Dust

4.9 (27 reviews)

AI Assistant , Automation & Agents , Productivity

A developer-centric RAG platform for building internal AI assistants that query company data across Slack, Notion, and GitHub with granular control over retrieval logic.

Excellent for technical teams needing customizable AI agents integrated into Slack, weaker for non-technical users seeking a zero-config setup.

Ai Agents Knowledge Management Rag Workflow Automation Collaboration Enterprise Llm Productivity Tools

Analysis based on product data, pricing structure, traffic signals, and public user sentiment.

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Who Should Use Dust?

Typical users

Product operations, engineering leads, and knowledge managers at mid-sized tech companies (50-500 employees).

Maturity fit

scaling

Choose this if…

You need to combine data from multiple silos like Notion, Slack, and GitHub into a single assistant
Your priority is controlling the specific retrieval logic rather than using a black-box solution
You want the flexibility to switch between models like GPT-4o, Claude 3.5 Sonnet, and Mistral Large

Skip this if…

You are a solo user or a two-person team (minimum seat requirements apply)
You only need AI for a single tool like Notion, which already has native AI features
You lack the technical capacity to configure data connections and agent instructions

About Dust

Dust is an internal AI assistant builder designed to turn company knowledge into actionable data for LLMs. It focuses on the 'operator' persona, providing a workspace where teams can build, test, and deploy agents that live where they work, primarily Slack.

Official profiles

X (Twitter) LinkedIn YouTube GitHub

What it actually does

The platform connects to internal data sources, indexes them for semantic search, and allows users to build custom assistants. These assistants can be queried via a web interface or directly within Slack to answer questions, summarize threads, or extract information from documentation.

What makes it different

Unlike 'chat with your PDF' wrappers, Dust provides a low-code environment called 'Dust Apps' for chaining LLM calls and data retrieval steps. It treats internal AI as programmable infrastructure, allowing developers to inspect exactly which documents were used to generate an answer.

Multi-source data synchronization (Notion, Slack, GitHub, Drive) Custom agent builder with system prompt configuration Direct Slack integration for team-wide querying Support for multiple LLM providers (OpenAI, Anthropic, Mistral) Granular data source permissions and visibility controls Developer API for custom integrations Retrieval-Augmented Generation (RAG) with source citations

Ratings across the web

4.9 (27 reviews)

G2 26 reviews

4.9/5

Capterra 1 reviews

5.0/5

Ratings aggregated from independent review platforms.

Key Features

Slack Integration

Allows users to summon specific assistants in any channel using @mentions to summarize long threads or find docs.

Dust Apps

A low-code IDE for building complex workflows that involve multiple LLM steps and specific data queries.

Managed Data Sources

Automatically syncs and re-indexes changes in Notion or Google Drive to keep the AI's knowledge current.

Model Flexibility

Lets you choose the best model for the task, such as Claude 3.5 for writing or GPT-4o for logic.

Citations and Transparency

Every answer includes links to the specific Slack messages or Notion pages used as context.

Public/Private Assistants

Enables teams to build agents for specific departments (e.g., Sales vs. Engineering) with restricted data access.

Pricing

Free

1 managed data source
50 messages per month
Standard models only
Web interface access

Popular

Pro

€29 per user/month

Minimum 3 seats (€87/mo)
Unlimited data sources
Unlimited messages
Slack & Google Drive integrations
Advanced models (GPT-4, Claude 3)

Business

€500 + €20 platform fee + per user/month

Minimum 10 seats
SAML SSO & SCIM
Advanced data permissions
Dedicated support
Enterprise-grade security

Enterprise

Custom annual

Custom data retention policies
On-premise deployment options
Dedicated account management
Custom legal agreements

Pricing checked 6 months ago

Pricing guidance

Best plan for most users: The Pro plan is the sweet spot for most tech teams, providing unlimited messages and the full suite of integrations for a predictable per-user cost.

Free plan enough? No — the 50-message limit and single data source restriction make it purely a trial tier for testing the interface.

Upgrade when:

When you need to connect more than one data source (e.g., Notion AND Slack)
When you need SSO for company-wide deployment
When you hit the 50-message monthly cap on the free tier

Watch out for:

Minimum 3-seat requirement on Pro plan
Minimum 10-seat requirement on Business plan
Large platform fee (€500/mo) for Business tier regardless of usage

Premium pricing that targets established mid-market companies rather than price-sensitive solopreneurs.

Pros & Cons

Strengths

Superior Slack experience
The Slack integration is more than an afterthought; it supports threading, mentions, and specific agent summoning, making it the primary way teams actually use the tool.
Model agnosticism
Users aren't locked into one provider. Being able to toggle between Anthropic and OpenAI models ensures you can use the most efficient model for a specific internal task.
High transparency
The platform shows exactly which chunks of data were retrieved. This makes debugging 'hallucinations' much easier for admins compared to simpler competitors.

Weaknesses

High entry cost for small teams
The Pro plan requires a minimum of 3 seats, and the Business plan has a significant flat platform fee, making it expensive for startups under 10 people.

Affects: Early-stage startups and small agencies
Technical learning curve
While basic agents are easy to set up, the 'Dust Apps' feature and advanced RAG configuration require a developer-level understanding of LLM parameters.

Affects: Non-technical HR or Admin teams
Limited 'Agentic' actions
It is excellent at retrieval and summarization but lacks deep 'action' capabilities like booking meetings or updating CRM records directly.

Affects: Teams looking for autonomous agents rather than knowledge assistants

Real User Sentiment

Users generally view Dust as a professional-grade tool that solves the 'internal knowledge' problem better than native AI features in Slack or Notion.

Users tend to like

The speed and accuracy of the Slack bot
The ability to see the exact source of an answer
The flexibility to use Claude 3.5 Sonnet for better reasoning
Clean, developer-friendly UI

Users commonly complain about

The jump to the Business plan is too expensive for 15-20 person teams
Initial indexing of large Google Drive folders can be slow
Occasional difficulty in fine-tuning agent behavior without technical help

Recurring tradeoffs

You trade ease of setup for much higher control over how the AI processes your data.

Happiest users

Engineering and Ops teams who live in Slack and have well-documented processes in Notion or GitHub.

Often frustrated

Small teams on a budget who find the minimum seat costs and platform fees prohibitive.

Use Cases

Customer Support

Building an agent that queries Zendesk and internal docs to draft responses for agents.

Engineering Onboarding

Creating a bot that answers 'How do I set up the dev environment?' by searching GitHub and Notion.

Sales Enablement

An assistant that summarizes recent Slack conversations about a specific prospect or deal.

Product Research

Querying a repository of user interview transcripts stored in Google Drive to find recurring pain points.

Internal Wiki Search

Replacing the standard (and often poor) search functionality of Notion and Confluence with semantic AI search.

Frequently Asked Questions

Is there a free version of Dust?

Yes, Dust offers a free tier, but it is very limited. You can only connect one data source and send 50 messages per month. It is designed for individual testing rather than team use. To get the Slack integration and unlimited messages, you must move to the Pro plan, which starts at €87/month for a minimum of 3 users.

How does Dust compare to Glean?

Glean is an enterprise search tool that added AI, while Dust is an AI agent builder that uses search. Glean is typically much more expensive and aimed at large enterprises (1,000+ employees) with complex security needs. Dust is more flexible for developers and mid-sized teams who want to build custom logic and specific assistants for different departments.

Is my data used to train the LLMs?

No. Dust uses the API versions of models from OpenAI, Anthropic, and Mistral. These providers have strict terms that prevent data sent via API from being used to train their global models. Dust also provides SOC2 compliance and data encryption to ensure internal knowledge remains private.

Can I use Dust if I don't know how to code?

You can use the basic features, like connecting Notion and creating a standard assistant, without coding. However, to get the most out of the platform—specifically the 'Dust Apps' feature for complex workflows—you will need a basic understanding of how LLMs work and potentially some light scripting knowledge.

Which data sources does Dust support?

Dust currently supports native integrations with Slack, Notion, Google Drive, GitHub, Intercom, Confluence, and Zendesk. It also allows for custom data uploads via API or CSV for more specialized use cases.

Can I use Claude 3.5 Sonnet with Dust?

Yes, Dust allows you to select the specific model for each assistant you build. You can choose between various versions of GPT-4, Claude 3/3.5, and Mistral models depending on your needs for speed, cost, or reasoning capability.

Why trust this page?

This evaluation combines product positioning, pricing analysis, traffic and market signals, and public user sentiment into a single decision-support page. Content is generated editorially — not copied from the vendor's website.

Funding & Company

Founded

2022

Stage

Series a

Total Raised

$21.5M

Latest Round

Series A (Jun 2024)

Notable Investors

Sequoia Capital XYZ Connect Ventures Seedcamp

Dust has raised a total of $21.5 million over two rounds, led by top-tier investor Sequoia Capital. This funding provides a strong financial foundation for the company to continue developing its AI assistant platform and expand its enterprise customer base, suggesting good product stability and longevity.

Full funding report high confidence

Market Signals & Traffic

Estimated visits, global rank, geography, traffic sources, monthly visit trends, and organic search keywords (Similarweb)—on a dedicated page built for depth and search.

Estimated visits: 0
Global rank: —
Snapshot: May 2026
Traffic trend: Surging