NeuroLite

Inspiration

We wanted to make AI feel like a real discussion, not a single opinion. NeuroLite was inspired by the idea that better decisions come from multiple perspectives.

What it does

NeuroLite takes a prompt, sends it to multiple AI personas in parallel, and combines their responses into one final result with judging insights, a biggest risk, and a next step.

How we built it

We built it with Vite, React, and a live Ollama-compatible model endpoint. Each persona has its own prompt, and the app merges their structured outputs into a final decision.

Challenges we ran into

The hardest part was keeping the responses consistent, structured, and reliable enough for a live demo while handling failures gracefully.

Accomplishments that we're proud of

We created a working multi-agent AI experience that feels distinct, fast, and memorable, while still producing useful final outputs.

What we learned

We learned a lot about prompt engineering, agent orchestration, and how much personality changes the way AI responses are perceived.

What's next for NeuroLite

Next, we want to add memory, RAG, visual data layers, and more specialized decision modes like city planning and smart city analysis.

Built With

• agent
• ai
• api
• css
• javascript
• ollama-compatible
• orchestration
• parallel
• qwen3:8b
• react
• vite