Using Classical ML to Empower AI Agents

AI agents can be made more powerful and reliable by incorporating classical machine learning models as tools. While LLMs excel at language and orchestration, they are often inaccurate, expensive, and uninterpretable for specific analytical tasks where classical models provide superior accuracy, control, and cost-efficiency. Implementation can be done through direct API calls from the agent to the model or by pre-calculating inferences and storing them in a database for the agent to retrieve. This hybrid approach leverages the strengths of both LLMs and classical ML to build more robust and capable systems.