Use Case: Hedge Fund Research (Expanded)
Hedge Fund AI Research Workflows
Contents
Overview & outcomes
Pipeline for ingestion of filings and calls to produce research briefs and Q&A interfaces.
- 3–5× faster first-draft notes
- Traceable citations to primary sources
- Lower research ops cost
Acquire: data sources
- SEC EDGAR filings, earnings call transcripts
- Broker research PDFs, news feeds
- Market data APIs (tickers, factors)
Enrich: transforms & policies
- Parse tables & footnotes into structured fields
- Normalize entity names; map to tickers & identifiers
- Vectorize segments; attach source URLs
schema: filings.v1 fields: [ticker, period, revenue, guidance, risk_factors]
Reason: agents & rules
- Briefing Agent: generates overview, key drivers, risks
- Cross-Doc Q&A: retrieves relevant paragraphs with citations
- Scenario Tool: sensitivity analysis on guidance
prompt: "Answer with citations from filings only."
Orchestrate: workflows
- Approval: Analyst → PM sign-off
- Export to research notes system; notify portfolio channel
- Append audit log with source hashes
Security & compliance
- PII avoided; licensing constraints respected
- Model access scoped per analyst/PM
KPIs & SLAs
- Time-to-brief, coverage per analyst, citation density
- SLA: source retrieval < 1s p95, Q&A accuracy ≥ 90% on sampled checks
Rollout plan
- Pilot 2 tickers across last 6 quarters
- Define evaluation rubric and ground truth set
- Expand to sector after pass