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Sovereign AI & document intelligence

Financial RAG for a European hedge fund

European long/short hedge fund · 2025 · regulated-document RAG

RAGFinanceMNPIAudit log

Problem

A multi-strategy European hedge fund needed retrieval-augmented research over regulated financial filings, broker reports, internal models, and news. PMs were spending hours per name on document-trawling that should be a 30-second query, while compliance demanded a defensible audit trail for every output.

Approach

Metadata-filtered RAG with strict admissibility gating — MNPI windows, broker-license tiers, deal-list information barriers, jurisdiction-of-issue. Multimodal PDF parsing without OCR for tables and charts in 10-K and annual reports. Guarded generation with calibrated refusal scoring, so the system says "I do not have admissible evidence" instead of confabulating across firewalled sources. Per-query audit log indexed by analyst, session, and active deal-list.

Stack

Claude · custom retrieval over a metadata-aware vector index · Python service backbone · secure ingestion pipeline

Outcome

Substantial reduction in PM research time per name. Compliance team can reconstruct the evidence trail for any answer the system produced — analyst, session, retrieved chunks, generated output, refusal events. Compliance-defensible by design rather than retroactively bolted on.

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Aru Bhardwaj

Fractional CTO architecting sovereign AI systems for startups and scale-ups across Europe. Custom ML, agentic RAG, and secure LLM infrastructure. 7+ years turning complex data into production intelligence.

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