Business documents contain information that another system needs, but layouts vary and required data can be incomplete or inconsistent.
Finch Demonstration
Document Intelligence for RFQs and Invoices
A controlled document workflow separating classification, extraction, validation, exceptions and the next business action.
- Solution type
- Document Processing · Structured Output
- Industry context
- Manufacturing & Engineering · Professional Services · Corporate Operations
- Status
- Interactive Demo
- Publication
- Public demonstration
Demonstration scope · fictional or generalised information · no claimed client deployment
Overview
What this demonstration is intended to show.
Fictional sample documents become structured records, then deterministic rules surface missing information and reconciliation exceptions.
Workflow
From manual hand-offs to a controlled system.
- DocumentFictional sample→
- AIClassify + extract→
- SoftwareNormalise fields→
- ValidationCheck completeness→
- HumanReview exception→
- RecordNext workflow
System boundary
Constraints are part of the design.
- Document layouts vary.
- Extraction can be uncertain.
- Missing information cannot be invented.
- The public demonstration uses only bundled fictional samples.
- Accept public file uploads
- Read real business documents
- Post records to finance or ERP systems
- Approve extracted data automatically
What the demo proves
Claims bounded by what is inspectable.
- 01Documents can become structured records.
- 02Missing information can be made visible.
- 03Validation can remain separate from extraction.
- 04A structured record can start another workflow.
Connected architecture
Related capabilities and systems.
ServicesDocument IntelligenceWorkflow Automation
SolutionsInvoice ProcessingAI RFQ ProcessingDocument Reconciliation
IntegrationsEmailDocument repositoriesPostgreSQL
Industry contextsManufacturing & EngineeringProfessional ServicesCorporate Operations
Inspect the demonstration
Use the system already built into this site.
Use only fictional or generalised information. Do not enter confidential, personal or commercially sensitive data into a public demonstration.