aakashprasad91

This is exactly the hard part symbols aren’t enough when each drafter overloads them, so we lean on the annotation + schedule context (fixture tags, notes like “DIM,” control zones, panel/ckt callouts, and control intents) to disambiguate.

Yep, exactly, when layer data survives the PDF export, it’s a huge help. We use it as a weak signal for clustering and object grouping, but never rely on it fully since it’s often inconsistent or stripped. When it’s there, accuracy and speed both improve noticeably.

Starting on their first project! Thank you!

Awesome — thank you! Easiest is email: [email protected] or they can book a demo call on our website or upload plans directly on website. If they can share (1) a representative drawing/spec set (or a small sample) + (2) what trade/Division they focus on, we can run it and send back findings with sheet refs.

We do best on CAD-originated PDFs where we can use the underlying vector data, but we can run on scanned/hand-drawn sets too. In that case we rely more on image-based detection + OCR (no clean vector layer), so accuracy depends on scan quality, contrast, and how consistent the annotations are. We’ve had success on some older/detail-heavy scans, but it’s definitely a harder mode. If you have a representative “old-school” set, we’d love to run it and show you where it works well vs where it struggles.

Great question. By “vector geometry” we mean we’re using the underlying CAD-style vector data embedded in many PDFs (lines, arcs, polylines, hatches, etc.), not just raster images. We reconstruct objects and regions from that geometry, then fuse it with OCR (for annotations, tags, labels) and a detection model that operates on rendered tiles. The detector + OCR tells us what something is; the vector layer tells us exactly where and how it’s shaped so we can run dimension/clearance and cross-sheet checks reliably.

Great point! Owner’s reps and commissioning teams are becoming one of the fastest-growing user groups for us. At SD/DD we can surface coordination risks early, highlight spec–drawing mismatches, and give owners a clearer picture of design completeness before things get locked in. If you’re open to it, we’d love to run a sample SD/DD set from your world and see what’s most useful.

Happy to swap notes. If you send a representative lighting plan set, we can run it and share how the detector clusters, resolves, and cross-references symbols across sheets. Always excited to compare approaches with teams solving adjacent problems.

Hallucinations still happen occasionally, but we bias heavily toward high-confidence findings so noise stays low. On typical projects we surface a few hundred coordination issues that are real, observable conflicts across sheets rather than speculative checks. We’re actively improving precision by learning from every false positive customers flag. We show you the drawings, specs, etc. so you can verify it yourself not just trust the AI.

Yes today users simply gather the sheets for whatever phase they want reviewed (DD, 80% CDs, 100% CDs, etc.), ZIP them or upload PDFs directly, and the system handles the rest. It auto-detects disciplines, reconstructs callout graphs, and runs checks across the full set. We're also adding integrations with ACC/Procore/Revit so sheet aggregation becomes automatic.

That comment comes across as racially loaded and isn’t helpful. If you ran into a real issue, I’m happy to take a look.

Could you share a bit more about what didn’t work on your end?

Today the workflow is simple: users just drag-and-drop the full drawing/spec set (ZIP or PDFs) for whatever phase they want reviewed. The system automatically splits sheets by discipline, reconstructs callout relationships, and runs the checks. We’ll be adding integrations with ACC/Procore/Revit exports so this becomes even more automated.

Symbol variation is a huge challenge across firms.

Our approach mixes OCR, vector geometry, and learned embeddings so the model can recognize a symbol plus its surrounding annotations (e.g., “6-15R,” “DIM,” “GFCI”).

When symbols differ by drafter, the system leans heavily on the textual/graph context so it still resolves meaning accurately. We’re actively expanding our electrical symbol library and would love sample sets from your workflow.

Yes one of the biggest values of our system is reducing “noise.” Instead of surfacing 2,000 micro-clashes, we cluster findings into higher-order issues (e.g., “all conflicts caused by this duct run” or “all lighting mismatches tied to this dimming spec”). We’re not a BIM viewer yet, but we do map issues back to sheet locations, callouts, and detail references so teams can navigate directly to the real source of the problem.