[ MULTIPLE_ENGAGEMENTS ]
Multi-Model Chat Deployments
What it is
Branded, self-hosted chat interfaces over multiple model providers.
[ THE_PROBLEM ]
Why this existed
Companies want AI chat with their own branding, their own login and their own data boundary — not to send staff and customers to somebody else's consumer product.
[ WHAT_WE_BUILT ]
What we built
A family of chat front-ends built for different clients and internal needs: model selector across Gemini, OpenAI and Claude, streaming responses, markdown and code highlighting, chat history and organisation, auth with account management, subscription and settings services, and light/dark theming. Each deployment is branded and hosted separately.
- Model selector across multiple providers
- Streaming responses with markdown and code highlighting
- Chat history with organisation and search
- Authentication with account management and password reset
- Subscription and user settings services
- Light and dark theming per deployment
[ HOW_IT_IS_USED ]
How a company uses it
A company that wants AI chat on its own domain, with its own branding, its own auth and its own data boundary — rather than sending staff to a third-party consumer product.
Built with
[ COMMON_QUESTIONS ]
Questions clients ask
Why build rather than buy a white-label product?
Often you should buy. Building makes sense when you need a specific model mix, a data boundary a vendor will not commit to, deep integration with your own systems, or a UI that is genuinely yours rather than a recoloured template. If none of those apply, we will say so.
How long does a deployment like this take?
The chat surface itself is not the long pole — auth, billing, history and admin are. Because we have built several, a branded deployment is measured in weeks rather than months, with most of that time going to the integration specifics rather than the chat.
Can it use our own fine-tuned or self-hosted model?
Yes. The provider layer is abstracted, so any OpenAI-compatible endpoint — including a self-hosted or fine-tuned model — drops in as another option in the selector.
[ RELATED_WORK ]
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