What if your AI could organise your knowledge without sending it to the cloud?

That's the idea behind Knemora, an open-source, local-first AI Second Brain I've been building in my spare time.

Imagine turning your documents into interconnected knowledge, exploring relationships, and asking an AI questions about everything you've collected.

All running locally, on your own machine.

A few weeks after releasing the first alpha, I realized something:

Building an AI application is one thing. Making it genuinely useful every day is another.

So I kept building.

Knemora v0.2.0-alpha is here!

This update focuses on making Knemora more reliable, responsive, and easier to use.

Here's what's new:

• Better conversation continuity and automatic language matching.
• Wiki and Direct Chat Modes.
• Fast and Deep reasoning controls.
• Stronger knowledge compilation and relationships.
• Gemma 4 E4B joins the tested local model registry.

I also ran a small benchmark comparing Qwen3-8B and Gemma 4 E4B.

In this particular Direct-mode test, Gemma delivered 20.6% lower median application latency and 31.1% higher decode throughput.

Not a universal benchmark, just another step toward making local AI more responsive.

Knemora is still in alpha, and there's plenty left to improve. I'm building it one iteration at a time, with the goal of reaching a stable v1.0.0.

Would you use a local AI to build your own connected knowledge base? What would you expect it to do?

GitHub: https://github.com/federicolaterra/knemora

Website: https://knemora.space

Watch the demo: https://www.youtube.com/watch?v=kl5qNrWPOnY

Feedback and contributions are always welcome!