The Structuring Pipeline & Spec Rail
Structuring in Talonic starts with a Spec: a reusable configuration that composes a rail of stages over one schema. Running the Spec compiles that rail into a pipeline that processes each document through its stages in order, filling a structured table with per-cell confidence scores and provenance traces.
The rail
| Stage | Purpose |
|---|---|
| Source | Select the documents the run reads — uploads, connectors, or API ingestion |
| Field Registry | Map schema fields to registry fields discovered across your corpus |
| Extraction | Locate and extract values from each document, with confidence and source spans |
| Resolution | Normalize extracted values — formats, lookups, transforms |
| Matching (optional) | Decide matches against reference data: auto_match, shortlist, or no_match |
| Agent (optional) | Park document-scoped tasks for an external agent over MCP |
| Validation | Type, format, and coherence checks; failures route to the review queue |
| Assembly | Compose per-document records into the final table |
| Data Product | The terminal, governed output other systems consume |
Only Source, Extraction, and the terminal Data Product are mandatory — the rest compose per Spec. The full stage-by-stage guide lives in the Platform Guide.
Confidence and review
Every cell carries a confidence score and a reasoning trace. Validation checkpoints flag cells and records that fail checks into a review queue, where a reviewer sees the value beside its highlighted source region and accepts or corrects it. Corrections are recorded with full audit history.
Running and monitoring
Trigger a run in one call with POST /v1/run (ingest + run a published Spec), or compile and start pipelines explicitly via the Pipelines API. Poll per-phase progress, read governed results, and subscribe to webhooks for completion events.