DOCUMENT INTELLIGENCE
Stop paying people to retype what's already on the page.
Contracts, invoices, applications, AI that reads, extracts, and routes information from any document format. Hours of manual entry become seconds.
Why it matters
The case for doing this now.
Most of the data your business depends on lives in documents that weren't designed for machines: PDFs, scanned forms, screenshots, contracts with footnotes that reverse the main clause. The default fix is hiring people to retype it. That cost grows with every new vendor, every new client, every new format.
An IDP system inverts that curve. Once it understands your sources, adding more coverage becomes a software problem instead of a staffing one.
What’s included
How we ship this.
Source-aware ingestion
Email attachments, shared drives, vendor portals, and uploads - pulled in on a schedule, deduped, and timestamped.
LLM extraction with structure
Fields, tables, and clauses extracted into the schema your downstream systems expect - not a wall of unstructured text.
Validation and anomaly flagging
Confidence scores, cross-checks against historical data, and a human review queue for the cases that don't pass.
Direct routing into your stack
Extracted data lands in your ERP, CRM, billing system, or data warehouse - not in another spreadsheet.
Data points
The numbers behind the case.
Sources are linked beneath each number. Items marked typical range come from our own engagements rather than a published study.
~80%
of enterprise data is unstructured - much of it locked in documents
typical rangeIndustry estimate (IDC, Gartner)
~20%
of knowledge-worker time spent searching for information
typical rangeAIIM / McKinsey range
60–80%
typical reduction in document processing time after IDP rollout
typical rangeWhat we've seen
1–4%
manual data-entry error rate replaced by validated extraction
typical rangeIndustry benchmarks
Where this shows up
What this looks like in practice.
AppAdvisor - college admissions platform
Replaced overseas manual data entry with an AI pipeline that finds, parses, and validates university data from PDFs and HTML - 99% cost reduction on data sourcing, with a daily refresh across thousands of schools.
Real engagementRead the case study
A small finance team handling vendor invoices
Inbound invoices auto-extracted, matched to POs, and queued for one-click approval. The two days a month spent on AP reconciliation collapsed to a Friday afternoon review.
Representative engagement
Next step
Scope your first document workflow
Send us the messiest document workflow you have. We'll show you what an automated version looks like and what it would cost to run.