # Check some data values are present
+    for data in expected_data_samples:
+        assert data in text_content, f"Expected table data not found: {data}"
+
+
+def extract_markdown_tables(text_content):
+    """
+    Extract all markdown tables from text content.
+    Returns a list of tables, where each table is a list of rows,
+    and each row is a list of cell values.
+    """
+    tables = []
+    lines = text_content.split("\n")
+    current_table = []
+    in_table = False
+
+    for line in lines:
+        line = line.strip()
+        if line.startswith("|") and line.endswith("|"):
+            # Skip separator rows (contain only dashes and pipes)
+            if re.match(r"^\|[\s\-|]+\|$", line):
+                continue
+            # Parse cells from the row
+            cells = [cell.strip() for cell in line.split("|")[1:-1]]
+            current_table.append(cells)
+            in_table = True
+        else:
+            if in_table and current_table:
+                tables.append(current_table)
+                current_table = []
+            in_table = False
+
+    # Don't forget the last table
+    if current_table:
+        tables.append(current_table)
+
+    return tables
+
+
+def validate_table_structure(table):
+    """
+    Validate that a table has consistent structure:
+    - All rows have the same number of columns
+    - Has at least a header row and one data row
+    """
+    if not table:
+        return False, "Table is empty"
+
+    if len(table) < 2:
+        return False, "Table should have at least header and one data row"
+
+    num_cols = len(table[0])
+    if num_cols < 2:
+        return False, f"Table should have at least 2 columns, found {num_cols}"
+
+    for i, row in enumerate(table):
+        if len(row) != num_cols:
+            return False, f"Row {i} has {len(row)} columns, expected {num_cols}"
+
+    return True, "Table structure is valid"
+
+
+class TestPdfTableExtraction:
+    """Test PDF table extraction with various PDF types."""
+
+    @pytest.fixture
+    def markitdown(self):
+        """Create MarkItDown instance."""
+        return MarkItDown()
+
+    def test_borderless_table_extraction(self, markitdown):
+        """Test extraction of borderless tables from SPARSE inventory PDF.
+
+        Expected output structure:
+        - Header: INVENTORY RECONCILIATION REPORT with Report ID, Warehouse, Date, Prepared By
+        - Pipe-separated rows with inventory data
+        - Text section: Variance Analysis with Summary Statistics
+        - More pipe-separated rows with extended inventory review
+        - Footer: Recommendations section
+        """
+        pdf_path = os.path.join(
+            TEST_FILES_DIR, "SPARSE-2024-INV-1234_borderless_table.pdf"
+        )
+
+        if not os.path.exists(pdf_path):
+            pytest.skip(f"Test file not found: {pdf_path}")
+
+        result = markitdown.convert(pdf_path)
+        text_content = result.text_content
+
+        # Validate document header content
+        expected_strings = [
+            "INVENTORY RECONCILIATION REPORT",
+            "Report ID: SPARSE-2024-INV-1234",
+            "Warehouse: Distribution Center East",
+            "Report Date: 2024-11-15",
+            "Prepared By: Sarah Martinez",
+        ]
+        validate_strings(result, expected_strings)
+
+        # Validate pipe-separated format is used
+        assert "|" in text_content, "Should have pipe separators for form-style data"
+
+        # --- Validate First Table Data (Inventory Variance) ---
+        # Validate table headers are present
+        first_table_headers = [
+            "Product Code",
+            "Location",
+            "Expected",
+            "Actual",
+            "Variance",
+            "Status",
+        ]
+        for header in first_table_headers:
+            assert header in text_content, f"Should contain header '{header}'"
+
+        # Validate first table has all expected SKUs
+        first_table_skus = ["SKU-8847", "SKU-9201", "SKU-4563", "SKU-7728"]
+        for sku in first_table_skus:
+            assert sku in text_content, f"Should contain {sku}"
+
+        # Validate first table has correct status values
+        expected_statuses = ["OK", "CRITICAL"]
+        for status in expected_statuses:
+            assert status in text_content, f"Should contain status '{status}'"
+
+        # Validate first table has location codes
+        expected_locations = ["A-12", "B-07", "C-15", "D-22", "A-08"]
+        for loc in expected_locations:
+            assert loc in text_content, f"Should contain location '{loc}'"
+
+        # --- Validate Second Table Data (Extended Inventory Review) ---
+        # Validate second table headers
+        second_table_headers = [
+            "Category",
+            "Unit Cost",
+            "Total Value",
+            "Last Audit",
+            "Notes",
+        ]
+        for header in second_table_headers:
+            assert header in text_content, f"Should contain header '{header}'"
+
+        # Validate second table has all expected SKUs (10 products)
+        second_table_skus = [
+            "SKU-8847",
+            "SKU-9201",
+            "SKU-4563",
+            "SKU-7728",
+            "SKU-3345",
+            "SKU-5512",
+            "SKU-6678",
+            "SKU-7789",
+            "SKU-2234",
+            "SKU-1123",
+        ]
+        for sku in second_table_skus:
+            assert sku in text_content, f"Should contain {sku}"
+
+        # Validate second table has categories
+        expected_categories = ["Electronics", "Hardware", "Software", "Accessories"]
+        for category in expected_categories:
+            assert category in text_content, f"Should contain category '{category}'"
+
+        # Validate second table has cost values (spot check)
+        expected_costs = ["$45.00", "$32.50", "$120.00", "$15.75"]
+        for cost in expected_costs:
+            assert cost in text_content, f"Should contain cost '{cost}'"
+
+        # Validate second table has note values
+        expected_notes = ["Verified", "Critical", "Pending"]
+        for note in expected_notes:
+            assert note in text_content, f"Should contain note '{note}'"
+
+        # --- Validate Analysis Text Section ---
+        analysis_strings = [
+            "Variance Analysis:",
+            "Summary Statistics:",
+            "Total Variance Cost: $4,287.50",
+            "Critical Items: 1",
+            "Overall Accuracy: 97.2%",
+            "Recommendations:",
+        ]
+        validate_strings(result, analysis_strings)
+
+        # --- Validate Document Structure Order ---
+        # Verify sections appear in correct order
+        # Note: Using flexible patterns since column merging may occur based on gap detection
+        import re
+
+        header_pos = text_content.find("INVENTORY RECONCILIATION REPORT")
+        # Look for Product Code header - may be in same column as Location or separate
+        first_table_match = re.search(r"\|\s*Product Code", text_content)
+        variance_pos = text_content.find("Variance Analysis:")
+        extended_review_pos = text_content.find("Extended Inventory Review:")
+        # Second table - look for SKU entries after extended review section
+        # The table may not have pipes on every row due to paragraph detection
+        second_table_pos = -1
+        if extended_review_pos != -1:
+            # Look for either "| Product Code" or "Product Code" as table header
+            second_table_match = re.search(
+                r"Product Code.*Category", text_content[extended_review_pos:]
+            )
+            if second_table_match:
+                # Adjust position to be relative to full text
+                second_table_pos = extended_review_pos + second_table_match.start()
+        recommendations_pos = text_content.find("Recommendations:")
+
+        positions = {
+            "header": header_pos,
+            "first_table": first_table_match.start() if first_table_match else -1,
+            "variance_analysis": variance_pos,
+            "extended_review": extended_review_pos,
+            "second_table": second_table_pos,
+            "recommendations": recommendations_pos,
+        }
+
+        # All sections should be found
+        for name, pos in positions.items():
+            assert pos != -1, f"Section '{name}' not found in output"
+
+        # Verify correct order
+        assert (
+            positions["header"] < positions["first_table"]
+        ), "Header should come before first table"
+        assert (
+            positions["first_table"] < positions["variance_analysis"]
+        ), "First table should come before Variance Analysis"
+        assert (
+            positions["variance_analysis"] < positions["extended_review"]
+        ), "Variance Analysis should come before Extended Review"
+        assert (
+            positions["extended_review"] < positions["second_table"]
+        ), "Extended Review should come before second table"
+        assert (
+            positions["second_table"] < positions["recommendations"]
+        ), "Second table should come before Recommendations"
+
+    def test_borderless_table_no_duplication(self, markitdown):
+        """Test that borderless table content is not duplicated excessively."""
+        pdf_path = os.path.join(
+            TEST_FILES_DIR, "SPARSE-2024-INV-1234_borderless_table.pdf"
+        )
+
+        if not os.path.exists(pdf_path):
+            pytest.skip(f"Test file not found: {pdf_path}")
+
+        result = markitdown.convert(pdf_path)
+        text_content = result.text_content
+
+        # Count occurrences of unique table data - should not be excessively duplicated
+        # SKU-8847 appears in both tables, plus possibly once in summary text
+        sku_count = text_content.count("SKU-8847")
+        # Should appear at most 4 times (2 tables + minor text references), not more
+        assert (
+            sku_count <= 4
+        ), f"SKU-8847 appears too many times ({sku_count}), suggests duplication issue"
+
+    def test_borderless_table_correct_position(self, markitdown):
+        """Test that tables appear in correct positions relative to text."""
+        pdf_path = os.path.join(
+            TEST_FILES_DIR, "SPARSE-2024-INV-1234_borderless_table.pdf"
+        )
+
+        if not os.path.exists(pdf_path):
+            pytest.skip(f"Test file not found: {pdf_path}")
+
+        result = markitdown.convert(pdf_path)
+        text_content = result.text_content
+
+        # Verify content order - header should come before table content, which should come before analysis
+        header_pos = text_content.find("Prepared By: Sarah Martinez")
+        # Look for Product Code in any pipe-separated format
+        product_code_pos = text_content.find("Product Code")
+        variance_pos = text_content.find("Variance Analysis:")
+
+        assert header_pos != -1, "Header should be found"
+        assert product_code_pos != -1, "Product Code should be found"
+        assert variance_pos != -1, "Variance Analysis should be found"
+
+        assert (
+            header_pos < product_code_pos < variance_pos
+        ), "Product data should appear between header and Variance Analysis"
+
+        # Second table content should appear after "Extended Inventory Review"
+        extended_review_pos = text_content.find("Extended Inventory Review:")
+        # Look for Category header which is in second table
+        category_pos = text_content.find("Category")
+        recommendations_pos = text_content.find("Recommendations:")
+
+        if (
+            extended_review_pos != -1
+            and category_pos != -1
+            and recommendations_pos != -1
+        ):
+            # Find Category position after Extended Inventory Review
+            category_after_review = text_content.find("Category", extended_review_pos)
+            if category_after_review != -1:
+                assert (
+                    extended_review_pos < category_after_review < recommendations_pos
+                ), "Extended review table should appear between Extended Inventory Review and Recommendations"
+
+    def test_receipt_pdf_extraction(self, markitdown):
+        """Test extraction of receipt PDF (no tables, formatted text).
+
+        Expected output structure:
+        - Store header: TECHMART ELECTRONICS with address
+        - Transaction info: Store #, date, TXN, Cashier, Register
+        - Line items: 6 products with prices and member discounts
+        - Totals: Subtotal, Member Discount, Sales Tax, Rewards, TOTAL
+        - Payment info: Visa Card, Auth, Ref
+        - Rewards member info: Name, ID, Points
+        - Return policy and footer
+        """
+        pdf_path = os.path.join(
+            TEST_FILES_DIR, "RECEIPT-2024-TXN-98765_retail_purchase.pdf"
+        )
+
+        if not os.path.exists(pdf_path):
+            pytest.skip(f"Test file not found: {pdf_path}")
+
+        result = markitdown.convert(pdf_path)
+        text_content = result.text_content
+
+        # --- Validate Store Header ---
+        store_header = [
+            "TECHMART ELECTRONICS",
+            "4567 Innovation Blvd",
+            "San Francisco, CA 94103",
+            "(415) 555-0199",
+        ]
+        validate_strings(result, store_header)
+
+        # --- Validate Transaction Info ---
+        transaction_info = [
+            "Store #0342 - Downtown SF",
+            "11/23/2024",
+            "TXN: TXN-98765-2024",
+            "Cashier: Emily Rodriguez",
+            "Register: POS-07",
+        ]
+        validate_strings(result, transaction_info)
+
+        # --- Validate Line Items (6 products) ---
+        line_items = [
+            # Product 1: Headphones
+            "Wireless Noise-Cancelling",
+            "Headphones - Premium Black",
+            "AUDIO-5521",
+            "$349.99",
+            "$299.99",
+            # Product 2: USB-C Hub
+            "USB-C Hub 7-in-1 Adapter",
+            "ACC-8834",
+            "$79.99",
+            "$159.98",
+            # Product 3: Portable SSD
+            "Portable SSD 2TB",
+            "STOR-2241",
+            "$289.00",
+            "$260.00",
+            # Product 4: Wireless Mouse
+            "Ergonomic Wireless Mouse",
+            "ACC-9012",
+            "$59.99",
+            # Product 5: Screen Cleaning Kit
+            "Screen Cleaning Kit",
+            "CARE-1156",
+            "$12.99",
+            "$38.97",
+            # Product 6: HDMI Cable
+            "HDMI 2.1 Cable 6ft",
+            "CABLE-7789",
+            "$24.99",
+            "$44.98",
+        ]
+        validate_strings(result, line_items)
+
+        # --- Validate Totals ---
+        totals = [
+            "SUBTOTAL",
+            "$863.91",
+            "Member Discount",
+            "Sales Tax (8.5%)",
+            "$66.23",
+            "Rewards Applied",
+            "-$25.00",
+            "TOTAL",
+            "$821.14",
+        ]
+        validate_strings(result, totals)
+
+        # --- Validate Payment Info ---
+        payment_info = [
+            "PAYMENT METHOD",
+            "Visa Card ending in 4782",
+            "Auth: 847392",
+            "REF-20241123-98765",
+        ]
+        validate_strings(result, payment_info)
+
+        # --- Validate Rewards Member Info ---
+        rewards_info = [
+            "REWARDS MEMBER",
+            "Sarah Mitchell",
+            "ID: TM-447821",
+            "Points Earned: 821",
+            "Total Points: 3,247",
+        ]
+        validate_strings(result, rewards_info)
+
+        # --- Validate Return Policy & Footer ---
+        footer_info = [
+            "RETURN POLICY",
+            "Returns within 30 days",
+            "Receipt required",
+            "Thank you for shopping!",
+            "www.techmart.example.com",
+        ]
+        validate_strings(result, footer_info)
+
+        # --- Validate Document Structure Order ---
+        positions = {
+            "store_header": text_content.find("TECHMART ELECTRONICS"),
+            "transaction": text_content.find("TXN: TXN-98765-2024"),
+            "first_item": text_content.find("Wireless Noise-Cancelling"),
+            "subtotal": text_content.find("SUBTOTAL"),
+            "total": text_content.find("TOTAL"),
+            "payment": text_content.find("PAYMENT METHOD"),
+            "rewards": text_content.find("REWARDS MEMBER"),
+            "return_policy": text_content.find("RETURN POLICY"),
+        }
+
+        # All sections should be found
+        for name, pos in positions.items():
+            assert pos != -1, f"Section '{name}' not found in output"
+
+        # Verify correct order
+        assert (
+            positions["store_header"] < positions["transaction"]
+        ), "Store header should come before transaction"
+        assert (
+            positions["transaction"] < positions["first_item"]
+        ), "Transaction should come before items"
+        assert (
+            positions["first_item"] < positions["subtotal"]
+        ), "Items should come before subtotal"
+        assert (
+            positions["subtotal"] < positions["total"]
+        ), "Subtotal should come before total"
+        assert (
+            positions["total"] < positions["payment"]
+        ), "Total should come before payment"
+        assert (
+            positions["payment"] < positions["rewards"]
+        ), "Payment should come before rewards"
+        assert (
+            positions["rewards"] < positions["return_policy"]
+        ), "Rewards should come before return policy"
+
+    def test_multipage_invoice_extraction(self, markitdown):
+        """Test extraction of multipage invoice PDF with form-style layout.
+
+        Expected output: Pipe-separated format with clear cell boundaries.
+        Form data should be extracted with pipes indicating column separations.
+        """
+        pdf_path = os.path.join(TEST_FILES_DIR, "REPAIR-2022-INV-001_multipage.pdf")
+
+        if not os.path.exists(pdf_path):
+            pytest.skip(f"Test file not found: {pdf_path}")
+
+        result = markitdown.convert(pdf_path)
+        text_content = result.text_content
+
+        # Validate basic content is extracted
+        expected_strings = [
+            "ZAVA AUTO REPAIR",
+            "Collision Repair",
+            "Redmond, WA",
+            "Gabriel Diaz",
+            "Jeep",
+            "Grand Cherokee",
+            "Parts",
+            "Body Labor",
+            "Paint Labor",
+            "GRAND TOTAL",
+            # Second page content
+            "Bruce Wayne",
+            "Batmobile",
+        ]
+        validate_strings(result, expected_strings)
+
+        # Validate pipe-separated table format
+        # Form-style documents should use pipes to separate cells
+        assert "|" in text_content, "Form-style PDF should contain pipe separators"
+
+        # Validate key form fields are properly separated
+        # These patterns check that label and value are in separate cells
+        # Note: cells may have padding spaces for column alignment
+        import re
+
+        assert re.search(
+            r"\| Insured name\s*\|", text_content
+        ), "Insured name should be in its own cell"
+        assert re.search(
+            r"\| Gabriel Diaz\s*\|", text_content
+        ), "Gabriel Diaz should be in its own cell"
+        assert re.search(
+            r"\| Year\s*\|", text_content
+        ), "Year label should be in its own cell"
+        assert re.search(
+            r"\| 2022\s*\|", text_content
+        ), "Year value should be in its own cell"
+
+        # Validate table structure for estimate totals
+        assert (
+            re.search(r"\| Hours\s*\|", text_content) or "Hours |" in text_content
+        ), "Hours column header should be present"
+        assert (
+            re.search(r"\| Rate\s*\|", text_content) or "Rate |" in text_content
+        ), "Rate column header should be present"
+        assert (
+            re.search(r"\| Cost\s*\|", text_content) or "Cost |" in text_content
+        ), "Cost column header should be present"
+
+        # Validate numeric values are extracted
+        assert "2,100" in text_content, "Parts cost should be extracted"
+        assert "300" in text_content, "Body labor cost should be extracted"
+        assert "225" in text_content, "Paint labor cost should be extracted"
+        assert "5,738" in text_content, "Grand total should be extracted"
+
+        # Validate second page content (Bruce Wayne invoice)
+        assert "Bruce Wayne" in text_content, "Second page customer name"
+        assert "Batmobile" in text_content, "Second page vehicle model"
+        assert "211,522" in text_content, "Second page grand total"
+
+        # Validate disclaimer text is NOT in table format (long paragraph)
+        # The disclaimer should be extracted as plain text, not pipe-separated
+        assert (
+            "preliminary estimate" in text_content.lower()
+        ), "Disclaimer text should be present"
+
+    def test_academic_pdf_extraction(self, markitdown):
+        """Test extraction of academic paper PDF (scientific document).
+
+        Expected output: Plain text without tables or pipe characters.
+        Scientific documents should be extracted as flowing text with proper spacing,
+        not misinterpreted as tables.
+        """
+        pdf_path = os.path.join(TEST_FILES_DIR, "test.pdf")
+
+        if not os.path.exists(pdf_path):
+            pytest.skip(f"Test file not found: {pdf_path}")
+
+        result = markitdown.convert(pdf_path)
+        text_content = result.text_content
+
+        # Validate academic paper content with proper spacing
+        expected_strings = [
+            "Introduction",
+            "Large language models",  # Should have proper spacing, not "Largelanguagemodels"
+            "agents",
+            "multi-agent",  # Should be properly hyphenated
+        ]
+        validate_strings(result, expected_strings)
+
+        # Validate proper text formatting (words separated by spaces)
+        assert "LLMs" in text_content, "Should contain 'LLMs' acronym"
+        assert "reasoning" in text_content, "Should contain 'reasoning'"
+        assert "observations" in text_content, "Should contain 'observations'"
+
+        # Ensure content is not empty and has proper length
+        assert len(text_content) > 1000, "Academic PDF should have substantial content"
+
+        # Scientific documents should NOT have tables or pipe characters
+        assert (
+            "|" not in text_content
+        ), "Scientific document should not contain pipe characters (no tables)"
+
+        # Verify no markdown tables were extracted
+        tables = extract_markdown_tables(text_content)
+        assert (
+            len(tables) == 0
+        ), f"Scientific document should have no tables, found {len(tables)}"
+
+        # Verify text is properly formatted with spaces between words
+        # Check that common phrases are NOT joined together (which would indicate bad extraction)
+        assert (
+            "Largelanguagemodels" not in text_content
+        ), "Text should have proper spacing, not joined words"
+        assert (
+            "multiagentconversations" not in text_content.lower()
+        ), "Text should have proper spacing between words"
+
+    def test_scanned_pdf_handling(self, markitdown):
+        """Test handling of scanned/image-based PDF (no text layer).
+
+        Expected output: Empty - scanned PDFs without OCR have no text layer.
+        """
+        pdf_path = os.path.join(
+            TEST_FILES_DIR, "MEDRPT-2024-PAT-3847_medical_report_scan.pdf"
+        )
+
+        if not os.path.exists(pdf_path):
+            pytest.skip(f"Test file not found: {pdf_path}")
+
+        result = markitdown.convert(pdf_path)
+
+        # Scanned PDFs without OCR have no text layer, so extraction should be empty
+        assert (
+            result is not None
+        ), "Converter should return a result even for scanned PDFs"
+        assert result.text_content is not None, "text_content should not be None"
+
+        # Verify extraction is empty (no text layer in scanned PDF)
+        assert (
+            result.text_content.strip() == ""
+        ), f"Scanned PDF should have empty extraction, got: '{result.text_content[:100]}...'"
+
+
+class TestPdfTableMarkdownFormat:
+    """Test that extracted tables have proper markdown formatting."""
+
+    @pytest.fixture
+    def markitdown(self):
+        """Create MarkItDown instance."""
+        return MarkItDown()
+
+    def test_markdown_table_has_pipe_format(self, markitdown):
+        """Test that form-style PDFs have pipe-separated format."""
+        pdf_path = os.path.join(
+            TEST_FILES_DIR, "SPARSE-2024-INV-1234_borderless_table.pdf"
+        )
+
+        if not os.path.exists(pdf_path):
+            pytest.skip(f"Test file not found: {pdf_path}")
+
+        result = markitdown.convert(pdf_path)
+        text_content = result.text_content
+
+        # Find rows with pipes
+        lines = text_content.split("\n")
+        pipe_rows = [
+            line for line in lines if line.startswith("|") and line.endswith("|")
+        ]
+
+        assert len(pipe_rows) > 0, "Should have pipe-separated rows"
+
+        # Check that Product Code appears in a pipe-separated row
+        product_code_found = any("Product Code" in row for row in pipe_rows)
+        assert product_code_found, "Product Code should be in pipe-separated format"
+
+    def test_markdown_table_columns_have_pipes(self, markitdown):
+        """Test that form-style PDF columns are separated with pipes."""
+        pdf_path = os.path.join(
+            TEST_FILES_DIR, "SPARSE-2024-INV-1234_borderless_table.pdf"
+        )
+
+        if not os.path.exists(pdf_path):
+            pytest.skip(f"Test file not found: {pdf_path}")
+
+        result = markitdown.convert(pdf_path)
+        text_content = result.text_content
+
+        # Find table rows and verify column structure
+        lines = text_content.split("\n")
+        table_rows = [
+            line for line in lines if line.startswith("|") and line.endswith("|")
+        ]
+
+        assert len(table_rows) > 0, "Should have markdown table rows"
+
+        # Check that at least some rows have multiple columns (pipes)
+        multi_col_rows = [row for row in table_rows if row.count("|") >= 3]
+        assert (
+            len(multi_col_rows) > 5
+        ), f"Should have rows with multiple columns, found {len(multi_col_rows)}"
+
+
+class TestPdfTableStructureConsistency:
+    """Test that extracted tables have consistent structure across all PDF types."""
+
+    @pytest.fixture
+    def markitdown(self):
+        """Create MarkItDown instance."""
+        return MarkItDown()
+
+    def test_borderless_table_structure(self, markitdown):
+        """Test that borderless table PDF has pipe-separated structure."""
+        pdf_path = os.path.join(
+            TEST_FILES_DIR, "SPARSE-2024-INV-1234_borderless_table.pdf"
+        )
+
+        if not os.path.exists(pdf_path):
+            pytest.skip(f"Test file not found: {pdf_path}")
+
+        result = markitdown.convert(pdf_path)
+        text_content = result.text_content
+
+        # Should have pipe-separated content
+        assert "|" in text_content, "Borderless table PDF should have pipe separators"
+
+        # Check that key content is present
+        assert "Product Code" in text_content, "Should contain Product Code"
+        assert "SKU-8847" in text_content, "Should contain first SKU"
+        assert "SKU-9201" in text_content, "Should contain second SKU"
+
+    def test_multipage_invoice_table_structure(self, markitdown):
+        """Test that multipage invoice PDF has pipe-separated format."""
+        pdf_path = os.path.join(TEST_FILES_DIR, "REPAIR-2022-INV-001_multipage.pdf")
+
+        if not os.path.exists(pdf_path):
+            pytest.skip(f"Test file not found: {pdf_path}")
+
+        result = markitdown.convert(pdf_path)
+        text_content = result.text_content
+
+        # Should have pipe-separated content
+        assert "|" in text_content, "Invoice PDF should have pipe separators"
+
+        # Find rows with pipes
+        lines = text_content.split("\n")
+        pipe_rows = [
+            line for line in lines if line.startswith("|") and line.endswith("|")
+        ]
+
+        assert (
+            len(pipe_rows) > 10
+        ), f"Should have multiple pipe-separated rows, found {len(pipe_rows)}"
+
+        # Check that some rows have multiple columns
+        multi_col_rows = [row for row in pipe_rows if row.count("|") >= 4]
+        assert len(multi_col_rows) > 5, "Should have rows with 3+ columns"
+
+    def test_receipt_has_no_tables(self, markitdown):
+        """Test that receipt PDF doesn't incorrectly extract tables from formatted text."""
+        pdf_path = os.path.join(
+            TEST_FILES_DIR, "RECEIPT-2024-TXN-98765_retail_purchase.pdf"
+        )
+
+        if not os.path.exists(pdf_path):
+            pytest.skip(f"Test file not found: {pdf_path}")
+
+        result = markitdown.convert(pdf_path)
+        tables = extract_markdown_tables(result.text_content)
+
+        # Receipt should not have markdown tables extracted
+        # (it's formatted text, not tabular data)
+        # If tables are extracted, they should be minimal/empty
+        total_table_rows = sum(len(t) for t in tables)
+        assert (
+            total_table_rows < 5
+        ), f"Receipt should not have significant tables, found {total_table_rows} rows"
+
+    def test_scanned_pdf_no_tables(self, markitdown):
+        """Test that scanned PDF has empty extraction and no tables."""
+        pdf_path = os.path.join(
+            TEST_FILES_DIR, "MEDRPT-2024-PAT-3847_medical_report_scan.pdf"
+        )
+
+        if not os.path.exists(pdf_path):
+            pytest.skip(f"Test file not found: {pdf_path}")
+
+        result = markitdown.convert(pdf_path)
+
+        # Scanned PDF with no text layer should have empty extraction
+        assert (
+            result.text_content.strip() == ""
+        ), "Scanned PDF should have empty extraction"
+
+        tables = extract_markdown_tables(result.text_content)
+
+        # Scanned PDF with no text layer should have no tables
+        assert len(tables) == 0, "Scanned PDF should have no extracted tables"
+
+    def test_all_pdfs_table_rows_consistent(self, markitdown):
+        """Test that all PDF tables have rows with pipe-separated content.
+
+        Note: With gap-based column detection, rows may have different column counts
+        depending on how content is spaced in the PDF. What's important is that each
+        row has pipe separators and the content is readable.
+        """
+        pdf_files = [
+            "SPARSE-2024-INV-1234_borderless_table.pdf",
+            "REPAIR-2022-INV-001_multipage.pdf",
+            "RECEIPT-2024-TXN-98765_retail_purchase.pdf",
+            "test.pdf",
+        ]
+
+        for pdf_file in pdf_files:
+            pdf_path = os.path.join(TEST_FILES_DIR, pdf_file)
+            if not os.path.exists(pdf_path):
+                continue
+
+            result = markitdown.convert(pdf_path)
+            tables = extract_markdown_tables(result.text_content)
+
+            for table_idx, table in enumerate(tables):
+                if not table:
+                    continue
+
+                # Verify each row has at least one column (pipe-separated content)
+                for row_idx, row in enumerate(table):
+                    assert (
+                        len(row) >= 1
+                    ), f"{pdf_file}: Table {table_idx}, row {row_idx} has no columns"
+
+                    # Verify the row has non-empty content
+                    row_content = " ".join(cell.strip() for cell in row)
+                    assert (
+                        len(row_content.strip()) > 0
+                    ), f"{pdf_file}: Table {table_idx}, row {row_idx} is empty"
+
+    def test_borderless_table_data_integrity(self, markitdown):
+        """Test that borderless table extraction preserves data integrity."""
+        pdf_path = os.path.join(
+            TEST_FILES_DIR, "SPARSE-2024-INV-1234_borderless_table.pdf"
+        )
+
+        if not os.path.exists(pdf_path):
+            pytest.skip(f"Test file not found: {pdf_path}")
+
+        result = markitdown.convert(pdf_path)
+        tables = extract_markdown_tables(result.text_content)
+
+        assert len(tables) >= 2, "Should have at least 2 tables"
+
+        # Check first table has expected SKU data
+        first_table = tables[0]
+        table_text = str(first_table)
+        assert "SKU-8847" in table_text, "First table should contain SKU-8847"
+        assert "SKU-9201" in table_text, "First table should contain SKU-9201"
+
+        # Check second table has expected category data
+        second_table = tables[1]
+        table_text = str(second_table)
+        assert "Electronics" in table_text, "Second table should contain Electronics"
+        assert "Hardware" in table_text, "Second table should contain Hardware"