Document intelligence pipeline
Unstructured files in, validated records out, humans only on the uncertain ones.
Use it when
Invoices, KYC, claims, contracts, forms and emails that must become structured data in a system of record with an audit trail.
The parts, top to bottom
across every level
Hover or tap any part to see what it does. The light shows the order a request moves through.
What happens, in order
- 1Ingest from email, scan, upload
- 2Classify document type
- 3Extract with a typed schema
- 4Validate against rules & other docs
- 5Confidence routing: auto or review
- 6Post to system & keep evidence
What we typically build it with
Trade-offs
Accuracy is driven by parsing quality and validation design more than by the model; layout-aware parsers score from about 50% to 85% on document benchmarks, so we benchmark them on your documents. Confidence routing typically sends around 20% of items to humans and decides how much time you actually save.
Problems this architecture solves
Generic problem statements with the flow and the outcomes the industry has documented.
Documents keyed in by hand
Invoices, KYC files, claims and contracts arrive as PDFs and photos. People retype them, errors slip through, and the backlog grows every month-end.
How the system works
- Ingest PDF / image / email
- Classify document type
- Extract to a schema
- Validate & score confidence
- Auto-post or route to review
Outcome: Documented deployments classify documents in under a second, turn day-long claims backlogs into minutes, and reach 85% no-touch invoice processing within six months with a seven-month payback. DXC with Claude; Vic.ai
ArchitectureOther data patterns
Lakehouse, semantic layer and analytics copilot
Raw data becomes governed metrics, then answers in plain language.
Use it when: When dashboards disagree, analysts are a bottleneck, or leadership wants to ask questions of the data directly without breaking the definitions.
Flow
- 1Ingest batch & streams
- 2Bronze → silver → gold tables, partitioned by time / tenant
- 3Quality tests & lineage
- 4Semantic layer defines metrics
- 5Text-to-SQL agent with guardrails
Let's build intelligent systems that drive growth
Tachyon is the engineering partner for teams that need AI in production, not in a deck. Start with a free 60-minute discovery call.
Tell us the problem, we will map it to the architecture
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