Case Study

Multi-Agent Financial Advisory Platform.

AI-powered multi-agent system coordinating specialized financial agents for budgeting, investment analysis, and portfolio management.

FinancialAI AgentsMulti-AgentGuardrails

Overview

A financial services firm needed an intelligent advisory system that could handle the full spectrum of personal finance — from day-to-day budgeting to investment research and portfolio construction. Rather than building a single monolithic AI, we designed a multi-agent architecture that mirrors how professional advisory firms operate: specialized agents coordinated by an orchestrator.

The system routes each client query to the right specialist — a budget agent for spending analysis or an investment agent for market research — then synthesizes their outputs into coherent, personalized advice. Built-in guardrails ensure responsible financial guidance with content filtering, compliance safeguards, and mandatory disclaimers.

3
Coordinated AI Agents
6
Specialized Financial Tools
0.0
Temperature (Deterministic)
Real-time
Market Data Integration

Multi-Agent Architecture

1. Budget Agent — Personal Finance Specialist

Handles personal budgeting and spending analysis using the 50/30/20 framework. Breaks down income into needs, wants, and savings, then analyzes spending patterns against benchmarks to deliver actionable recommendations.

  • Budget Breakdown — 50/30/20 allocation for any income level
  • Spending Analysis — Pattern detection with personalized recommendations
  • Financial Calculator — On-the-fly calculations for savings goals and projections

2. Financial Analysis Agent — Investment Research Specialist

Focuses on investment research, portfolio management, and market analysis. Retrieves real-time stock data, generates risk-adjusted portfolio recommendations, and compares multi-stock performance over configurable time periods.

  • Stock Analysis — Real-time data retrieval with comprehensive performance metrics
  • Portfolio Construction — Risk-based diversified portfolio recommendations
  • Performance Comparison — Multi-stock comparison over custom time periods

3. Orchestrator Agent — Intelligent Coordinator

Routes client queries to the right specialist, coordinates multi-agent workflows for complex requests, and synthesizes outputs into coherent advice. Maintains conversation context across agent interactions for seamless follow-up questions.

  • Intelligent Routing — Determines which specialist agent handles each query
  • Response Synthesis — Combines outputs from multiple agents into unified advice
  • Context Retention — Maintains conversation memory across agent handoffs

Architecture & Infrastructure

The platform is built on a serverless, production-ready architecture using Amazon Bedrock AgentCore for agent runtime management. Each agent operates independently with its own tools, while the orchestrator manages routing, synthesis, and context sharing.

AI & Agents

Strands Agents framework, Claude 3.7 Sonnet via Bedrock, multi-agent orchestration with tool routing

Data & Analytics

Real-time market data via yfinance, pandas for financial analysis, matplotlib for visual reporting

Safety & Compliance

Bedrock Guardrails with content filtering, crypto investment blocking, prompt attack prevention, mandatory disclaimers

Observability

OpenTelemetry distributed tracing, CloudWatch monitoring, structured logging across agent workflows

Responsible AI & Guardrails

Financial advice carries inherent risk, so the platform includes multi-layered safety controls powered by Amazon Bedrock Guardrails:

Content Filtering

Blocks harmful, misleading, or off-topic content

Domain Restrictions

Prevents cryptocurrency and speculative investment advice

Prompt Protection

Defends against injection attacks and jailbreak attempts

Disclaimers

Mandatory financial advice disclaimers on all outputs

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