📘 Overview of Dust
👉 Summary
As companies look to integrate AI without sacrificing security or relevance, Dust positions itself as a serious answer. Founded by former engineers from Stripe and Alan, the platform was designed from the ground up for professional teams that want to go beyond generic chatbots. Dust is not just a simple AI assistant: it is a complete environment for creating, deploying, and managing agents capable of understanding your organization's specific context. With over $6 million in annual recurring revenue and rapid growth, it attracts both agile startups and large enterprises seeking a secure alternative to ChatGPT Enterprise.
💡 What is Dust?
Dust is a collaborative AI workspace. The platform enables teams to create custom agents that access the company's internal knowledge — documents, databases, business tools — and execute tasks autonomously. Each agent can be configured with a specific AI model, dedicated data sources, and precise permissions. Dust does not impose a single model: the platform is compatible with OpenAI GPT, Anthropic Claude, Google Gemini, Mistral, and others. Designed for support, HR, sales, and technical teams, Dust turns an organization's scattered knowledge into an asset actionable by intelligent agents.
🧩 Key features
Dust is built around several functional pillars. Agent creation happens via an intuitive interface, with over 50 ready-to-use templates to get started quickly. Each agent can be published to the whole team or kept private. Data source connections are a key strength: Slack, Notion, Google Drive, Confluence, GitHub, Salesforce, HubSpot, Jira, Zendesk, SharePoint, OneDrive, and Microsoft Teams are supported natively. The MCP protocol extends integration possibilities to third-party tools like Asana, Miro, and Fathom. Agents can be chained together: a research agent gathers information that a writing agent transforms into a report, both running in parallel. Persistent memory lets each agent remember user preferences and context across conversations. Automated triggers allow scheduling in natural language or activation via webhooks. Observability tools round out the picture: success rates, token usage, and performance metrics per agent.
🚀 Use cases
Dust fits naturally into many professional contexts. Support teams build agents that automatically answer tickets based on internal documentation. Sales teams deploy agents connected to Salesforce to qualify leads or prepare client meetings. HR teams build onboarding assistants that answer new employee questions by drawing from internal policies. Technical teams automate report generation, code review summaries, and runbook synthesis. Content managers use research agents to compile industry intelligence. In all cases, Dust's value lies in connecting agents to an organization's real data sources.
🤝 Benefits
Dust's main advantage is making AI genuinely operational in a real enterprise context. Rather than forcing teams to adapt workflows to a generic AI tool, Dust adapts to existing tools and processes. Model agnosticism protects against vendor lock-in: if a better model emerges, agents simply need to be reconfigured. Security is built in from day one with SOC 2 Type II certification, GDPR and HIPAA compliance, and a clear policy: your data is never used to train external models. Centralized access management via Okta or Entra ID greatly simplifies administration in large organizations.
💰 Pricing
Dust offers two plans. The Pro plan is billed at €29 per user per month and includes all main features: agent creation, integrations, persistent memory, and triggers. A 15-day free trial with no credit card required is available. The Enterprise plan is custom-priced for organizations of 100 members or more and adds multiple workspace management, SSO/SCIM, dedicated support, and service level guarantees. A separate API pricing tier is available for programmatic usage.
📌 Conclusion
Dust represents a coherent and ambitious vision of what AI can bring to professional teams. By combining a flexible architecture, deep native integrations, and enterprise-grade security, the platform establishes itself as a serious option for organizations that want to industrialize AI without compromise. The 15-day free trial allows for a concrete evaluation before committing.
