Document Intelligence Engine
A document-AI pipeline that ingests the business's document corpus, classifies by type, extracts the relevant fields, routes to downstream systems with confidence-graded review queue.
- Engagement
- 8–14 week build · ongoing operation
- Built for
- COOs · Operations directors · Finance teams · Compliance leads
Most established businesses accumulate document workflows that scale linearly with growth — invoices, contracts, supplier correspondence, customer onboarding documents, regulatory filings. Each workflow has its own quirks, none of them are automated, the operations team spends real hours per week on routine extraction.
What this is
A horizontal document AI engagement for established businesses. Three layers:
- Ingestion. Email-attachment intake, SFTP, file-upload, per-source connectors. The document corpus enters via whatever path the business already uses.
- Classification and extraction. Per-document-type model handling — invoices vs. contracts vs. shipping docs. Per-type extraction with confidence scoring.
- Routing and downstream integration. Per-document-type routing rules. Integration with the business's downstream systems.
How it's built
LayoutLM-class document AI for the structured extraction, BERT-class clause-extraction models for the legal-language fields, per-document-type templates as a fast path. Routing layer in Python with configurable rules. Adapters into the business's downstream systems (ERP, CRM, document management).
What you get
- The ingestion-and-classification pipeline.
- Per-document-type extraction models.
- The routing layer with configurable rules.
- Integration with downstream systems.
- The review-queue UI for confidence-graded human-in-loop handling.
Engagement is shape, not list.
Length and price are functions of the data and the destination. The shape below is the typical engagement.
- Length
- 8–14 week build · ongoing operation
- Lead
- Bogdan
- Cadence
- Async, weekly
- Bar
- Production
Scoped during the discovery call against the actual data and the operation it integrates with.
Principal engineer. Architecture and most code ships through one keyboard.
Written updates between, calls when the decision needs the room.
Async correctness, capacity under burst, observability at every boundary.
Products this composes with.
Same suite, or vertical-specialized versions in another.
- Same suite · AI Implementation Suite
Process Automation Agents
A multi-step agent orchestration layer — workflows expressed as agent-coordinated processes, integrated with the business's existing systems, with human-in-loop checkpoints where the workflow needs them.
- Same suite · AI Implementation Suite
Finance Operations AI
An AI layer over the finance-ops workflows — invoice ingestion and posting, expense categorization, AP/AR reconciliation, payment matching, fraud-pattern detection. Integrates with the business's accounting system (NetSuite, QuickBooks, Sage, Xero, custom).
- Also in · Family Office Suite
K-1 Extraction & Validation Engine
A document-AI pipeline that ingests the K-1 corpus as it arrives, extracts all 200+ fields with confidence scores, maps to the FO's chart of accounts, flags inconsistencies against partnership returns, and posts to AtlasFive (or your fund-accounting system) with audit trail.
- Also in · Family Office Suite
Statement & Capital-Call Ingestion Engine
A document-AI pipeline that ingests the year-round financial document corpus — statements, capital-call notices, distribution notices, trade confirms — extracts the relevant fields, classifies the transaction, and posts to the ledger of record with confidence-graded review queue.
What buyers ask about this one.
How is this different from the K-1 Extraction Engine in the FO Suite?
K-1 Extraction is vertical-specialized — built specifically for the family-office tax-season K-1 workflow with FO-specific integrations (AtlasFive, partnership-cross-check, etc.). This is the horizontal version for general businesses — same modeling backbone, generic document classification and extraction layer, no FO-specific specializations. If you're an FO, use the K-1 product. If you're a general business with similar workflows, this is the right tool.
How is this different from the PE Diligence Red-Flag Engine?
Same pattern. The PE Diligence engine is shaped specifically for the per-deal diligence sprint and the deal-team risk-heatmap output. This is the horizontal version for general document workflows — same extraction backbone, no PE-specific specializations.
What document types are supported?
Invoices, contracts, purchase orders, shipping documents, receipts and expense documents, customer onboarding forms, regulatory filings, certifications, ID documents. Per-engagement, new document classes are added — the model adapts.
What's the integration pattern with downstream systems?
Per-document-type routing — invoices to the AP system, contracts to the legal team, customer documents to the CRM. The routing layer is configurable and works with the business's existing software stack (ERP, CRM, legal-document-management, custom systems).
Pricing?
Scoped to document volume and document-type breadth. Discovery call covers both.
If the deliverable matches the gap, the next step is one call.
We'll scope length and price against your data and the operation it integrates with. No retainer, no fishing.
Bogdan and team · async-first · OP—2026