RelevanceAI and Stack AI get millions in funding to bring AI agents into the workforce

Agentic artificial intelligence is still in vogue for Silicon Valley’s venture capitalists, with Relevance AI and Stack AI joining the latest hot startups to attract millions of dollars in funding.

The two companies are among a host of startups looking to help enterprises harness the power of advanced AI models, without being held back by traditional barriers to adoption, such as the need for complex coding and expert data scientists.

Australia-based RelevanceAI is perhaps the more mature of the two companies at present, having just closed on its second major funding round – a $24 million Series B raise backed by prestigious VCs including Bessemer Venture Partners, which led the round, and earlier investors Insight Partners, King River Capital and Peak XV.

The startup has created a low-code platform that enables companies of all sizes to create AI agent workforces. Its AI agents are all focused on a specific task, and it provides tools for customers to customize them to their needs. It’s targeting companies and teams that want to automate repetitive work, freeing their employees to focus on more creative tasks.

It offers a number of prebuilt AI agents that can work autonomously, after receiving some initial prodding. For instance, it recently debuted a social posting agent that can repurpose blogs and social media posts for different platforms while ensuring the brand’s voice remains consistent. For each blog post someone creates, it will create a customized version for platforms such as LinkedIn and X, tailoring it to the unique engagement patterns of those services.

It also offers an automated meeting notetaker agent that’s able to capture and transcribe everything said during a meeting, and transform those conversations into actionable items once the meeting has concluded.

RelevanceAI co-founder and Chief Executive Daniel Vassilev said customers used its no-code platform to create more than 40,000 agents in January alone. Its clients range from major Fortune 500 enterprises such as Activision Publishing Inc., to startups such as Qualified.com Inc. and SafetyCulture PTY Ltd.

Vassilev said the new funding will help to accelerate the development of two key features in his company’s platform, including its visual multi-agent system builder, a tool for building sophisticated AI agent teams on a no-code canvas. “Think of your marketing specialist or sales leader designing workflows where specialized AI agents collaborate with each other and with human teammates — no engineering resources required,” he said.

The company is also planning to launch the world’s first “text-to-agent” generator, where companies will be able to describe what they need from an AI agent in natural language and sit back and watch as the platform builds it. “It’s a game-changer for organizations looking to rapidly deploy AI capabilities across various functions,” Vassilev said.

AI agents for every task

As promising as RelevanceAI’s platform sounds, it’s going to face a lot of competition from rival AI startups, and Stack AI could well be among them.

The company has just raised $16 million in a Series A round that saw participation from new investors Lobby VC and LifeX Ventures, plus Vercel AI CEO Guillermo Rauch and Weviate Inc. CEO Bob van Luijt, who participated as angel investors. Existing backers Gradient, Y Combinator and Epakon Capital also contributed to the round.

Stack AI has built a platform that allows enterprises to connect various data sources with a variety of large language models, including OpenAI’s GPT models, and create customized AI agents that can perform some very specific work-related tasks.

If it sounds a lot like RelevanceAI, that’s probably because it is very similar. At its core, Stack AI is all about work automation, with a low-code, drag-and-drop user interface for constructing AI-powered assistants, chatbots and content creation systems.

Stack AI says its AI agents can address many kinds of “operational challenges.” For instance, they can automate supply chain tasks such as generating and responding to proposals. They can also perform data analytics tasks, translating natural language commands into Structured Query Language queries to enable anyone to dig up useful insights.

Other tasks include assisting doctors by retrieving patient histories, treatment plans and other information from electronic health records, customer assistants for call centers, and financial AI agents that can automate financial reporting and monitor transactions for fraud.

“We’ve developed a platform that enables enterprises to create custom AI agents… that can interact with various data sources and systems and be deployed for diverse tasks,” said Stack AI co-founder Bernard Aceituno. “Our mission is clear – an AI agent for every job.”

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