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Ask HN: How would you distribute a privacy-first AI chat for teams?

1•shreyaspapi•1h ago
Hi HN,

I’m looking for advice on distribution and positioning for a privacy-first AI chat system we’ve been building.

We have two open-source pieces:

- Conduit — a native mobile client for Open WebUI (GPL). It started as a personal project, but now has teams using it and asking for things like SSO, reverse-proxy auth, and security reviews. - Onera — a privacy-first AI chat backend + client where conversations are end-to-end encrypted, with models running inside TEE enclaves. The operator (including us) can’t see conversation content. The client is fully open source and auditable.

The users we’re seeing are: - companies already using Open WebUI who want a mobile client - teams that want a hosted or self-hosted AI chat but don’t want the operator to access message data - privacy or security-sensitive orgs (internal tools, regulated environments, etc.)

What we’re struggling with isn’t building, it’s distribution: - How do teams usually discover tools like this? - Is it better to lead with "Open WebUI ecosystem" or "private AI chat"? - For companies evaluating something like this, what actually matters early on (audits, reference deployments, integrations, etc.)?

If you were building or buying something like this, how would you approach getting it in front of the right users?

Conduit: https://github.com/cogwheel0/conduit Onera: https://github.com/onera-app/onera

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