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Relevance AI raises $24 million in Series B funding to expand its platform for building autonomous AI agents. The company introduces tools like a no-code multi-agent builder and a text-to-agent generator, aiming to replace traditional automation with more adaptable systems. With growing enterprise adoption and a new San Francisco office, Relevance AI positions itself to lead the shift toward AI-driven operations.
From Startup Dreams to a $24M Milestone
Relevance AI, founded by Daniel Vassilev, Jacky Koh, and Daniel Palmer, began with a clear observation: traditional automation tools had reached a plateau. These systems were sufficient for rule-based tasks but lacked the adaptability for more complex, context-dependent decisions.
Their answer was an agent operating system designed to enable subject-matter experts to build and deploy tailored AI agents without requiring engineering backgrounds. These agents are capable of performing specialized, high-quality work aligned to the unique needs of each organization.
The platform has attracted usage from both startups and large enterprises, contributing to its fast-growing adoption. In January 2025 alone, 40,000 agents were created on Relevance AI’s platform, signaling strong product-market alignment and prompting investors to take early action.
Why Investors Bet Big on Relevance AI
Relevance AI’s $24 million Series B round was led by Bessemer Venture Partners. Existing investors—including Insight Partners, King River Capital, and Peak XV—also participated, continuing their backing from previous rounds.
The speed at which the funding round materialized was attributed to unexpected traction and user growth. Investor confidence reflected not only the current usage metrics but also belief in Relevance AI’s strategic direction toward an autonomous AI workforce model.
This funding is earmarked to scale both the product and go-to-market efforts, supporting ongoing development and global expansion. The company has also opened a new office in San Francisco to be closer to customers and the broader AI ecosystem.
Inside the Tools That Power the AI Workforce
Relevance AI’s two flagship features are designed to democratize the creation and deployment of AI agents:
- Workforce: A visual builder that allows non-technical professionals to design multi-agent workflows on a no-code canvas. These agents can interact with each other and collaborate with human team members.
- Invent: A generator that creates customized agents based on natural language input. Users can describe a task or goal, and the system generates an agent in minutes without requiring manual coding.
These tools are positioned to replace or augment traditional automation, which the company estimates represents just 5% of the potential that AI agents can unlock. The remaining 95% involves the non-deterministic functions where human-level judgment is needed.
Why Co-Pilots Aren’t Enough Anymore
Relevance AI draws a distinction between co-pilot models and autonomous agents. While many companies have focused on co-pilots that assist users during tasks, Relevance AI believes the greater value lies in agents that can execute end-to-end processes independently.
The company has observed a pattern across its customers: initial implementations often start with co-pilot use cases but quickly transition to full automation using agents that act more like delegated teammates. Relevance AI argues that users will increasingly favor autopilot modes once they experience their efficiency and autonomy.
This approach challenges the prevailing industry narrative and suggests a different trajectory for AI workforce development.
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Big Names, Bigger Use Cases
Relevance AI serves a broad range of clients, including startups and Fortune 500 firms. Among the more prominent names are Activision, Qualified, and SafetyCulture.
SafetyCulture’s CIO, Mike Welch, reported immediate and dramatic return on investment following their first agent deployment. The company is now scaling the technology across the organization.
These use cases demonstrate the flexibility of Relevance AI’s platform and its ability to generate value across different industries and stages of digital maturity.
Setting Up Shop Where Innovation Happens
To support its next phase, Relevance AI has opened a new office in San Francisco. The location brings the company closer to both customers and partners in the global AI hub.
Daniel Vassilev has personally relocated to lead the initiative and embed more deeply within the U.S. ecosystem. The team now includes more than 80 employees spanning San Francisco and Sydney.
New hires across the Customer Success division are focused on ensuring organizations derive measurable value from their agent deployments. Whether a startup or an enterprise, Relevance AI aims to support a seamless scale-up of AI integration.
Why the Door to First-Mover Advantage Is Closing Fast
Relevance AI predicts that by the end of 2025, having access to an AI agent-building platform will be a standard requirement for competitive organizations. The question, according to the company, is not whether AI agents will be adopted—but when.
The concept of AI agents as first-class team members reflects a shift in how organizations structure operations. Rather than merely automating repetitive tasks, businesses are starting to delegate ownership of entire workflows to AI systems.
Relevance AI believes those who move early will gain a significant edge in execution and scale.
AI Workforces Are Here—Are You Ready to Build One?
Relevance AI is continuing its expansion, product innovation, and customer engagement with clear momentum. The company’s vision centers on a world where success depends less on growing headcount and more on how effectively work can be delegated to intelligent systems.
The recent funding and platform evolution indicate a move beyond experimentation toward operational integration. As enterprises shift their approach, Relevance AI aims to serve as the infrastructure for building and managing AI workforces at scale.
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