Building an Explainable AI Lead Scoring Engine with FastAPI

A developer built a personal project called the Lead Qualification and Scoring Engine to help sales teams prioritize prospects. The application checks leads against an Ideal Customer Profile, produces a score from 0 to 100, and suggests a classification and next action. Its design uses AI to interpret unstructured lead information, while deterministic Python code applies configurable business rules to calculate the final score. Scoring criteria such as industry relevance, decision-maker role, and buying signals are stored in a JSON file, so each score can be explained and tested. The system is built with FastAPI, Pydantic, SQLAlchemy, SQLite, and Pytest.
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