Over 80% of enterprise knowledge is trapped in documents, PDFs, transcripts, and scans. We do what raw LLMs and parsers cannot: convert chaotic unstructured files into governed, evaluated, audit-ready data assets.
Feeds, APIs and flat files were solved years ago. Then a signed agreement or claim lands in an inbox and the whole discipline stops at the attachment.
No fields, no normalization, no lineage, no owner — for four-fifths of the enterprise estate.
That is the entire layer. Each stage runs inside your boundary, under your credentials, on your audit trail.
Shared drives, mailboxes, scanning queues, earnings call audio, video exhibits, supplier portals, and archival silos.
Layout-aware OCR keeps columns, tables, stamps and signatures where they were. Skewed scans are straightened; genuinely illegible pages are flagged, not guessed at.
Document type first, then the things inside it: parties, dates, amounts, identifiers, clauses, line items — typed in context rather than pattern-matched, and bound to the schema your structured feeds already use.
Your validation rules, automated PII redaction, entity resolution, and per-field confidence scoring. Ambiguous values route directly to human stewards, feeding an active learning loop that continuously retrains extractors.
Published once as a canonical data asset: written into core transactional databases, indexed with entitlement controls for enterprise RAG, and exposed as typed tools for agentic workflows.
One document from a run shaped like yours. Nothing under the bar reaches the database on its own.
| Field → your schema | Value & source | Confidence | Outcome |
|---|---|---|---|
| contract_value | $25,000,000 · page 1, cl. 2.1 | 0.99 | PASS |
| counterparty_id | Redwood Ind. LLC → PARTY_MASTER #48812 | 0.98 | PASS |
| effective_date | 2026-04-01 · page 1, preamble | 0.97 | PASS |
| payment_term_cd | NET45 · page 6, cl. 9.3 | 0.96 | PASS |
| termination_notice | 90 days · page 11, cl. 14.2 | 0.95 | PASS |
| governing_law | ambiguous — two jurisdictions named, page 12 | 0.87 | HOLD |
Raise it and more goes to review; lower it and more goes straight through. Either way the trace records which happened, for every field — including the ones a steward confirmed by hand.
Corrections are not discarded. They feed back as labelled examples, so the extractor that got governing_law wrong on a two-jurisdiction contract gets better at exactly that shape of document.
Commodity OCR and raw model parsing stop at text extraction. Level six and seven transform your operating model and compound accuracy over time.
| Level | Capability | Industry Standard | gothink.ai Solution |
|---|---|---|---|
| L1–L2 | OCR & Document Parsing | Standard LLM / OCR APIs | Geometry- & layout-aware extraction |
| L3–L4 | Entity & Relationship Extraction | Generic Named-Entity Recognition | Domain-native master schema mapping |
| L5 | Governed Validation & Lineage | Rarely supported (black box) | Pixel bounding-box lineage + field confidence |
| L6 | Master Data & Agent Tooling | Manual integration scripts | Direct system of record & tool-call generation |
| L7 | Continuous In-VPC Learning | Static pipelines | Steward overrides retrain models locally |
Without the layer, every consumer is its own extraction script, its own integration, and its own argument about which number is right.
Governed fields written back into ERP, CRM, or master databases.
Indexed with entitlements intact, citations down to the pixel.
Exposed by API to anything that needs to act on the record.
Every value with its source page, ready for compliance review.
K-1s, pitchbooks, earnings transcripts, and credit agreements normalized into master records.
ACORD forms, loss runs, and adjuster notes turned into deterministic payout logic.
Data room extraction, change-of-control clauses, and regulatory filings with 100% citation trails.
Complex multi-line POs, vendor terms, and service agreements validated against ERP systems.
The next consumer should be a permission grant, not another project. A reasoning engine is only ever as good as the corpus it can reach — and buying a better engine does not widen the corpus.
The five stages do not change. What changes is the schema they write to, the fields your risk function cares about, and the family that costs you the most re-keying. Open the estate that looks like yours.
Trust deeds, ACAT packs and held-away statements typed into the household master.
LPAs, PCAPs and capital notices typed onto your fund, party and security master.
Clause-level lease abstraction at portfolio volume, without an offshore queue.
Account packs, loan files, KYB packs, remittances and disputes typed onto one customer, merchant and settlement schema.
Broker submissions, SOVs, loss runs, FNOL packs and medical records typed onto your policy and claims master.
PBAs, ISDA schedules and lock-up addenda typed onto your client and financing master.
Structure documents, source-of-wealth evidence and pledge terms typed onto one client master.
The pipeline is the same in every one of these. What a pilot buys you is the schema, the thresholds and the ground-truth set for your estate — proven on your own documents before anything scales.
The structured feeds are already mastered. Prove the unstructured half end to end, in weeks, on your own documents.
Contracts, invoices, onboarding packs, claims or filings — whichever costs you the most re-keying.
Two weeks: map the master fields, agree thresholds, baseline today's manual effort.
A live pipeline into a sandbox master, scored on a set your experts signed, lineage on every field.