How Collate turns raw documents into trusted decisions
A transparent look at the pipeline, rules engine and data flow that power document intelligence — from ingestion to audit-ready reporting.
The extraction pipeline
Step 1
Ingest
PDF, Excel & Word files are uploaded and normalized into a canonical document model.
Step 2
Extract
The extraction engine detects fields, tables & entities with confidence scoring.
Step 3
Compare
Values are aligned across documents; the diff engine flags discrepancies.
Step 4
Review
Reviewers approve, reject or resolve findings with full traceability.
Step 5
Report
Audit-ready reports are generated and exported in PDF, XLSX or DOCX.
Weekly processing throughput
Documents & fields processed across the workspace.
Extraction accuracy by format
Field-level precision across supported file types.
Rules engine
Deterministic rules evaluate every extracted field and drive the review workflow.
Confidence < 85%Flag field for manual verificationValues differ across docsCreate a discrepancy findingRequired field missingBlock report generationAmount variance > 5%Escalate to reviewer queueDuplicate document hashMerge & de-duplicateSystem building blocks
Next.js + TypeScript
App Router UI
Postgres (Supabase)
Documents & audit log
Extraction Engine
Field & table OCR
Rules Engine
Diff & escalation
RBAC
Member / Reviewer / Admin
Edge Caching
Sub-second navigation
See the platform in action
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