vLLM vs DocsBot AI

DocsBot's feed mixes real product announcements with lead-gen education posts, and the product half now covers three layers at once: what the bot can read, what it is allowed to see, and where it runs. Ingestion and retrieval got the early work — Advanced Document Parsing for structured PDFs and Office files, Source Tags to scope a bot's search, and native connectors to Salesforce Knowledge, Dropbox, Box, OneDrive, GitHub and Bitbucket. On top of that sits browser-side PII redaction and a Slack integration that now streams responses and runs most AI Actions. Metering runs through AI Credits with BYOK model costs.

The center of gravity is shifting from a knowledge-answering widget on a customer's site to an agent that lives in the buyer's own tools and takes actions there. Each release moves one constraint: parsing and connectors widen what it knows, Source Tags narrow what it retrieves, redaction bounds what leaves the browser, and Slack changes who talks to it. Model upgrades arrive as credit-priced options rather than platform events, which keeps the pricing surface stable while capability moves.

Expect the same AI Actions and streaming treatment applied to a second workplace surface — Teams is the obvious next channel given the OneDrive and SharePoint-adjacent connector work — and further tightening of the permission story around what a workplace agent may execute.