Dust
Company AI workspace where teams build agents on internal data with connectors, workflows, code interpreter and enterprise governance.
Evaluation
What to know
Editorial notes based on the vendor's own documentation and public pricing, plus hands-on testing where a score or review is shown above. They describe fit for a job, not absolute quality.
Best for
- Startups and mid-market teams deploying internal AI agents
- Ops and support groups answering from shared docs
- Companies that need governance around model and data access
Not ideal for
- Individuals wanting a personal ChatGPT substitute only
- Orgs unwilling to connect SaaS knowledge bases
- Buyers needing a pure document editor
Key features
- Agents grounded on connected company data with citations
- Connectors for Drive, Notion, Slack, GitHub and more
- Workflows, tools and code interpreter for multi-step jobs
- Spaces and admin governance for team knowledge
- Free, Pro and Enterprise seat packaging
Pros
- Designed for internal knowledge rather than generic web chat
- Citations and connectors reduce hallucinated company answers
- Enterprise controls match IT expectations better than consumer bots
Cons
- Value depends on connecting real data sources first
- Seat pricing can scale quickly across large orgs
- Builder complexity is overkill for one-person note Q&A
ToolifyNav verdict
Dust is the company-agent workspace in this Office pair. Connectors, citations and admin controls are why IT-friendly teams shortlist it. Empty workspaces without data connectors will feel underwhelming, and seat math matters at scale. For personal meeting notes alone, Tactiq is narrower and faster to adopt. Dust is for companies ready to wire knowledge and govern agents. It is wasted on empty workspaces and lone chat curiosity. Seat math and connector quality determine ROI more than model brand names. Treat empty workspaces as failed pilots: connectors and governance are prerequisites, not optional polish, before seat counts expand across departments that expect reliable cited answers.
About
About Dust
Dust (dust.tt) positions itself as the operating layer for company AI agents. Teams connect Drive, Notion, Slack, GitHub and other sources, then design agents that answer with citations, run workflows and use tools such as a code interpreter. Spaces organize knowledge and agents by team, while admin controls cover data sources, model choices and usage.
Packaging is seat-based. Public materials describe a Free plan for individuals or tiny teams, then Pro and Enterprise tiers that unlock more agents, higher message limits, SSO, dedicated support and advanced governance. Exact seat prices should be read from dust.tt/pricing because Dust iterates packaging with model costs. The product assumes companies already have knowledge scattered across SaaS tools and want agents that respect that topology.
Dust is less a single chatbot and more a builder for internal copilots.
Successful Dust deployments treat connector setup as a project, not a toggle. Start with one well-owned knowledge space (for example support macros) before opening company-wide agent building. Without that discipline, agents either answer from thin air or expose documents that should stay restricted.
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