THE REGISTRY LAYER FOR UNSTRUCTURED DATA
Ingest once.
Query forever.
Talonic ingests messy enterprise documents once — PDFs, scans, handwriting, spreadsheets, emails — into persistent, schema-validated records with field-level evidence. Every workflow, system, and AI agent queries the same registry later. The source is never re-extracted.
Response within 1 business day · Or start free: 5,000 credits/mo, no credit card
Co-author of DIN SPEC 91491, Europe’s first AI data standard · GDPR · HIPAA · ISO 27001 / 42001 aligned · EU-resident infrastructure
TRUSTED ACROSS LOGISTICS, ENERGY, AUTOMOTIVE, AND CONTRACT OPERATIONS
THE PROBLEM
The data was never made reusable.
Most tools extract for one schema, then stop. The structure is thrown away with the workflow that asked for it — and the next system, report, or agent starts again from the raw documents.
Every new system re-extracts everything.
Without a registry, adding a downstream system means re-running every extraction. Cost scales as documents times systems.
Every new agent, workflow, or integration multiplies your extraction cost. Unless the data is already in a registry.
The same root cause, measured four ways:
10%
Of enterprise unstructured data is ever analyzed.
5%
Of enterprise data is queryable by AI today.
33%
Of enterprise applications are integrated.
5%
Of enterprise GenAI pilots reach production.
Four broken layers. None of them fixed by a better model. As long as extraction is disposable, every use case pays the O(n × m) bill.
REUSE, NOT RE-EXTRACTION
Solve the workflow. Keep the data.
Run the document work you already pay for. Every field Talonic touches lands in the registry, typed and queryable, so the next agent, schema, or report is served from structure instead of a fresh extraction. The platform is the byproduct of getting the work done.
- ·Vendor and customer contracts
- ·AP/AR: invoices, POs, receipts
- ·Logistics: manifests, bills of lading
- ·Claims, KYC, and onboarding files
3,465 documents · 412,908 fields · 1 registry
SERVED FROM REGISTRY
TOKENS SAVED
0
of 1.52M this run
DOCUMENTS RE-READ
0
the old way: 3,465 × every query
ingest once · query forever · pay once
LIVE DEPLOYMENTS
Live in regulated enterprise. Today.
8,500 active contracts under structuring as of Q2 2026. Schema v2, 59 German-language fields, Microsoft Dynamics injection in Q2 2026.
Next: automated anomaly detection across the full contract portfolio.
22,000 vendor contracts structuring to Ivalua. Commercial execution Q2 2026.
Next: extending schema coverage to clinical trial documentation.
930-document ground-truth benchmark. Accuracy from 75% to 92% across POC cycles (2025–2026). Replacing a six-figure incumbent system.
Next: full carrier-to-load matching across the Gemspring portfolio.
30,500+
enterprise contracts under structuring today.
6-figure
incumbent system being replaced at Bridgeway.
< 200ms
median per-document processing time.
THE MECHANISM
How Talonic works.
How Talonic works
01 Sources
An endless stream of documents. None of it queryable. Ingested through Talonic from email, drive, S3, SFTP, or API. Document types include contracts, invoices, emails, scans, carrier manifests, purchase orders, service reports, and allocations.
02 Data Capture
Every document, parsed. Every field, extracted. Every schema, recognized. In parallel, at scale. Talonic processes service agreements, invoices, carrier manifests, purchase orders, and service reports — extracting 64 to 113 fields per document with schema recognition (vendor_contract_v7, invoice_v3, carrier_manifest_v2, purchase_order_v2, service_report_v1).
03 Field Registry
Every field becomes canonical. Every extraction compounds. The registry never resets. Canonical fields include vendor_name, contract_value, effective_date, term_end, auto_renew, governing_law, notice_period, invoice_number, total_amount, tax_rate, currency, due_date, payment_terms, load_id, carrier, origin, destination, weight_kg, incoterms, vehicle_type, technician, report_id, service_date, and facility. New canonicals are continuously discovered: meter_id, incoterm_variant, clinical_phase, hs_code, vat_id, hazmat_class, and more.
04 Schema Matching
Every new schema, mapped to canonicals. Every field, recognized regardless of source terminology. Continuously. Example: customer_contract_v3 maps party_name to vendor_name (0.94 confidence), agreement_value to contract_value (0.91), termination_date to term_end (0.89), monetary_unit to currency (0.97). 4/4 matched with 0.93 average confidence.
05 Query
Every question, answered against the registry. Every answer, structured and typed. Continuously. Query with SQL, natural language, or API calls. Examples: "SELECT contract_value FROM canonicals WHERE governing_law = BGB § 305ff", "which contracts expire in Q4 2026?", "talonic.query(canonicals, filter={governing_law: BGB § 305ff})". Deliver to SAP S/4HANA, Salesforce CRM, NetSuite, Dynamics, Ivalua, or any REST endpoint.
Most document AI extracts for a schema. Talonic builds the data layer behind every future schema.
Traditional parsing tools start with a destination format and extract into it. Extraction quality is the floor, not the ceiling. Customers consistently see 90%+ accuracy in head-to-head benchmarks against incumbents. And with Talonic, that result lives in a registry that compounds across every future schema, system, and agent.
PROVENANCE
Every value points back to where it came from.
Most tools return a value. Talonic returns a value, the line it came from, the region of the scan that produced that line, the confidence, the phase, and the reasoning. Auditable by default. Defensible by design.
- vendor_nameMeridian Energy AG0.99
- customer_nameKent Logistics Ltd.0.97
- contract_start_date2026-01-010.99
- contract_end_date2027-12-310.99
- contract_value2,480,0000.97
- currencyEUR1.00
- auto_renewtrue0.96
- notice_period_days900.94
- governing_lawDE · BGB § 305ff0.92
- delivery_pointBerlin HKW0.93
- annual_volume_mwh144000.95
- schema_versionvendor_contract_v21.00
USE CASES
One registry. Every document workflow.
The same ingested corpus serves every downstream consumer. These are the four we see most.
Invoices, POs, receipts, and credit notes land as typed records. Three-way match runs against the registry — not against PDFs in a shared drive.
Commercial Invoice · Purchase Order · Goods Receipt Note
Invoice parsing →Parties, terms, renewal windows, and obligations extracted once, tracked across amendments and side letters. Cases group what belongs together.
Master Service Agreement · Contract Amendment · Side Letter
How cases work →Point an agent at the registry via MCP or REST and it reads any document like a typed database: fields, confidence, and provenance on every response.
MCP server · REST API · Node SDK
For agents →Serve copilots and internal tools the same governed fields your ERP consumes. One extraction, every consumer — no parallel pipelines to keep in sync.
Dynamics 365 · Ivalua · Salesforce · custom REST
Delivery infrastructure →MONEY FOUND
Your documents owe you money.
Leakage hides where nobody can query: duplicate payments, unbilled escalations, expiring windows. Once every field is typed and traceable, one pass over the corpus brings it back.
Representative findings from AP and contract portfolios. Every line traces to the value, the source line, and the scan that produced it.
RETRIEVAL
RAG where accuracy matters.
Vector search over raw text retrieves passages that look relevant. The registry retrieves values that are checkable — typed, scored, and traceable to the line that produced them.
When the answer feeds an ERP entry, a filing, or a decision that gets audited, the right-looking paragraph is not a data source.
| Embedding retrieval | Registry retrieval | |
|---|---|---|
| Returns | Text chunks | Typed fields |
| Certainty | Similarity score | Per-field confidence |
| Source | Approximate passage | Line + region of the scan |
| On re-query | Re-embed, re-rank | Read from the registry |
| Audit trail | — | Value → line → scan → reasoning |
DOCUMENT ONTOLOGY
529 document types. Zero templates.
From Schedule K-1 to Bill of Lading (Ocean), from Notarial Deeds to QC Inspection Forms — Talonic understands the structure of every enterprise document type out of the box.
Schedule K-1, Form 1099-MISC, Form W-8BEN, Form 1040, Form 990, and 48 more
Purchase Order, Commercial Invoice, Pro Forma Invoice, Goods Receipt Note, Three-Way Match Report, and 48 more
Bill of Lading (Ocean), Bill of Lading (Inland), Air Waybill (AWB), House Air Waybill (HAWB), Sea Waybill, and 48 more
Notarial Deed, Master Service Agreement, Statement of Work, Non-Disclosure Agreement, License Agreement, and 48 more
Commercial Register Extract, Certificate of Good Standing, Certificate of Incorporation, Annual Return, Director's Report, and 48 more
Patient Intake Form, Medical History Questionnaire, Informed Consent Form, Discharge Summary, Operative Report, and 48 more
QC Inspection Form, Certificate of Analysis (CoA), Certificate of Conformance, First Article Inspection Report, Material Test Report, and 48 more
Insurance Application, Policy Declaration Page, Insurance Policy Wording, Endorsement / Rider, Certificate of Insurance, and 48 more
Property Deed, Title Report, Land Registry Extract, Survey Plan, Zoning Certificate, and 48 more
Employment Application, Offer Letter, Employment Contract, Background Check Report, I-9 Employment Eligibility, and 47 more
For AI Agents
Built to be the data layer your agent reaches for.
Point your agent at Talonic and it can read any document like a database: typed fields, per-cell confidence, and provenance. Discovery surfaces and an MCP server are ready out of the box.
Connect via MCP
npx -y @talonic/mcp@latestDIN SPEC 91491
We co-authored the standard.
Talonic co-authored DIN SPEC 91491 with Fraunhofer IIS, Humboldt-Innovation, GIIC, and the German standards body. Europe's first standard for AI-ready data at the schema layer.
As the EU AI Act extends into data-layer compliance, DIN SPEC 91491 defines what schema-layer data readiness looks like. Enterprises aligning with the standard need an implementation that was built alongside it.
The standard we helped write. The implementation we ship.
See what Talonic would do to your data.
Send a representative sample of contracts, scans, case files, or operational documents. We run them through Talonic and send back your extracted data: field-level coverage, confidence, provenance, and a concrete recommendation for making your corpus reusable, within five business days.
P.S. Six fields, committed once, queryable forever. Your documents work the same way.
Not ready to share a sample?
Frequently asked questions
What is Talonic?
Talonic is the schema layer for enterprise data. It transforms unstructured documents into schema-validated structured data with per-cell provenance and full audit trail.
What types of documents can Talonic process?
Talonic supports over 25 file formats including PDFs, scans, Word documents, Excel spreadsheets, images, emails, and more, classified into a 529-type document ontology.
Is Talonic GDPR compliant?
Yes. Talonic is GDPR and HIPAA compliant, ISO 27001 and ISO 42001 aligned, and co-authored DIN SPEC 91491. All data is processed in EU-resident infrastructure in Germany West Central.
What is DIN SPEC 91491?
Europe's first standard for AI-ready data at the schema layer, published in 2025. Talonic co-authored the standard alongside Fraunhofer IIS, Humboldt-Innovation, and GIIC.
How does Talonic differ from OCR or document parsing tools?
OCR converts pixels to text. Talonic classifies documents against a 529-type ontology, extracts schema-validated fields with confidence scores, reconciles entities into cases, and delivers typed data to systems of record with full audit trail.
Can I test Talonic on my own documents?
Yes. Send a representative sample of your documents and Talonic runs them within five business days. You receive a field-level analysis of extractability, confidence distribution, recommended schema, and a production roadmap.