Document intelligence + legal reasoning
EvolveDocs classifies, extracts, and forensically reviews thousands of documents under deadline pressure — then runs every finding through domain-specific rule layers built to flag the failure modes legal-AI tools are notorious for. Fields checked against the document, not just extracted from it.
Every document runs through five domain rule sets before findings reach a reviewer. Output is checked against document-internal evidence — not just generated.
Adversarial multi-perspective deliberation over one shared record, relationship and timeline analysis across thousands of documents, and citation-checked Q&A with closed-loop knowledge retrieval.
The difference between a platform that connects the evidence across the whole record — and shows its work — and one that retrieves documents mentioning matching keywords. Your analysis; better raw material.
Typical ediscovery vendors cover one or two. EvolveDocs ships domain-depth extraction across five — with consistent tooling, billing, and review workflow.
IRS authority taxonomy built in — rev_rul, rev_proc, PLR, TAM, CCA distinguished. Returns: 1040, 1120, 1120-S, 1065, 990.
Opinions, briefs, motions, orders across 10+ jurisdictions — US federal + state, UK, Canada, Australia. Citation validation against source.
Per-jurisdiction claim grammars for US, EP, CN, JP, KR, PCT. Grants, office actions, amendments, IDS, assignments.
14 form variants with TRID/RESPA compliance fields in the schema. Loan-package reassembly from unsorted scans into a reviewer-grade report.
Journal-entry double-entry validation, balance-sheet consistency, cross-statement reconciliation.
Validated documents flow back into the reference corpus, so classification gets more precise with use — no per-customer training labels, no weeks of manual setup.
Feed in a 2,500-page scanned loan package — unsorted, mixed, degraded. Get back a working report for your review: pages classified and reassembled into their logical documents, expected fields checked, cross-document inconsistencies flagged with the evidence behind each finding.
Mortgage Loan File Report
4 documents · 4 pages · reassembled
✓ loan_application — Form 1003 / URLA
✓ form_1098 — Mortgage Interest Statement
✓ promissory_note
✓ closing_disclosure
⚠ Amount mismatch
Note principal $343,000.00 vs. $340,000.00 on the application, 1098, and closing disclosure.
⚠ Date-sequence violation
Closing dated Feb 28, 2025 precedes the note (Mar 3, 2025).
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Upload anything — scanned PDFs, office docs, email archives. Every page rendered, OCR'd, and accounted for.
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Fused-signal classification — image similarity, text similarity, form codes, model judgement — against a reference corpus that grows with every validated document.
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The matched type drives its domain schema: claim elements, TRID fields, IRS authorities, holdings.
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Five domain rule layers interrogate the extracted record before a reviewer ever sees it.
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The loan file report — every finding evidence-cited to the page it came from, every page in the package accounted for.
Bring a matter. The platform classifies it, extracts it, interrogates it, and hands your reviewers the finished report.