TRASER sits between your documents and any AI. Ask a question, get the answer — plus a marked-up proof document showing what the AI used, what it ignored, and what it may have missed.
| Item | Qty | Amount |
|---|---|---|
| Structural steel beams (W12x26) | 18 | $21,600 |
| Rebar #5, 20ft | 340 | $14,280 |
| Freight & handling | — | $8,450 |
In engineering, a redline is the marked-up drawing that shows what actually happened. TRASER gives every AI answer a redline: a color-coded overlay on your original document.
The AI relied on this to form its answer. Every claim links to an evidence ID.
OCR extracted it, but the AI didn't factor it in. You decide if that matters.
Possibly misread or missed — handwriting, stamps, poor scans. Flagged for human eyes.
A reviewer fixed or confirmed it. Corrections are stored in the audit trail.
Background content — headers, footers, boilerplate — not relevant to the question.
PDFs, photos, scans — even messy ones. Handwriting, tables, and signatures included.
Enterprise-grade OCR maps every element to its exact location and a confidence score.
Plain English. "What's the total due?" "Does the PO number match?" "Who signed this?"
The AI must point to evidence IDs for every claim — no evidence, no answer.
Click any highlight to see what was extracted. Accept, correct, or reject — your call is recorded.
Annotated PDF, original file hash, OCR data, evidence IDs, corrections, timestamps, and model used.
TRASER builds memory by workflow — every verified document makes the next one faster.
Verify totals, PO matches, and payment terms before money moves. Catch what the AI didn't read.
Proof-of-delivery signatures, change orders, site photos — redlined the way your industry already works.
Know which clauses the AI actually weighed when it summarized a 40-page agreement.
Extract data from papers and scans with a verifiable trail from claim back to page and pixel.
Trust AI study help because you can see exactly which passage every answer came from.
Every processed document exports an audit package: who, what, when, which model, what changed.
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