On-device AI, indie software, privacy by default.
Technical writeups and founder essays. Why we build AI that runs on your hardware, what we've learned shipping it, and what the post-cloud era of AI software actually looks like.
Why I Built My Own AI: The Case for Self-Hosted Domain Agents
In 2024 I got tired of paying OpenAI to know everything about my life. So I built Kulvex AI — 80B parameter model on consumer GPUs, 17 domain agents from Zigbee lights to self-evolution, ~$155/month amortized. Why, how, and the honest part.
Read postBuilding a Clinical Speech-Therapy App With a Real SLP: 4 Lessons From PhoenixSteps
My son's speech-language pathologist drives all the clinical content. Four lessons from six months co-designing a pediatric clinical iOS app — including how we taught Vision to detect tongue direction when Apple won't.
Read postLive Captions Without Sending Your Voice to the Cloud: Building ClearCaps
My dad started losing his hearing five years ago. Every captioning app required uploading audio to a cloud — which doesn't work for medical visits, family conversations, or anywhere wifi is bad. The founder story and the technical pieces (WhisperKit, Pyannote, Apple Translate) that make on-device live captioning actually work on iPhone in 2026.
Read postApple Silicon as a Serious AI Dev Box: What an M4 Max Actually Does With a 70B Model
Mac M-series has quietly become one of the best local AI dev boxes on the market. Real tokens/sec numbers on M2 Pro through M3 Ultra, where unified memory beats NVIDIA, and why we built SiliconMon to see what your chip is actually doing.
Read postStatic Analysis Without Sending Your Code to the Cloud: Building KCode
Snyk, SonarQube Cloud, GitHub Advanced Security — all ask the same thing: ship your source code to us. For a lot of teams, that's not negotiable. Here's how we built KCode with a local LLM verifier, what F1 0.96 actually buys you, and the honest revenue numbers behind it.
Read postWhy We Run LLMs On-Device in 2026
The cloud isn't the only place for AI anymore. The math on cost, privacy, latency, and vendor lock-in has flipped. Here's the full case for running LLMs on your own hardware — and what we ship at AstroLexis to make it work.
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