“Find our most similar past projects”
Quote from precedent, not from a blank page.
A new RFQ and drawings in, your most similar past projects out, with the reasons why.
Why teams hand it over
Someone always says "we've done one like this", then loses an afternoon hunting for it, or the estimate starts from zero. Your past projects are your best pricing data, and most days they're unreachable.
Capable where it counts. Careful where it matters.
- Extracts the attributes that matter from the RFQ and drawings: ratings, dimensions, performance, OEM.
- Shows you what it read, and lets you correct it before searching.
- Ranks your whole history with per-attribute match scores.
- Traces every value to a source document and page.
- Filters by won/lost, year or OEM, re-ranks instantly.
- Deterministic: same query, same ranking, every time.
A simulated run, on synthetic documents.
Made-up companies and numbers. The workflow is the real one.
Watch it read a new RFQ, then rank your past projects.
What you get back
- 01A ranked shortlist of your most similar projects
- 02Per-attribute match scores, the why behind each
- 03References into source proposals and drawings
- 04An index that gets sharper with use
Common questions about this task
Is this a black-box AI search?
No. Extraction is AI; the ranking is a deterministic score over named attributes. Every result shows its per-attribute match.
What if it misreads a drawing?
You see the extracted values before any search runs and can correct them. Corrections are remembered.
How much history do we need?
Useful from a handful of projects, scales to hundreds. Indexing is one-time; search is instant.
Send a real tender. Get the output back.
Hand Elora Grid one real task and judge the result yourself.