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Why isn't Beam's AI reading my file correctly?

If Beam’s AI is not reading your PDF, missing line items, skipping details, or producing an incomplete estimate, the issue is usually related to file quality or formatting.

1. The File Is a Scanned PDF (Not Text-Based)

What happens:
If your plan set was scanned as an image (rather than exported directly from design software), the AI cannot “see” text in the usual way. It must rely on optical character recognition (OCR), which is less accurate.

Common signs:

  • You can’t highlight text in the PDF.

  • Sheet numbers or callouts aren’t searchable.

  • Text appears slightly blurry when zoomed in.

Best practice:

  • Export directly from Revit, AutoCAD, Bluebeam, or your design software as a vector-based PDF.

  • Avoid printing and re-scanning digital plans.

2. Low Resolution or Blurry Sheets

Low-resolution scans reduce the clarity of small text (dimensions, callouts, detail references). The AI may misread numbers or miss annotations entirely.

Common signs:

  • Text looks pixelated when zoomed in.

  • Dimensions are difficult to read even for humans.

  • Fine linework looks fuzzy.

Best practice:

  • Export at 300 DPI or higher.

  • Avoid compressed “smallest file size” PDF settings.

3. Flattened Drawings

When vector drawings are flattened into a single image layer, the AI loses access to structured text and linework data.

Common signs:

  • The entire sheet behaves like one image.

  • No selectable text.

  • Larger file sizes than expected.

Best practice:

  • Preserve vector data when exporting.

  • Avoid unnecessary “print to PDF” workflows.

4. Handwritten Markups

Handwritten notes, redlines, or sketch annotations can be difficult for AI systems to interpret — especially if handwriting is unclear.

Common signs:

  • AI ignores handwritten comments.

  • Numbers or markups are misinterpreted.

Best practice:

  • Use typed annotations when possible.

  • Ensure handwritten notes are dark and legible.

5. Unusual Fonts or Custom Symbol Sets

Some plan sets use specialized fonts or proprietary symbol libraries that don’t translate cleanly when exported.

Common signs:

  • Symbols appear as boxes or incorrect characters.

  • Legends don’t align with sheet symbols.

Best practice:

  • Embed fonts during PDF export.

  • Use standard text formatting when possible.

6. Overly Compressed Files

Heavy compression can degrade small text, thin lineweights, and details.

Common signs:

  • Extremely small file size for a large plan set.

  • Noticeable quality loss when zooming.

Best practice:

  • Avoid aggressive compression.

  • Prioritize clarity over file size.

7. Extremely Large or Combined Plan Sets

Very large multi-volume plan sets (hundreds of sheets combined into one file) can make navigation and sheet indexing harder.

Common signs:

  • AI responses fail or reference incorrect sheets.

  • Slower response times.

Best practice:

  • Split into logical volumes (e.g., Arch, Structural, MEP).

8. Missing or Inconsistent Sheet Titles

What happens:
Beam relies on sheet numbers and titles to understand context. Inconsistent naming can reduce accuracy.

Common signs:

  • AI struggles to locate specific sheets.

  • Cross-discipline references aren’t detected.

Best practice:

  • Use standard sheet naming conventions.

  • Ensure sheet numbers are clearly visible and consistent.

How to Ensure the Best Results

For optimal AI performance:

  • Export vector-based PDFs directly from design software

  • Use high resolution (300 DPI+)

  • Embed fonts

  • Avoid scans whenever possible

  • Keep sheet naming clear and consistent

If you're unsure whether your file is text-based, try selecting text in your PDF viewer. If you can highlight it, the AI likely can read it clearly too.