Relevance AI

Relevance AI frames automation around an "AI workforce": instead of a single agent, you assemble a team of agents, each with a defined role (e.g., researcher, outreach writer, support responder), tools they're allowed to use, and goals they work toward — with a manager-style orchestration layer coordinating handoffs between them. A library of pre-built agent templates covers common business functions like outbound sales prospecting, customer support triage, and market research, which can be customized to your stack and connected to CRMs and other business tools. The free tier supports a limited number of agent runs for testing; paid plans starting around $19/mo raise usage limits and unlock more agents, seats, and integrations. Getting real value requires some upfront investment in defining roles and tools clearly — vaguely-configured multi-agent teams tend to produce inconsistent results, and overall output quality is still bounded by the underlying LLM each agent uses.