Relevance AI is a no-code platform for building AI agents, founded in 2020 by Daniel Vassilev, Jacky Koh and Daniel Palmer. The company is headquartered in Sydney, Australia with a second office in San Francisco, and raised a US$24M Series B in May 2025 led by Bessemer Venture Partners, bringing total disclosed funding to roughly US$37M.
The product's distinguishing idea is the "AI workforce": rather than configuring one chatbot, you assemble a team of specialized agents on a visual canvas and let them delegate work between each other. Agents are built from plain-language instructions plus tools — reusable actions that call native integrations, custom APIs or webhooks. The platform is model-agnostic, routing to OpenAI, Anthropic or Google models, and ships a prebuilt sales agent called Bosh that handles prospect research, outreach and CRM updates.
Pricing is where buyers should pay attention. Relevance AI bills on two meters: Actions (counted each time an agent runs a tool) and Vendor Credits (the underlying LLM and tool compute, passed through at wholesale). The transparency is welcome, but the forecasting burden is real, and overage rates of $80 per 1,000 Actions have generated the platform's most persistent complaints. Reported customers include Qualified, Activision and SafetyCulture; the company said 40,000 agents were created on the platform in January 2025 alone.
Key Benefits
- Multi-agent by design: The Workforce canvas treats agent-to-agent delegation as a first-class primitive, not an afterthought bolted onto a single-agent product.
- Broad connectivity: 2,000+ integrations mean most workflows can be wired to existing systems of record without custom engineering.
- No model lock-in: Switching between OpenAI, Anthropic and Google models is a configuration choice, which protects against single-vendor pricing changes.
- Low-cost entry: A functional free tier and a $19/mo paid plan let teams validate a use case before committing budget.
Use Cases
- Outbound sales development — Bosh and custom BDR agents research prospects, personalize outreach, handle replies and objections, and write results back to HubSpot or Salesforce.
- Lead enrichment and routing — Agents pull data from multiple sources, score inbound leads and route them to the right rep automatically.
- Internal operations automation — Multi-step workflows spanning Slack, Google Sheets and internal APIs, handling approvals, reporting and data hygiene.
- Market and competitor research — Research agents gather and synthesize information on a schedule, delivering structured summaries into existing team channels.
