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BaseThread vs Dust
Dust is a platform for building assistants over your connected data. BaseThread is the context your existing AI tools read and write, no new assistant required.
In short
Dust is a platform for building AI assistants and agents on top of your connected company data, used inside Dust. BaseThread is a shared context layer: instead of adopting a new assistant, the AI tools your team already uses (Claude Code, Cursor, ChatGPT) read and write one current context over MCP. Dust gives you assistants to build and run; BaseThread makes the tools you already have smarter about your team.
Dust
Enterprise AI assistants
Dust is a capable platform for teams that want to build and deploy custom AI assistants and agents over their company data, with connectors, a builder, and a place for non-technical teammates to use those assistants. If your goal is to ship internal assistants, Dust gives you the scaffolding to do it.
Where BaseThread is different
Team shared context
Dust connects to your tools and gives you assistants to build and run inside Dust. BaseThread never connects to your tools and adds no new assistant. Your AI reads your sources with its own access and writes a curated signal into a graph that the AI tools you already use read over MCP. The context flows into your daily tools instead of into a separate assistant you have to adopt and maintain.
Side by side
BaseThread and Dust, dimension by dimension
The dimensions a team actually evaluates. Wide tables scroll horizontally on phones.
BaseThread
Dust
Honest take
When to use which
Use Dust when
You want to build and deploy custom AI assistants and agents over your company data for your team to use.
Use BaseThread when
You want the AI tools your team already uses to share one current context, without adopting a new assistant.
FAQ
BaseThread vs Dust, answered
For teams who don't want to adopt a new assistant, yes. Dust is a platform for building assistants over connected data. BaseThread gives the AI tools your team already uses one shared context over MCP, so you make existing tools smarter instead of building and maintaining new ones.
Go deeper
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