FOR FINANCIAL SERVICES TEAMS

Structured extraction at the scale of a 10-K backlog.

Large filings, dense earnings packets, broker decks, footnoted contracts — find the needle in the haystack, with citations back to the source. Accurate, auditable, and ready to deploy wherever and whenever you need it.

TRUSTED BY
PROOF · BENCHMARKS

Benchmarked on the documents you actually work with.

Methodology and corpus available at benchmarks. Marker, Surya, and Chandra are open source — and Chandra is the model running inside the Datalab API.

  • 86.7% OLMOCR-BENCH · DATALAB API
  • 90.7% OLMOCR-BENCH · TABLES
  • 80.4% MULTILINGUAL · 43 LANGUAGES
  • 67.7k+ OPEN-SOURCE STARS · MARKER + SURYA + CHANDRA
WHY DATALAB

Numbers you can verify, on the tables that usually break.

01 BENCHMARKS YOU CAN AUDIT

Published methodology. Named competitors.

The benchmark suite, the document corpus, and the methodology are public, so procurement verifies the numbers instead of trusting them.

02 BUILT FOR THE HARD TABLES

We test against the financial-document parts that usually break.

Multi-column 10-K tables, footnoted regions, multi-period statements, and ISDA definitional sections are checked on every model release.

03 FIELD-LEVEL CITATIONS

Every extracted value cites the page it came from.

Schema-defined extraction emits typed JSON with a page coordinate per field, so risk and compliance trace each number back instantly.

DEPLOYMENT

Run it wherever your filings have to live.

  • Managed cloud

    Start with an API key — nothing to host or operate.

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  • EU data residency

    Run in-region, with no egress to US infrastructure.

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  • Your VPC

    Runs inside your own AWS, GCP, or Azure account.

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  • On-prem & air-gapped

    Fully offline, the same model weights, dedicated support.

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SOC 2 Type II · BAA available View our trust center →
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