PitchFight AI is an AI platform designed to help student founders practice their startup pitches by simulating real-world questioning scenarios. The tool allows users to engage in structured pitch battles with AI judges that mimic the scrutiny of investors and technical experts. Founders can prepare for tough questions about market viability, competitive advantage, and traction before presenting their ideas in actual pitch events. The app also provides a scorecard to assess what works and what needs improvement. The tool is built for the Hugging Face Build Small Hackathon and is submitted for several categories, including Backyard AI and NVIDIA Nemotron Quest.
The platform uses NVIDIA Nemotron as the core model for judge reasoning and feedback. The AI model is accessed through an API, with the API key stored securely as a Hugging Face Space secret. PitchFight AI runs on Hugging Face Spaces as a Gradio app, but the interface is fully custom-built rather than using default Gradio components. The frontend is designed to resemble a pitch battle screen, featuring opponent cards, a confidence meter, round flow, and scorecard feedback. The backend manages pitch structuring, judge logic, multi-round battle states, and final scoring.
The app was developed to address the gap in pitch preparation for student founders. Unlike generic pitch feedback tools, PitchFight AI focuses on creating pressure by asking founders to defend their assumptions under simulated scrutiny. The tool was built for the Hugging Face Build Small Hackathon and is submitted for categories like Backyard AI and NVIDIA Nemotron Quest. It emphasizes practical tools for student founders rather than theoretical approaches.
Source: huggingface
