Build an AI Finance Agent with Amazon Bedrock
Build an AI agent that autonomously writes Python code to analyze your spending data using Amazon Bedrock and Code Interpreter.
Difficulty
Beginner
Time to complete
45 minutes
Availability
Free
BUILD
What you'll build
Build an AI finance agent with Amazon Bedrock that writes its own Python code. Upload spending data, watch the agent analyze it autonomously, iterate on instructions, and add cross-session memory.
1. Set Up Amazon Bedrock
Navigate to Amazon Bedrock, confirm Amazon Nova 2 Lite is available, and preview the Agents feature.
2. Build Your AI Agent
Create a Bedrock Agent with custom instructions, select a foundation model, and enable Code Interpreter.
3. Analyze Spending Data
Upload a transactions CSV and watch the agent autonomously write Python to break down your spending.
4. Iterate with Agent Traces
Inspect the Python code your agent wrote, then refine instructions to improve output quality.
5. Add Cross-Session Memory
Enable session summarization so your agent remembers spending goals across conversations.
Your portfolio builds as you work.
Every project documents itself as you go. Finish the work, and your proof is ready to share.
PROJECT
Real world application
Skills you'll learn
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Agentic AI
Build AI agents that reason through tasks and take actions autonomously
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Code Interpreter
Enable agents to write and execute Python code in a sandboxed environment
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Prompt Engineering
Write and refine natural language instructions that control agent behavior
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Agent Traces
Inspect step-by-step reasoning to debug and improve agent performance
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Agent Memory
Configure session summarization for context retention across conversations
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Data Analysis
Upload financial data and get automated spending breakdowns and budget recommendations
Tech stack
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Amazon Bedrock
Agent framework that lets you build AI agents with reasoning, code execution, and memory
OUTCOME
Where this leads.
Relevant Jobs
Roles where these skills matter:
- AI Engineer
- Generative AI Developer
- Solutions Architect
- AI Product Builder
Generative AI on AWS Roadmap
Keep building with Amazon Bedrock. This roadmap covers chatbots, agents, RAG, and more across the full generative AI stack on AWS.
Generative AI on AWS Roadmap
Continue the JourneyFAQs
Everything you need to know
No. You do not write any Python code yourself. The AI agent writes and executes Python autonomously using Code Interpreter. You configure the agent through the AWS Console and give it instructions in plain English.
Less than $0.01. Amazon Bedrock charges per token during agent interactions. Amazon Nova 2 Lite is one of the cheapest models available. There are no running servers or ongoing costs after you finish.
A Bedrock Agent can reason through multi-step tasks, decide what actions to take, write and run code, and iterate on results. A chatbot just answers questions. An agent figures out the steps on its own and executes them.
Code Interpreter gives your agent the ability to write, execute, and debug Python code in a secure sandbox. When you ask the agent to analyze spending data, it writes Python using libraries like pandas, runs the code, and returns the results. You see the actual code in the agent trace.
Agent memory enables cross-session context retention through session summarization. After each conversation, the agent creates a summary of key points. When a new session starts, those summaries are provided as context. This means your finance agent can remember spending goals and track progress over time.
Yes. Bedrock Agents support multiple foundation models including Anthropic Claude and Meta Llama. Amazon Nova 2 Lite is used here because it requires no manual enablement and is the most affordable option for data analysis tasks.
One Project. Real Skills.
45 minutes from now, you'll have completed Build an AI Finance Agent with Amazon Bedrock. No prior experience needed. Just step-by-step guidance and a real project for your portfolio.
Beginner-friendly