Factor-First AI Investment Analysis Narrated by a Six-Persona Committee
Built a Quality + Valuation + Growth + Momentum + Health factor composite narrated by a six-persona committee — one consistent framework across every public equity.
The Problem
Standard brokerage tools expose raw financial metrics but do not synthesize them into a conviction-level judgment. Investors still do their own mental weighting, often inconsistently and without a documented framework.
The core gap is not data access; financial APIs are commodity. The real problem is a missing, repeatable scoring architecture that combines quantitative fundamentals with qualitative moat assessment.
The platform also had to be robust enough for real decision-making with personal capital, not a demo workflow.
The Approach
Moved from a Graham-centric parallel-scorer committee to a factor-first composite (ADR-011): Quality, Valuation, Growth, Momentum, and Health each score independently and aggregate into a single composite.
Built a six-persona investment committee that narrates the factor scores rather than recomputing them in parallel — each persona owns a factor lens and explains the reading in their philosophical voice.
Added Piotroski F-Score and Altman Z-Score as diagnostic gates that surface independently, not as factor bars, so a distress zone hard-caps the composite instead of being averaged away.
Pulled quantitative signals from financial data APIs and delegated committee narration to Claude via the Anthropic API (with Bedrock failover) using a constrained prompt that returns structured verdicts rather than open-ended commentary.
Grounded the LLM with factual financial context at inference time and added public no-login access with rate limiting at 10 requests per IP per hour.
The Impact
- Returns a repeatable, structured verdict for any US-listed equity — a 0-100 composite and A+ to F grade with six-persona narration underneath — instead of raw metrics the investor has to weigh by hand
- Distress gates (Piotroski F-Score, Altman Z-Score) hard-cap the composite rather than being averaged away, so a weak balance sheet can't be masked by a strong factor
- One consistent factor framework across every ticker makes ticker-to-ticker comparison repeatable instead of ad-hoc, and surfaces which factor and which persona drove conviction
- A public no-login demo narrates a fixed sample portfolio so anyone can see the committee in action — engineered for safe public exposure with a hard daily cost ceiling, per-session rate caps, and a default-off kill switch
Related
Investment Committee
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