AI Agents for increased productivity and efficiency
summary
A practical account of building an EY multi-agent valuation tool that combines RAG retrieval, a central orchestrator, memory, and agents that run SQL/Python code and generate PowerPoint/Word reports; deployments use code-interpreter style custom Python functions to calculate valuations and a news/sentiment agent to fetch external signals. Real projects report 50–60% faster end-to-end process time and fewer errors, with the orchestrator responsible to assign and collect agent outputs.
AI-written summary · about
chapters (7)
- 0:00AI agents introduction
- 1:28Generative to agentic AI
- 3:15Agents automate tasks
- 6:28Orchestrating agents
- 9:22Multi-agent systems example
- 11:52Efficiency gains and trends
- 12:57Q&A
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