Collina

Inspiration

Arguments happen everywhere, but strong reasoning often gets lost beneath confidence, interruptions, and rhetorical tricks. We built Collina to make debates clearer and more entertaining by turning argument analysis into a live, game-show-style experience.

What it does

Collina is an AI referee for spoken debates. It separates speakers, generates a live transcript, flags logical fallacies, rewards strong arguments and rebuttals, updates an explainable scoreboard, calls fouls out loud, and crowns a winner with a punchy final verdict.

How we built it

• Next.js, React, TypeScript, and Tailwind CSS: Power the debate interface, transcript, foul flags, animations, and live scoreboard.
• Deepgram: Provides speech recognition, speaker diarization, and spoken referee callouts.
• Claude: Analyzes each turn for argument strength and fallacies, then generates the final verdict.
• Redis Vector Search: Retrieves the most relevant definitions from our 17-fallacy taxonomy for grounded analysis.
• Hugging Face Transformers: Generates local sentence embeddings for semantic fallacy retrieval.

A shared debate client supports both a stage-safe prerecorded demo and a live microphone mode using the same analysis and scoring pipeline.

Challenges we faced

Our biggest challenge was balancing speed with accuracy. The referee must react quickly enough to feel live, but false fallacy calls can make the entire experience feel unfair. We also had to design scoring rules that were consistent, explainable, and immediately understandable to an audience.

Reliability was equally important, so we built an offline mock demo and a local semantic-search fallback that keep the core experience working when an external service is unavailable.

Built With

• anthropic-claude
• deepgram
• hugging-face-sentence-embeddings
• next.js
• react
• redis-vector-search
• tailwind-css
• transformers.js
• typescript
• web-audio-api