Relevance AI
No-code platform for building AI workforces — teams of agents that do the work.
About
Relevance AI, based in Sydney and San Francisco and founded by Daniel Vassilev, Jacky Koh, and Daniel Palmer, offers a no-code 'AI workforce' platform where subject-matter experts build teams of specialized agents without engineering help. Its Workforce feature orchestrates multi-agent collaboration across departments, while Invent generates agents from simple text prompts. The platform is model-agnostic and reported 40,000 agents created in January 2025 alone, with customers including Qualified, Activision, and SafetyCulture.
The company raised a $10 million Series A led by King River Capital and a $24 million Series B in May 2025 led by Bessemer Venture Partners (with Insight Partners and Peak XV), bringing the disclosed total to about $37 million; some later profiles cite higher totals (~$64.6M), which is not reconciled across sources. It is SOC 2 Type 2 certified. Caveat: independent reviews note it targets technical teams more than pure business users — non-trivial agents still need careful configuration.
What it can do
- No-code AI agent builder
- Multi-agent Workforce collaboration
- Invent: text-prompt-to-agent generation
- Pre-built agents for sales, support, and research
- Model-agnostic across LLM providers
Setup
Sign up at relevanceai.com; build agents with the no-code canvas or Invent prompts.
Prerequisites
A Relevance AI account; connections to your business tools (CRM, email, etc.).
Use cases
Works with
Trust score — 7/10
Scored 7/10 (metrics tier, metrics-v1). Evidence: Verified via vendor site/docs/GitHub and reputable coverage, wave 62; Trending score 70/100 from researcher assessment.
Sources
Every fact above was checked against these sources. Where a claim comes from the provider and couldn't be independently verified, the text says so.