02 · Data
Document & data pipelines, with schema validation.
OCR + LLM extraction with typed schemas, confidence thresholds, and a human-QA review queue for the long tail. Built for PDFs, invoices, contracts, spec sheets — anything structured enough to validate.
What you get
- OCR + LLM extraction — pre-processed images, then Claude or GPT-5 for field parsing with structured-output prompting.
- Schema validation — every document parsed against a typed contract. Rejections trigger QA, not silent drops.
- Confidence-gated QA — high-confidence extractions flow through; low-confidence ones land in a review UI for human sign-off.
- Integration hand-off — output writes into QuickBooks, NetSuite, Salesforce, Postgres, or a drop zone you control.
- Observability — per-vendor accuracy, cost per doc, review-queue latency.
Document shapes we handle
- Invoices and receipts — multi-line items, totals, tax breakdowns, vendor normalisation.
- Contracts — clause extraction, effective date, counterparty, renewal terms.
- Spec sheets and technical PDFs — tables, field labels, part numbers.
- Identity and compliance documents — ID/KYC flows with masking and audit trails.
Process
- Week 0 — audit. Sample 50–200 real documents, define the target schema, agree success rate.
- Week 1 — pipeline build. OCR stage, extraction stage, validator stage, review UI.
- Week 2–3 — accuracy tuning. Measure on held-out samples, tune prompts and thresholds until we hit the agreed rate.
- Week 3–4 — rollout. Shadow-mode first, then production, with dashboards live on day one.
Pricing
Fixed-scope pipelines from $6,000, delivered in 2–4 weeks. Complex multi-schema work scopes separately — see pricing.