A Telegram AI bot with an on-premises model
The model and knowledge base can remain on company servers, but every user message still traverses Telegram, so local processing is not equivalent to a fully closed channel.
Separate transport from processing
Telegram delivers an update to an internal gateway that authenticates, applies policy and invokes local retrieval and inference. Mark all data crossing the internal boundary.
Mark user text and generated replies as external-channel data even when retrieval and inference remain entirely on company hardware.
Map chat identity to corporate access
A chat identifier alone does not authorise internal documents. Use managed enrolment, revocation and permission filtering on every retrieval and action.
Map chat identity through managed enrolment to a revocable corporate account and enforce document permissions before retrieval.
Bound resources and actions
Apply per-user rates, file and context limits, cited answers, allowlisted tools, confirmation before writes and an operator handoff carrying status and history.
Rate limits, file bounds, citations, allowlisted tools and confirmation for writes protect both infrastructure and business systems.
Test both products together
Test bot delivery and retry behaviour separately from model quality, retrieval, hostile content and tools, then exercise the complete chain with a dedicated test bot.
Exercise delivery retries and bot interactions separately, then test the full path through local retrieval, model, tools and operator handoff.
Continue with the underlying material
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