Autonomous Financial Intelligence
- Of deal data unstructured
- 80%Of deal data unstructured
The challenge
For mid-market private equity firms and enterprise corporate development teams, deal velocity and risk assessment are severely bottlenecked by a manual data paradox.
Investment decisions must be backed by absolute quantitative certainty, yet over 80% of critical target company data is trapped in unstructured formats — multi-page SEC filings, disparate data rooms, and inconsistent management call transcripts.
Analysts spend the early part of every deal transcribing that material into models by hand, which is exactly the phase where speed decides who wins the asset.
What we built
- 01
Document ingestion
Filings, data room contents and call transcripts are ingested as they are, without requiring a consistent format across sources or targets.
- 02
Structured extraction
Agentic extraction pulls the figures, terms and disclosures analysts would otherwise transcribe, normalising them into a consistent structure with a reference back to the source document and location.
- 03
Analyst query layer
The resulting dataset is queryable in plain English, so a diligence question can be asked directly instead of scheduling an analyst to go and find the answer.
What came out of it
- The unstructured majority of target company data made available as structured, queryable records.
- Early-deal analyst time redirected from transcription to judgement.
- Every extracted figure traceable back to its source document.
More case studies
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