Dust
Why Dust
Dust lets teams build custom agents grounded in their own company data and business tools. It connects to more than 70 integrations including Slack, Notion, Salesforce, and GitHub, with support for multiple AI models. Agents can be shared across a workspace with built-in human review.
What it does
Dust is a platform for building AI agents that work with your company's data. It connects to more than 70 tools, including Slack, Notion, Google Drive, GitHub, Salesforce and Zendesk. An agent can read from those sources and answer or act from what it finds.
It supports more than 20 models from providers such as OpenAI, Anthropic, Google and Mistral, so you are not tied to one.
Why you would need it
A general chat assistant knows nothing about your business. You end up pasting context in each time, and the answer is only as good as what you remembered to paste.
You feel the pain when the answer sits in a support ticket, a wiki page and a sales call note, and nobody can find all three. An agent that is connected to those places can.
Where it fits
Dust sits on top of the tools you already use. It reads from them and, depending on set-up, acts in them. The vendor lists use cases by team: code debugging and incident response for engineering, ticket triage and response drafting for support, account research for sales, and brief drafting for marketing.
It sits next to other agent builders such as Lindy and Relevance AI. It replaces ad hoc prompting and shared prompt documents.
What stands out
- A dual-layer permission model that separates what an agent can access from what each user may see.
- SOC 2 Type II certification, US or EU data residency, single sign-on and audit logs.
- Model choice across more than 20 models.
- A free tier to try before committing.
My take
I'd pick it when your team already has knowledge spread across several tools and wants agents that respect permissions. The governance features suggest it was built for companies that cannot let an assistant read everything.
What I'd watch is cost. Usage is credit-based, so a busy agent costs more than a quiet one, and it is harder to predict than a flat seat price. Run a real workload for a week and count credits before you scale it to the team.
Verdict
Pick it when you want agents on your own data with real access control. Skip it when you want the cheapest possible chat tool, or when your data lives in one place already covered by that tool's own AI.
Notes
Your note
Before you choose
Credits make cost harder to predict
Plans include a credit allowance, and the free tier has a small one for the workspace. Heavy agents burn credits fast. Estimate with a real workload before choosing between plans, and ask how pooled credits work on Enterprise.
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The 14-day trial is not confirmed on the pricing page
A 14-day trial appeared in a search result, not on the pricing page. Check the current trial terms when you sign up.
Agent quality is your work
Dust gives you the platform, but the agents are only as good as the instructions and the data you connect. Plan time to write instructions, test them and fix the content they draw from.
Alternatives to compare
Look at Lindy, Relevance AI, Zapier Agents and Microsoft Copilot Studio. For a general assistant with company context, compare ChatGPT and Claude.