Australian AI Startup Secures $24M for AI Agents

In an era where artificial intelligence is not just a tool but a transformative force reshaping the future of work, the recent $24 million Series B funding for Sydney-based Relevance AI is a watershed moment. The round, led by Bessemer Venture Partners and supported by Insight Partners, King River Capital, and Peak XV, brings the startup’s total funding to $37 million. Relevance AI is at the forefront of a new wave of enterprise technology: the creation and deployment of AI agents designed to automate and optimize workflows across industries, from marketing to customer service and beyond. But what makes this company’s approach so compelling—and why is the market so eager to invest in agentic AI right now? ## The Rise of Agentic AI Agentic artificial intelligence—AI systems that can autonomously perform tasks, often in teams or “workforces”—has become the latest obsession for Silicon Valley’s venture capitalists and enterprise customers alike. Unlike traditional AI models that require extensive coding and data science expertise, agentic AI platforms, such as those developed by Relevance AI, empower non-technical professionals to build and customize their own AI agents. This shift is democratizing access to advanced automation, enabling companies of all sizes to reap the benefits of AI without the traditional barriers[3][4]. Relevance AI’s platform stands out for its low-code, no-code approach, allowing domain experts to create teams of AI agents tailored to their specific needs. The company recently launched two new features, ‘Workforce’ and ‘Invent,’ which further streamline the process. ‘Workforce’ enables users to design multi-agent systems using a visual canvas, while ‘Invent’ allows for the generation of AI agents directly from text prompts[4]. ## Breaking Down the Numbers: Funding, Growth, and Adoption The numbers behind Relevance AI’s latest funding round tell a story of rapid growth and broad market appeal. With $24 million (approximately A$37 million) secured in Series B, the company now employs over 80 people across San Francisco and Sydney. As of January 2025, Relevance AI reported creating 40,000 agents on its platform in a single month, a staggering figure that underscores both the scalability of its technology and the appetite for AI-driven automation among businesses[4]. Key customers include Qualified, Activision, and SafetyCulture, with the latter’s managing director, Mike Welch, noting, “The ROI from our first agent deployment was immediate and dramatic. Now we're looking at how to scale this across our entire organisation”[4]. ## Real-World Applications: From Social Media to Enterprise Workflows Relevance AI’s platform is designed to automate repetitive, time-consuming tasks, freeing human employees to focus on more creative and strategic work. One of its flagship use cases is a social posting agent, which automatically repurposes blogs and social media posts for different platforms—ensuring brand consistency and optimizing content for each channel’s unique engagement patterns. For example, a single blog post can be transformed into customized versions for LinkedIn, X (formerly Twitter), and other social networks, all while maintaining the brand’s voice and style[3]. But the applications don’t stop at marketing. Relevance AI’s agents are being deployed across customer support, data analysis, and internal workflows. The company’s vision is to become the “definitive home of the AI workforce,” where organizations are limited only by their ideas, not their headcount[4]. ## The Competitive Landscape: How Relevance AI Stacks Up To understand Relevance AI’s position in the market, it’s helpful to compare it to other players in the agentic AI space. Stack AI, for example, is another startup attracting significant funding and attention for its enterprise-focused AI agent platform. However, Relevance AI is considered more mature, with a proven track record and a rapidly expanding customer base[3]. | Feature | Relevance AI | Stack AI | |------------------------|-------------------------|-------------------------| | Platform Type | Low-code / No-code | Low-code | | Key Features | Workforce, Invent, visual canvas | Customizable agents, integrations | | Funding (latest round) | $24M (Series B) | Undisclosed (millions) | | Customer Base | Qualified, Activision, SafetyCulture | Enterprise-focused | | Geographic Reach | San Francisco, Sydney | US-based | ## The Human Element: AI Experts and the Future of Work The rise of agentic AI raises important questions about the future of work and the role of AI experts. According to industry leaders, AI experts can be broadly categorized as either researchers or developers. Researchers focus on innovation and solving complex problems, often coming from diverse backgrounds in data science, statistics, or even economics. Developers, on the other hand, are tasked with bringing these innovations to life through code and deployment[5]. As someone who’s followed AI for years, I’ve noticed that the demand for AI expertise far outstrips supply. Companies are increasingly creative in their recruitment strategies, seeking out candidates with advanced degrees, industry experience, and even military backgrounds. The challenge now is not just building powerful AI, but ensuring that organizations have the talent and vision to harness it effectively[5]. ## Historical Context and the Evolution of AI Agents The concept of AI agents is not new, but the technology has evolved dramatically in recent years. Early AI systems were rigid, rule-based, and required extensive manual programming. Today’s agentic AI platforms, by contrast, are flexible, scalable, and accessible to non-technical users. This shift has been driven by advances in large language models (LLMs), generative AI, and cloud computing, all of which have lowered the barriers to entry for AI adoption[3][4]. Relevance AI’s success is a testament to this broader trend. By focusing on usability and customization, the company has positioned itself as a leader in the next wave of AI-driven automation. ## Future Implications: What’s Next for Relevance AI and the Industry? Looking ahead, the implications of Relevance AI’s growth are profound. As more organizations adopt agentic AI, we can expect to see significant changes in workforce dynamics, productivity, and even the nature of work itself. The ability to automate routine tasks at scale will allow businesses to reallocate resources, innovate faster, and respond more nimbly to market changes. At the same time, the rise of AI agents raises important questions about ethics, accountability, and the future of human employment. As these systems become more autonomous, organizations will need to establish clear guidelines for their use and ensure that they complement, rather than replace, human workers. ## Voices from the Industry Daniel Vassilev, co-founder and co-CEO of Relevance AI, sums up the company’s vision: “This funding fuels our vision of making Relevance AI the definitive home of the AI workforce. We're creating a world where organisations are limited only by their ideas, not their headcount”[4]. Mike Welch, Managing Director of SafetyCulture, adds: “The ROI from our first agent deployment was immediate and dramatic. Now we're looking at how to scale this across our entire organisation”[4]. ## Conclusion: A New Era for AI and Work Relevance AI’s latest funding round is more than just a financial milestone—it’s a signal of the growing demand for intelligent automation and the transformative potential of agentic AI. As the company continues to expand its platform and customer base, it’s clear that the future of work will be shaped by teams of humans and AI agents working side by side. Let’s face it: the days of manual, repetitive tasks are numbered. In their place, we’re entering a new era where creativity, strategy, and innovation take center stage, powered by the collaborative potential of AI agents. For Relevance AI and its customers, the journey is just beginning—and the possibilities are limitless[4][3]. **