ManIQ
Financial intelligence and contextual RAG analysis for modern market investors.
Context & The Challenge
A financial intelligence platform for investors offering real-time market updates, trending stock analytics, and custom document-based RAG chat features for deep analysis.
Retail and angel investors spend hours sifting through dense quarterly reports, SEC filings, and disparate market news. Traditional dashboards show static numbers without explaining context or enabling fast queryable intelligence over complex financial documents.
System Architecture & Approach
Designed a multi-layer financial platform combining real-time market data feeds, OCR table extraction for financial statements, and a contextual Retrieval-Augmented Generation (RAG) assistant that indexes SEC filings and allows users to question earnings calls directly.
Hybrid Search Indexing
Vector embeddings combined with hybrid keyword search to ensure financial figures are queried with exact precision.
Streaming SSE Pipelines
Streaming Server-Sent Events (SSE) with Vercel AI SDK to eliminate perceptible latency for complex multi-page document queries.
Deliverables & Results
- —Real-Time Market Tracking: Live price tickers, volume indicators, and sentiment analysis.
- —Financial Document OCR: Ingests PDF balance sheets, annual reports, and investor decks into machine-readable structures.
- —Document-Based RAG Chat: Context-window semantic search over ingested reports with verified citations.
- —Strict Schema Outputs: Zod-validated JSON responses preventing LLM hallucinations in numeric analysis.
Reduced document inspection time from hours to seconds for test portfolios, with zero hallucination on cited numeric disclosures and 60% faster page render times.
“Financial data demands zero tolerance for ambiguity; combining strict Zod schema validation with hybrid vector-keyword retrieval is essential when models handle balance sheets and earnings metrics.”
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