Numerous companies have already integrated generative AI tools, such as OpenAI’s ChatGPT, to enhance employee performance, demonstrating up to a 40% improvement compared to those not utilizing such tools. However, the ability to construct personalized AI workforces has largely been confined to businesses boasting sizable engineering teams. Addressing this gap, Australian startup Relevance AI seeks to empower companies of all sizes by offering a SaaS-based low-code platform for crafting custom AI agents tailored to diverse use cases, thereby maximizing productivity.
Daniel Vassilev, Co-founder of Relevance AI, stated, “Our mission is to enable teams only to be limited by their ideas, not their size — from the seasoned industry player to the ambitious newcomer.” The startup aims to simplify the process, allowing AI agents to autonomously execute intricate workflows and handle complex tasks with a level of accuracy and predictability that instills confidence in companies.
In a recent Series A funding round led by King River Capital, Relevance AI secured $10 million (AUD 15 million), bringing its total raised capital to $13.2 million. The funds will be utilized to further develop its low-code platform, enabling companies to build and deploy customized AI agents for automating repetitive tasks.
Relevance AI reported significant traction, with approximately 6,000 companies joining in the past three months alone. These companies have executed over 250,000 tasks, ranging from customer inquiries to outbound sales and market research. The startup is currently engaged with major players in the technology, retail, and fast-moving consumer goods sectors.
The startup’s strategic focus initially revolves around two verticals: sales and support teams. By concentrating on text-based tasks, Relevance AI aims to deliver a substantial return on investment (ROI). The company has introduced two products, AI Tools and AI agents, allowing users to seamlessly integrate AI into existing workflows, automating repetitive tasks and facilitating end-to-end workflows, such as research, marketing, and sales.
Relevance AI’s flagship AI agent, the Business Development Representative (BDR) agent, streamlines sales teams’ activities, minimizing time spent on administrative tasks like inbox management and follow-ups. The company envisions a future where every team will incorporate at least one AI agent by 2025, with fully-fledged AI teams supporting them by 2030.
Targeting companies and teams aiming to automate repetitive work with a reliable AI co-worker, Relevance AI differentiates itself by focusing on task-based outcomes rather than individual conversations. The platform’s applications extend across various domains, including product management, code reviews, and the startup is actively exploring multi-modal use cases involving image and audio.
Founded in 2020 by Daniel Vassilev, Jacky Koh, and Daniel Palmer, Relevance AI currently has 19 staff members, with plans to expand to around 30 by mid-2024. The startup is poised for further growth, intending to scale its team and establish a U.S. presence with an office in San Francisco next year.
