When the auditor asks where a value came from
You have source grounding instead of hand waving. Extracted entities point back to character ranges in the original text.
Stop paying experts to copy data out of documents.
Manual extraction is overhead. Bad extraction is risk.
You know the lifecycle because you have lived it:
Someone writes a parser. It works on the demo file.
A scanned document arrives. You bolt on OCR.
A table breaks. You bolt on another parser.
Someone asks, “where did this number come from?” and nobody has a clean answer.
The person who built it leaves. The workflow becomes institutional folklore.
Kautious Extract is built on the opposite assumption: parsers fail, source formats drift, and every useful result has to be observable, repeatable, and reviewable from the beginning.
From raw document to source-grounded JSON.
POST /extract
curl -X POST https://api.kautio.us/extract \
-H "Authorization: Bearer $TOKEN" \
-H "Content-Type: application/json" \
-d '{
"text": "Acme Corp CFO Jane Doe sold 12,000 shares at $48.20 on March 3.",
"prompt": "Extract insider transactions with person, role, shares, price, and date.",
"include_source_grounding": true
}'No brittle script. No one-off spreadsheet. No mystery output. Need a schema first? POST /auto-schema reads representative documents and drafts entity types, prompts, and examples.
- Word
- Excel
- PowerPoint
- Scanned images
- EPUB
- ZIP
- CSV/TSV
- XML
- Jupyter notebooks
- Live web pages
- Audio transcription
Your experts were hired to judge the facts, not hunt for them.
You are buying the version of your workflow that is already running, monitored, and defensible.
When the boss asks if the AI is accurate
You show the quality score. Every extraction is graded across five dimensions, and model comparison explains why one configuration won.
When the ugly document shows up
The system has a plan. The parser chain moves through local OCR, cloud OCR, agentic parsing, PDF fallback, and broad-format conversion.
When everything must work in ChatGPT
You are not starting from scratch. The same capabilities are exposed through MCP tools, OAuth, scheduled jobs, and interactive widgets.
Five parsers. One defensible result.
Ingestion that expects failure
A five-tier parser stack: LiteParse, Datalab Marker, LlamaParse, pypdf, and MarkItDown. Pick a parser when precision matters, or let the registry fall through automatically.
Web extraction for the modern internet
Extract from URLs with provider-aware acquisition through Stagehand/Browserbase, OloStep, and Spider.cloud. Render pages, capture HTML tables, fall back when needed.
Quality controls operators can use
Quality scoring, model comparison, extraction summaries, cache metadata, operation history, streaming progress, and visualizations: inspect work instead of trusting a black box.
One workflow across surfaces
A FastAPI service for product integration, a React dashboard for operators, MCP tools for ChatGPT/OpenAI Apps, and Convex-backed metadata for scheduled jobs and batches.
Generic extraction is a head start. Domains are a finish line.
Kautious Extract ships domain templates, schemas, validators, and connectors for workflows where wrong answers get expensive.
SEC
Filing search, sections, XBRL facts, company lookup, and per-filing extraction.
Fed & rates
Federal Reserve material, yield curves, reference rates, and auction data.
Market
Corporate actions, earnings, M&A, and market-event extraction.
Regulatory
FINRA and CFPB enforcement workflows.
KYC & audit
Sanctions, beneficial ownership, and financial-statement footnote templates.
Inbox & meeting
Email triage and meeting-intelligence templates for analyst workflows.
Hardened before you asked.
This audience reads vague security language as a red flag. The security review happened before launch, not after the incident.
- SSRF-protected URL ingestion
- Request-size limits at the ASGI layer
- OAuth 2.1 + JWT auth
- Rate limiting
- Provider-aware proxy controls
- Dependency auditing in CI
- OpenTelemetry tracing
- Prometheus metrics
- Convex-backed audit records
Production workflow onboarding
Turn document backlog into decision-ready data.
Bring us the documents your current stack cannot handle. If it is a fit, we'll build the extraction path around the real workflow.
Design partners in financial services, compliance, legal, and AI product teams get priority.