FinTech Multi-Agent AI Stock Analysis NSE/BSE LangGraph

StockAI India

Client
Codevally
Industry
FinTech / Stock Market
Duration
2 months
Team count
2
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Overview

Indian retail investors face an information overload problem — technical indicators, quarterly filings, FII/DII flows, and breaking news all move stock prices, but no consumer-facing tool fuses them across NSE and BSE coverage. Most traders end up copying tips from Telegram channels or watching lagging broker terminals, with no visibility into why a stock should be bought or sold.


Codevally built StockAI India, a multi-agent AI platform that turns any NSE/BSE ticker into an institutional-grade BUY, SELL, or HOLD recommendation in around 25 seconds. A LangGraph orchestrator runs four specialist agents in parallel, and a master agent synthesizes their signals into a single weighted decision — with full transparency over the evidence and risk flags behind it.


The Solution delivers institutional-grade equity analysis by providing:

  • Technical Agent: Multi-timeframe RSI, MACD, EMA stacks, ADX, OBV, and automatic candlestick pattern detection.
  • Fundamental Agent: Sector-relative P/E, P/B, ROE, debt-to-equity, earnings and revenue trends with LLM-generated interpretation.
  • Market Context Agent: FII/DII flows, Nifty/Sensex/BankNifty regimes, India VIX, global indices, and sector relative strength.
  • News Sentiment Agent: NewsAPI, Economic Times, and Reuters feeds processed through VADER pre-filtering plus LLM event detection.
  • Master Agent: Weighted synthesis of all four agents into a conviction-scored BUY/SELL call with target price, stop loss, key evidence, and risk flags.

This Codevally product condenses what would take a research analyst hours of cross-referencing into a single 25-second pipeline — every recommendation ships with explicit evidence and risk flags, so users always see why the model called BUY or SELL, no black-box scores. The fuzzy ticker resolver, free public access, and Next.js + Tailwind interface remove the last barriers between retail investors and institutional-grade decision support.

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Bringing institutional-grade equity analysis to every Indian retail trader.

01. Discovery and Architecture

Mapped Indian retail trader pain points across NSE and BSE, defined four agent boundaries, scored data sources, and selected LangGraph for parallel orchestration.

02. Multi-Agent Engineering

Built specialist agents — technical, fundamental, market context, news — each wired to its own data feed and LLM-backed analysis layer with deterministic scoring.

03. Master Synthesizer

Engineered the weighted decision agent that fuses all four signals into a single BUY/SELL/HOLD call with conviction score, target price, stop loss, and evidence.

04. Frontend and Ticker Resolver

Shipped a Next.js plus Tailwind interface with fuzzy NSE/BSE ticker search, real-time agent progress display, and structured recommendation rendering.

05. Launch and Hardening

Hardened rate limits, caching, error handling, and free-tier guards. Public launch with telemetry tracking agent latency, query patterns, and recommendation accuracy.
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