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This looks really great! Quick question, is there any support for using local models?
Yes! You can use local models through Ollama and LM Studio. We do some special handling when you use local models, such as suppressing background agents when you chat, so the model is not overwhelmed.
If I edit or delete a note straight in the vault (outside the app), does the graph re-index it or go stale?
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Fair list: 1. True - no OS-level container today. The constraint is approval gating: consequential actions surface as a permission ask before they run (a separate supervisor LLM flags anything outside your intent). 2. True today. We'd deprioritized generic IMAP (drafts-on-thread is unreliable cross-provider), but you're the third person in this thread to raise it, so we'll scope it properly. 3/4/5. Today: Deepgram fo…
Thank you for addressing my list. I'd like to use it, but requirements on non-local services is a deal breaker for me. Right now, with my Nanoclaw, I'm running it in a container on a VM on proxmox. If things get bad, I lose a backed up machine and any services it has credentials to. I can understand why IMAP is a pain. There's plenty of functions that can trash mailboxes. I don't envy you all in this task. For my STT…
Will go through these and see what we could support. If you drop your stack into a GitHub issue, that's the best place for us to work through it (and for others to +1).
My aim is to build a truly local app using only tiny/small models. I have had really good results from Qwen 3.5 1B, 4B, etc. Also, Gliner or similar models for different uses. SQLite + sqlite-vec + Tantivy + a tiny embedding model will stay as my go to.
In my case, coding agent is a separate product. I have https://github.com/brainless/nocodo for that. nocodo is also built for tiny/small models from the ground up. And recently I started building a wGPU based UI framework to build both these apps as native UI apps in Rust: https://github.com/brainless/akar. I also want e2e encrypted team/family sharing in my products.
Thank you for the inspiration. Would love to share notes and follow your progress.
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This isn't exactly what you're looking for but for just the coding part, I am working on https://www.buildautomaton.com to allow multiple people to participate on a shared coding session. It's also bring your own agent subscription, uses ACP to talk to any agent (Cursor, Claude, Codex, etc), and is end-to-end encrypted for most of your IP.
Looks great, but the pricing model is a challenge for a small team. If there was a generous trial period (for testing) with a lower small team price I might be able to consider it, but it’s hard to justify constantly increasing AI and compute costs (already paying for several model subscriptions, existing orchestration tools… in addition to typical infrastructure)
I have a project on very similar lines, https://github.com/brainless/dwata , which I have not been developing for the past few months. I have been meaning to get back to it and I really like what I see on your project page. My aim is to build a truly local app using only tiny/small models. I have had really good results from Qwen 3.5 1B, 4B, etc. Also, Gliner or similar models for different uses. SQLite + sqlite-vec…
I have a project on very similar lines, https://github.com/brainless/dwata , which I have not been developing for the past few months. I have been meaning to get back to it and I really like what I see on your project page. My aim is to build a truly local app using only tiny/small models. I have had really good results from Qwen 3.5 1B, 4B, etc. Also, Gliner or similar models for different uses. SQLite + sqlite-vec…
Thank you! And would love to share notes. The tiny-models-only discipline is interesting; we do special handling just to keep local models from being overwhelmed, so I'd like to hear how far you've pushed it. You can find me on Discord, if you want to chat on anything.
Rowboat markets itself as "local-first," but if you look in the actual codebase, transcription is Deepgram cloud, voice is ElevenLabs, analytics is PostHog, and the LLM is a cloud API.
Local-first for us means: your data such as emails, notes, meetings, the knowledge graph - lives on your machine as plain Markdown, readable and deletable, and the app doesn't require our servers to run. You can also go fully local for the LLM with Ollama or LM Studio. We do special handling there, like suppressing background agents during chat, so local models aren't overwhelmed. That's the core of the product. Some…
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Yes! You can use local models through Ollama and LM Studio. We do some special handling when you use local models, such as suppressing background agents when you chat, so the model is not overwhelmed.
sweet, is there any plans to implement VLLM in the future?
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Local-first for us means: your data such as emails, notes, meetings, the knowledge graph - lives on your machine as plain Markdown, readable and deletable, and the app doesn't require our servers to run. You can also go fully local for the LLM with Ollama or LM Studio. We do special handling there, like suppressing background agents during chat, so local models aren't overwhelmed. That's the core of the product. Some…
Instead of having to define what “local-first” means to you personally you should emphasize that the data lives on your local machine. For some example messaging take a look at how Apple is marketing their new Siri AI.