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FinTech

Multi-Agent Financial Analysis Across Data, APIs, and Charts

Financial analysis lived in separate databases, vendor APIs, and charting tools, so answering a question meant stitching those sources together by hand.

Multi-Agent Architecture Database + API Tooling Charting Integration
Business Impact
Helped design and ship a multi-agent analysis system over live data sources

The Problem

Analysts already had the raw material — warehouse tables, market and fundamentals APIs, and charting tools — but none of it worked as one system. A single question meant hopping between query consoles, API docs, and chart UIs, then assembling the answer by hand. I helped design and implement an agentic layer that could use those resources together.

The Architecture

flowchart TB
  subgraph sources [Analysis Resources]
      DBs[(Databases)]
      APIs[Market and Fundamentals APIs]
      Charts[Charting Resources]
  end

  subgraph agents [Multi-Agent System]
      Planner[Planner Agent]
      DataAgent[Data Agent]
      MarketAgent[API Agent]
      ChartAgent[Charting Agent]
      Synthesizer[Synthesis Agent]
  end

  subgraph output [Analysis Output]
      Brief[Analysis Brief]
      Figures[Charts and Figures]
  end

  Planner --> DataAgent
  Planner --> MarketAgent
  Planner --> ChartAgent

  DataAgent --> DBs
  MarketAgent --> APIs
  ChartAgent --> Charts

  DataAgent --> Synthesizer
  MarketAgent --> Synthesizer
  ChartAgent --> Synthesizer
  Synthesizer --> Brief
  Synthesizer --> Figures

Multi-Agent Tooling

The system treats each source as a capability, not a destination:

  1. Planner Agent: Breaks an analysis question into retrieval, computation, and visualization steps
  2. Data Agent: Queries internal databases for positions, history, and reference data
  3. API Agent: Pulls live and historical series from external financial APIs
  4. Charting Agent: Renders the relevant views from the charting stack
  5. Synthesis Agent: Combines those results into a brief an analyst can actually use

Agents share context so a chart request can follow from a database result, and an API pull can fill gaps the warehouse does not have.

Tech Stack

  • Multi-agent orchestration — Planner plus specialist agents with tool access
  • SQL / warehouse access — Structured financial data
  • External APIs — Market and fundamentals feeds
  • Charting resources — Figures generated as part of the analysis path

The Impact

The work was design and implementation of the analysis system itself: a multi-agent architecture that can move across databases, APIs, and charting resources in one pass, instead of leaving that stitching to the analyst.