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.
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.
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.
We store files securely on AWS with strict access controls, encryption in transit and at rest, and zero sharing outside the file owner’s account. Only our engineers can access a project for debugging and only if the customer explicitly allows it. We can also offer an enterprise option with private cloud/VPC deployment for firms that require even tighter controls. Users can delete all files permanently at any time.
We parse symbols using a mix of vector geometry, OCR, and learned detection for common architectural/MEP symbols. Cross-discipline checks are a big focus as we already flag mismatches between architectural, structural, and MEP sheets, and we’re expanding into deeper electrical/mechanical spec alignment next. Would love to hear which symbols matter most in your workflow so we can improve coverage.
We’d love that — perfect use case. Send a recent set and we’ll run a discounted comparison so you can see what we catch vs. what surfaced during construction. If helpful, we can hop on a quick call to walk through results and collect feedback. Email me [email protected]
Most teams run us late DD through CD anywhere the set is stable enough that coordination issues matter. Subs especially like running it pre-bid at ~80–100% CDs so they don’t inherit coordination risk. Earlier checks also help designers tighten the set before hand-offs, so value shows up at multiple stages. Eventually the goal is to be continuous QA tool including during construction by pulling in field data too and comparing to drawings and specs. Like drawings showed X size and field photos show Y size.
We see that a lot — specs that are clearly boilerplate or outdated relative to the drawings. Our goal isn’t to force a change, but to surface where the specs and drawings diverge so the designer can quickly decide what’s intentional vs what’s baggage. “Flag + context for fast human judgment” is the philosophy.