Projects
GenAIFebruary 7, 2026

RAG Equity Research Agent

Deployed personal research prototype combining LangGraph orchestration, hybrid RAG over SEC filings, market data, and a conversational agent delivered through a messaging channel on Azure Container Apps. Designed to support analyst workflows with cited evidence, not replace human financial judgment.

Overview

RAG Equity Research Agent is a personal research prototype that aggregates and analyzes multiple financial sources to support evidence-led exploration. Built with LangGraph for multi-agent orchestration, hybrid RAG (BM25 + dense embeddings) for SEC filings analysis, and deployed on Azure Container Apps with a conversational agent delivered through a messaging channel. The system surfaces evidence and analytical steps for human review. It is not investment advice and does not replace professional financial judgment.

Key Features

FeatureDescription
Deep AnalysisAutonomous research combining market data, SEC filings, and sentiment analysis
Hybrid RAGBM25 sparse + dense embeddings with RRF reranking for accurate document retrieval
Multi-Agent SystemLangGraph orchestration with specialized agents (market data, news, RAG, synthesizer)
Real-time DataYahoo Finance integration for live quotes, financials, and historical data
Risk ScoringAutomated risk assessment from 10-K filings with keyword extraction
Messaging AgentConversational interface with inline actions, watchlists, and price alerts

Technology Stack

LayerTechnologies
LLMGroq (Llama 3.3 70B), Azure OpenAI (GPT-4o-mini)
OrchestrationLangGraph, LangChain
RAGQdrant Vector DB, BM25, Hybrid Search, RRF Reranking
Data SourcesYahoo Finance, SEC EDGAR, Reddit API, DuckDuckGo
BackendFastAPI, Pydantic, Python 3.11+
Messaging interfaceAsynchronous handlers for conversations and alerts
InfrastructureDocker, Azure Container Apps, Terraform
CI/CDGitHub Actions (lint, test, security, deploy)
QualityRuff, pytest (53% coverage), Bandit security scan

Messaging Agent Commands

CommandDescription
/analyze TICKERDeep multi-source analysis
/quote TICKERReal-time stock quote
/compare TICKER1 TICKER2Side-by-side comparison
/dcf TICKERDiscounted Cash Flow valuation
/risk TICKERRisk score from 10-K analysis
/peers TICKERAutomatic peer comparison
/reddit TICKERReddit/WSB sentiment analysis
/watchlistManage personal watchlist
/alert TICKER PRICESet price alerts

RAG Pipeline

The hybrid search pipeline combines multiple retrieval strategies:
  • Chunking - SEC filings split into semantic chunks with metadata
  • BM25 Sparse - Traditional keyword matching for exact terms
  • Dense Embeddings - Semantic similarity via text-embedding-ada-002
  • RRF Fusion - Reciprocal Rank Fusion combines both rankings
  • Reranking - Final relevance scoring for top-k results

Cloud Infrastructure

Deployed on Azure with infrastructure-as-code:
  • Container Apps - Serverless containers with scale-to-zero
  • Container Registry - Private Docker image storage
  • Azure OpenAI - GPT-4o-mini with 10K TPM quota
  • Qdrant - Vector database on Container Instance
  • Key Vault - Secure secrets management
  • Log Analytics - Centralized logging and monitoring

Results

MetricValue
Code Coverage53%
Lines of Code10,400+
Test Cases205
CI PipelineLint + Test + Security + Build
Estimated Cost~$50-110/month (Azure)