Dust
by Dust
Custom AI assistants connected to company data sources such as Notion, Slack, Google Drive, and GitHub. Dust is an enterprise AI assistant platform founded in 2023 in Paris, France. The product allows non-developer teams to build custom assistants that retrieve answers from connected data sources rather than relying solely on a base model.
Performance Scores
2 rankings evaluated
Score range: 7.3 – 7.6
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#5Best AI Agent Builders for Non-Developers in 2026
Score: 7.6 · Best for: Mid-market and enterprise teams building internal Slack-based knowledge assistants
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#6Best LLM App Platforms for Building AI Agents in 2026
Score: 7.3 · Best for: Companies that want a shared AI workspace connected to internal documents and tools, with workspace-level governance.
Key Facts
| Attribute | Value | As of | Source |
|---|---|---|---|
| Pricing | Pro at approximately $29/user/month; Enterprise custom; 14-day trial | Apr 2026 | Dust |
| Connectors | Native connectors: Notion, Slack, Google Drive, GitHub, Intercom, Confluence, Microsoft 365 (7+ sources) | Apr 2026 | Dust docs |
| Founded | 2023 | Apr 2026 | Sequoia Capital |
| Key Differentiator | Founded by Stanislas Polu (ex-OpenAI) with $16M Sequoia funding; permission-aware RAG over connected data | Apr 2026 | Dust |
Strengths
- ●Native ingestion connectors for Notion, Drive, Slack, GitHub, and Intercom
- ●Agents can be deployed inside Slack as chat-native assistants for employees
- ●Workspace-grade access control and per-source permissioning
- ●Strong fit for internal knowledge assistants and on-boarding bots
- ●Strong native connectors to internal knowledge sources
- ●Workspace governance with audit logs and per-assistant permissions
- ●Suits horizontal company-wide deployment more than narrow product use cases
Limitations
- ●Less suited to outbound or always-on agents that act on email and calendar events
- ●Visual workflow building is shallower than Gumloop or Relay.app
- ●Pricing is workspace-based and may exceed credit-based tools at small team sizes
- ●Builder is lighter than dedicated agent or workflow platforms
- ●Targets internal company use — less suited for customer-facing product agents
- ●Fewer model-routing controls than Vellum or CrewAI
Based on evaluations in 2 rankings: Best AI Agent Builders for Non-Developers in 2026, Best LLM App Platforms for Building AI Agents in 2026
About Dust
Dust is an enterprise AI assistant platform founded in 2023 in Paris, France. The product allows non-developer teams to build custom assistants that retrieve answers from connected data sources rather than relying solely on a base model.
Dust ships with managed connectors for Notion, Slack, Google Drive, GitHub, Intercom, Confluence, and Microsoft 365. Documents are indexed and made available to assistants through retrieval-augmented generation, with permissions inherited from the source system. Builders compose assistants from instructions, model choice (Claude, GPT-4 family, Mistral), tools, and connected data spaces. The platform also offers Dust Apps for custom code-based pipelines. Pricing is per-seat: Pro at approximately $29/user/month and Enterprise custom-quoted, with a 14-day trial. Source-level permissions and SSO are available on Enterprise.
Integrations (4)
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AI Agent PlatformsLindy
AI agent platform for building autonomous digital workers
AI Agent PlatformsSee How It Ranks
Best AI Agent Builders for Non-Developers in 2026
A ranked list of the best AI agent builders for non-developers in 2026. This ranking evaluates platforms that let operations, marketing, and customer-success teams construct multi-step AI agents without writing production code. The shortlist includes Lindy, Gumloop, Relay.app, Relevance AI, and Dust. Tools were evaluated on visual agent design, model and tool integration, observability and debugging, pricing accessibility, and documentation depth. Stack AI and Magic Loops were considered but excluded where the platform was not present in the database at evaluation time.
Best LLM App Platforms for Building AI Agents in 2026
A ranked list of platforms for building LLM-powered applications and AI agents in 2026. This ranking covers tools that combine prompt engineering, model orchestration, retrieval-augmented generation, tool calling, and deployment into a single workflow for product and engineering teams. Entries span low-code agent builders (Gumloop, Lindy, Relevance AI), code-first orchestration (CrewAI), open-source visual builders (Langflow), enterprise prompt engineering platforms (Vellum), and team-oriented agent suites (Dust). Scoring reflects developer experience, model and integration breadth, pricing, governance posture, and runtime reliability.
Questions About Dust
What is the best LLM app platform in 2026?
As of April 2026, the leading LLM app platforms are LangChain (most-used Python and JS framework), Vellum (production prompt and eval platform), Langflow (open-source visual builder), Dust (workspace assistants), and LlamaIndex (data-framework for RAG). Choice depends on visual versus code preference and whether teams need eval, RAG, or workspace assistants.
What is the best AI agent platform in 2026?
As of April 2026, the leading AI agent platforms are Relevance AI (low-code AI workforce), Lindy (personal AI assistants), Dust (workspace-grade assistants), Gumloop (visual AI workflows), and Relay.app (human-in-the-loop automations). Choice depends on whether teams want autonomous agents, personal assistants, or audit-trail workflows.
How do you build a Dust assistant in 2026?
As of April 2026, building a Dust assistant takes four steps: connect data sources (Notion, Slack, Drive, GitHub, Salesforce), define the assistant's instructions and model, attach the relevant data sources or knowledge bases, and publish to a workspace channel. Assistants run inside Dust's chat interface or via Slack.
What are the best Dust alternatives in 2026?
As of April 2026, the leading Dust alternatives are Relevance AI (low-code AI workforce), Lindy (personal AI assistants), Gumloop (visual AI workflows), Relay.app (human-in-the-loop automations), and Glean (enterprise search and assistants). Choice depends on whether teams want internal assistants, agent workforces, or workflow automation.