Sentient OS

Nobody's built truly proactive AI, because it requires running inference on your entire life. In the cloud, that's insanely expensive and a privacy nightmare. But not on your own chip. Every night, Sentient's on-device LLM wakes your Mac and understands what's new in your life (email, messages, files, Granola transcripts...), entirely locally, and distills it into a knowledge base. You wake up to your work already prepared: the reply you forgot, drafted from your own context; the subscription you never use renewing tomorrow, caught; the report you promised in the group chat, ready to send. Everything is one click from firing through computer use, and nothing fires until you click. Or click your Mac notch anytime and say "finish this for me." Sidekick takes over the thing you were doing with its own cursor while you move on. On-device inference at this scale was supposed to be impossible: devices too slow, and models too dumb. So we built the stack ourselves: a custom LiteRT-LM fork (KV-cache reuse, speculative decoding, custom k-quants) that runs nightly on 8 GB Macs. The user's hardware does ~90% of the compute, and their own ChatGPT or Claude subscription does the rest, so our marginal cost is ~$0, and our servers store nothing. Our alpha soft-launch was top post of the month on r/macapps (688 upvotes), and we launched to 4000+ users in our first week with $0 marketing. We're free and open source for consumers; the same engine on the work stack (Slack, Granola, Linear, Notion) is the enterprise business. Sentient OS raised ~$1M in pre-seed, backed by YC, Afore, and the a16z Speedrun scout fund.

San Francisco, CA, USA

• Artificial Intelligence
• Productivity
• AI