tanchi
Open-source AI prospecting agent you can self-host
What it does
Tanchi sources prospects at night, researches them, writes the outreach, and learns from what actually gets replies. You approve your queue in ten minutes each morning. Email is the only automated channel. AGPL-3.0, self-host free with one Docker command.
Autonomous B2B prospecting engine, open source and self-hostable. The AI sources, researches and writes every evening. You review your queue in ten minutes.
The AI sources, researches and writes your outreach every evening. You review your queue in ten minutes. While you sleep, the loop turns. Each step feeds the next, and every pass improves the one after. The Profiler verifies every fact on the prospect's site and LinkedIn. Email automated, the rest prepared. Never the other way around. The Copywriter writes from the file and the playbook. No invented facts. The Profiler verifies every fact on the prospect's site and LinkedIn. Email automated, the rest prepared. Never the other way around. The Copywriter writes from the file and the playbook. No invented facts. Writes from the file and the playbook. Never invents a fact. Never a client, a…from tanchi.io
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I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
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Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
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Launched alongside, August 2026
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Hello HN! I found that picking out plausible but diverse skin tones for my digital art and game development projects was kind of difficult, and I got curious about if there was a way to define a color space that made it easy. I've built a color picker and procedural generation algorithm based on the space as well as a bunch of other fun js features and demos throughout the page that use the equations. If you find it interesting, I have lots of explanations of how I built it and what properties the space has. The methodology might be a bit shaky, but hopefully the result is as helpful for…
Life & fun · Aug 2026 · toneyalexander.github.io


I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
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