Dust, a two-year-old artificial intelligence platform that aids businesses in creating AI agents capable of carrying out entire business workflows, has grown to$ 6 million in annual revenue, a six-fold increase from the previous year’s$ 1 million. The company’s explosive growth indicates a shift in the adoption of enterprise AI, moving away from simple chatbots to complex systems capable of carrying out specific actions across business applications.
The San Francisco-based company announced on Thursday that it has been chosen as part of Anthropic’s” Powered by Claude” habitat, highlighting a brand-new type of AI companies that are building specific business tools on top of border language models more than creating their own AI systems from scratch.
In an appointment with VentureBeat, Gabriel Hubert, CEO and co-founder of Dust, said that “users want more than just verbal interface.” They prefer to make the actual document quickly rather than creating a draft. They require automatic updating of CRM information more than meet summary documents.
The chatbot-style AI tools that predominated earlier sector implementation are now a part of Dust’s system. Dust’s AI agents can maintain enterprise-grade security protocols while maintaining GitHub issues, routine calendar meetings, release customer records, and even conduct code reviews immediately based on internal coding standards.
How AI officials automate GitHub tickets and Salesforce changes from sales calls.
A business-to-business revenue company using various Dust agents to practice sales call transcripts becomes clear about the company’s strategy in the practical example Hubert gave. One broker compiles a list of sales arguments that made sales sense to prospects and updates the battle cards in Salesforce quickly. Additionally, another broker locates buyer have requests, assigns them to the item strategy, and, in some cases, generates GitHub tickets for minor features that are deemed ready for growth.
Each contact text will be analyzed by several agents, Hubert continued. A sales war cards optimizer agent will examine the arguments the seller made, which ones were persuasive and seemed to be in the prospect’s favor, and that will be used to inform a Salesforce process.
The Model Context Protocol (MCP), a new normal created by Anthropic that enables AI techniques to properly interact with additional information resources and applications, makes this level of automation possible. Anthropic’s Head of EMEA, Guillaume Princen, described MCP as “like a Bluetooth connection between AI models and apps,” enabling brokers to get company data while maintaining protection boundaries.
Why are Claude and MCP helming the upcoming generation of business AI automation?
Dust’s victory reflects broader shifts in how businesses are implementing AI. Companies like Dust are combining foundation models that are extremely advanced with specialized automation software and using them instead of creating specialized models.
We simply want to provide our customers with access to the best designs, according to Hubert. And I believe that Anthropic is still in the result, especially in terms of coding-related models. The business offers a monthly fee of$ 40 to$ 50 to its customers, and it serves a wide range of workspaces, from small startups to large corporations with tens of thousands of employees.
Anthropic reports a 300 % increase in Claude Code usage over the past four weeks following the release of its most recent Claude 4 models, which shows a particularly strong adoption for coding tasks. Princen remarked that” Opus 4 is the most potent programming system in the world.” ” We were already in the lead in the programming culture. We’re strengthening that.
Business safety becomes more complicated when AI agents actually take action.
The transition to AI agents that can perform actual actions across company systems introduces new safety complexity that weren’t present with standard robot implementations. Dust addresses this by utilizing what Hubert refers to as a “native permissioning layer,” which separates agent usage rights from data access rights.
The company states in technical documentation that “permission creation, as well as data &, tool management is a part of the onboarding experience to mitigate sensitive data exposure when AI agents operate across multiple business systems. When agents have the ability to create GitHub issues, update CRM records, or change documents across an organization’s technology stack, this becomes crucial.
The company uses Anthropic’s Zero Data Retention policies to ensure that the model provider doesn’t store sensitive business information that is being processed by AI agents. Enterprises considering scaling up AI adoption are impacted by this.
The rise of AI-native startups that instead focus on developing foundation models
Dust’s expansion is a result of what Anthropic refers to as an emerging ecosystem of” AI native startups,” which are companies that fundamentally couldn’t exist without advanced AI capabilities. These businesses are constructing their businesses by building sophisticated applications on top of already existing foundation models, not by developing their own AI models.
According to Princen,” These companies have a very, very strong sense of what their end customers need and want for that specific use case.” We’re giving them the tools to kind of design and modify their goods to those specific needs and use cases they’re looking for.
This approach alters the structure of the AI industry significantly. Specialized platforms like Dust can provide the orchestration layer that makes powerful AI models useful for specific business applications rather than every company needing to develop its own AI capabilities.
What Dust’s$ 6M revenue growth indicates about the potential for enterprise software
The success of businesses like Dust points out that the market for enterprise AI is moving beyond the testing phase to practical application. These systems are designed to eliminate routine tasks and context-switching between applications, allowing employees to concentrate on higher-value tasks rather than replacing human workers in large numbers.
We are laying the groundwork for a future-proof agent operating system by providing universal AI primitives that improve all company workflows and provide a sound permissioning system, Hubert said.
Organizations are among the clients of the business because they are convinced that AI will fundamentally alter how business operations operate. The customer base is pretty skewed toward the future and convinced that this technology will change a lot of things, Hubert observed.
The distinction between AI tools that simply provide information and those that take action is likely to become a key differentiation in the enterprise market as AI models become more capable and protocols like MCP mature. Due to the rapid growth in revenues, it seems that businesses are willing to pay premium prices for AI systems that can perform real work rather than just to assist with it.
The wider structure of enterprise software is affected, as well as individual businesses. It could change how organizations think about software procurement and workflow design, potentially lowering the complexity that has long plagued enterprise technology stacks, if AI agents can seamlessly integrate and automate workflows across disparate business applications.
The way that Hubert naturally describes AI agents as digital employees who show up to work every day is perhaps the most telling sign of this transformation. Companies like Dust are demonstrating that the future might not require connecting everything—just teaching AI to navigate the chaos we’ve already created in a business world that has spent decades connecting systems with APIs and integration platforms.
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