CrawlChat is built for software teams whose documentation is the front line of support. Instead of a generic chatbot bolted onto a marketing site, it indexes the sources developers actually use — documentation sites, API references, GitHub issues and pull requests, Notion pages, Confluence spaces, Linear projects — and keeps each source re-synced on its own schedule. Every answer returned by the agent carries links back to the page it came from, which reduces hallucination and gives users a way to verify the details themselves.
The platform is deliberately omni-channel. The same agent can be dropped in as a website widget, added as a Slack app to a workspace, invited to a Discord server as a bot, wired into GitHub discussions, exposed through an MCP server for AI coding tools, or called from your own application over a REST API. Because behaviour, tone and escalation rules are shared across channels, users get a consistent experience whether they ask inside the product or in a community server.
Beyond chat, CrawlChat ships a documentation analytics layer. It categorises incoming questions, applies sentiment analysis, flags low-rated answers and produces a list of data gaps — topics users asked about that the existing sources do not cover clearly. Teams can accept or reject each gap suggestion and turn recurring questions into concrete documentation improvements. Plans are credit-based, starting with a free trial and scaling to enterprise arrangements.
