An AI-powered financial risk intelligence agent built with LangGraph and Claude Sonnet 4, connected to 163 tools via the SAJHA MCP Server with SSE streaming.
An AI-powered financial risk intelligence agent built with LangGraph and Claude Sonnet 4, connected to 163 tools via the SAJHA MCP Server. Uses SSE streaming for real-time analysis.
Financial risk analysis requires synthesizing data across dozens of sources — market data, credit metrics, regulatory filings, internal models. Traditional dashboards show data; they don’t reason about it. Risk teams needed an AI agent that could orchestrate across multiple financial data tools, reason through complex risk scenarios, and stream findings in real time.
Built a stateful AI agent using LangGraph’s graph-based orchestration framework with Claude Sonnet 4 as the reasoning engine. Integrated the SAJHA MCP (Model Context Protocol) Server giving the agent access to 163 financial tools. SSE (Server-Sent Events) streaming delivers analysis token-by-token. The agent can traverse multi-step workflows: retrieve data, compute risk metrics, cross-reference regulatory requirements, and synthesize a coherent risk assessment.
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