Dust Secures $16 Million to Enhance Enterprise AI Assistants with Internal Data Integration

French startup Dust has successfully raised $16 million in a Series A funding round led by Sequoia Capital. Dust specializes in creating custom AI assistants for enterprises, enabling employees to work more efficiently by connecting these assistants to internal company data and documents.

Unlike consumer-facing AI tools such as ChatGPT, Dust’s AI assistants can access and interact with company-specific resources like Notion pages, Google Drive documents, Intercom conversations, and Slack channels. This feature allows each assistant to perform specialized tasks tailored to the needs of different teams within an organization.

Dust advocates for the use of multiple AI assistants within a company, each designed to address specific tasks. For instance, support teams can use an assistant familiar with the company’s knowledge base and past interactions, while HR teams might use an assistant to manage questions about corporate policies or draft job descriptions.

For technical teams, assistants can understand database schemas and help generate SQL queries. Sales teams can use AI to draft emails based on CRM data and contextual information about potential clients. Additionally, Dust offers an API for creating custom connectors and integrating assistants with other tools.

Dust’s platform allows employees to interact with AI assistants via a web interface or directly within Slack, making it a seamless part of daily communication. The startup has already achieved $1 million in annual recurring revenue, with notable clients like Watershed, Alan, Qonto, Pennylane, and PayFit extensively using its services.

Qonto reports that 75% of its 1,600-strong team use Dust assistants monthly, while 80% of Alan’s staff engage with the AI assistants weekly. Pennylane has developed 86 custom assistants with Dust.

In addition to Sequoia Capital, Dust’s existing investors, including XYZ, GG1, Connect Ventures, Seedcamp, and Motier Ventures, also participated in the funding round. Dust’s customer-centric approach includes allowing users to choose from various large language models, such as OpenAI’s GPT, Anthropic’s Claude, Mistral, and Google’s Gemini models.

As competition in the enterprise AI assistant space heats up, with players like Brevian, Tektonic AI, Ema, Kore.ai, and even Atlassian’s Rovo, Dust aims to stand out with its unique approach and easy onboarding process.