Document Intelligence
Your platform shouldn't be a graveyard of PDFs, email attachments, and orphaned uploads. We design production pipelines that classify, extract, organize, and surface documents, with audit trails your clients and compliance teams can trust.
94%+
Field-level accuracy on scoped schemas (with HITL)
48 hr
Corpus audit & feasibility assessment available
100%
IP transfer (pipelines, models, and runbooks
NDA
First conversation, before any sample data
Recent mandate pattern
A B2B platform had years of client uploads spread across folders, ticket attachments, legacy storage buckets, and ad-hoc shared drives. End clients logged in expecting a single source of truth, and got a maze of duplicate filenames, missing metadata, and no search that worked.
What we built
Clients find the right document in seconds, not support tickets. Your team stops manually re-filing uploads. The platform becomes a document product, not a file dump.
6–10 weeks
Typical production mandate
Eight production patterns we deploy, not generic "upload a PDF and hope." Each scoped to your sources, schemas, and client experience.
AI taxonomy for multi-tenant platforms
Per-client document views with automatic classification, deduplication, version awareness, and semantic search, built on your existing auth and tenancy model, not a separate DMS rip-and-replace.
Contracts, invoices, forms, and reports → schema
Custom extraction schemas per document type, parties, dates, line items, clauses, identifiers, validated against business rules and exported as JSON, CSV, or warehouse-ready tables.
Find answers inside your corpus, not hallucinate them
Retrieval pipelines with citation requirements, access controls, and evaluation harnesses, so internal teams and client-facing copilots answer from approved documents only.
One pipeline from every place files land
Consolidate uploads, email attachments, SFTP drops, S3 buckets, SharePoint exports, and third-party APIs into a normalized document layer with consistent metadata and processing status.
Confidence scores, review queues, audit trails
Production document AI isn't fire-and-forget. We build review workflows where analysts confirm extractions, correct edge cases, and feed corrections back into monitoring, full audit trail for regulated environments.
Biotech, legal, insurance, and federal workflows
Entity extraction from lab reports, regulatory filings, policies, and SOWs, with NDA-first delivery, anonymized references, and architecture designed for your compliance partners to validate.
Scans, faxes, and image-only PDFs
High-volume OCR with layout preservation for historical archives and inbound mail workflows, pre-processing pipelines that improve downstream extraction accuracy, not generic cloud OCR with no QA.
Documents as a data product
Structured fields land in Postgres, Snowflake, BigQuery, or your existing warehouse, enabling dashboards, automation triggers, and ML features without manual re-keying.
Fixed-scope mandates with the Production Standard: deployable pipelines, monitoring, and runbooks.
Discovery
Week 1
Document inventory, source mapping, sample corpus review, and KPI definition, what does 'organized' mean for your clients and operators?
Schema & taxonomy
Week 1–2
Extraction schemas, classification taxonomy, tenancy rules, and acceptance criteria documented before pipeline build.
Pipeline build
Week 2–6
Ingestion connectors, extraction/classification models, review UI, and platform integration; iterative eval against held-out samples.
QA & hardening
Week 6–8
Human review calibration, load testing, monitoring dashboards, runbooks, and security review aligned to your environment.
Production & transfer
Week 8–10
Deploy, shadow period, capability transfer to your team, all code, schemas, and documentation owned by you.
Deep experience in biotech and life sciences under NDA. View biotech capabilities →
Product path
Beta product for standard extraction workflows, PDF and DOCX ingestion, custom schemas, human review, and API output to your warehouse. Consulting mandates handle platform integration and complex tenancy.
Learn about Doc Engine →The Production Standard
Six commitments contracted in writing on every engagement.
01
If AI isn't the right tool, we say so in week one and redirect budget to what will ship. No POC theater.
02
Business KPIs locked in discovery. Model selection follows the metric, not the hype cycle.
03
Model cards, access controls, evaluation harnesses, and audit trails, not a compliance bolt-on at go-live.
04
Deployed code, monitoring dashboards, CI/CD pipelines, and incident runbooks. Not recommendations for someone else to implement.
05
Scoped projects designed for production in 6–10 weeks. Boutiques move; global programs wait for steering committees.
06
Your team can operate, extend, and maintain what we build. IP and documentation transfer is included, not upsold.
Every scoped project includes a production deliverable checklist signed off before close. If we can't commit to deployable output, we won't take the engagement.
No. We integrate with S3, GCS, Azure Blob, SharePoint, and platform-native storage. The intelligence layer sits on top, classification, extraction, search, and client views, without a rip-and-replace DMS project.
Generic APIs return JSON blobs with no tenancy rules, no review workflows, and no platform integration. We build end-to-end systems: ingestion from your sources, schemas matched to your business, QA queues your operators use, and output wired into your product and warehouse.
Yes, that's a common mandate. AI classification routes uploads into client-scoped collections, surfaces semantic search per tenant, and flags duplicates or missing document types, so clients see an organized portal instead of a flat file list.
Contracts, invoices, purchase orders, insurance claims, lab reports, regulatory filings, onboarding packets, technical manuals, and platform-specific uploads. We scope extraction schemas to your highest-value document types first, not boil-the-ocean.
Confidence thresholds route uncertain extractions to human review. Full audit trails log who approved what and when. We design for your compliance requirements; formal validation (GxP, SOC audit scope) remains with your QA and security partners.
Start with a discovery call and optional 48-hour corpus feasibility review. Production mandates are fixed-scope SOWs, typically 6–10 weeks, with the Production Standard and deliverable checklist. Doc Engine (beta) offers a productized path for standard extraction workflows.
Tell us where files live today, who needs to find what, and what "organized" looks like for your product. We'll scope an honest mandate, or tell you if a simpler path fits first.