Relevance AI

The platform enables non-technical teams to construct sophisticated multi-agent systems where agents hand off work to each other, verify each other's outputs, and collaborate to complete complex multi-step tasks without any developer involvement.

It is backed by serious enterprise adoption and positions itself as infrastructure for the AI-native business.

Agent building in Relevance AI centers on a visual tool-and-agent construction interface. Agents are configured with access to specific toolsweb search, document retrieval, CRM queries, email sending, data lookupsand given instructions defining their role and decision-making logic.

Multiple agents can be assembled into teams where one agent researches, another verifies, and a third synthesizes results into a final output. This multi-agent architecture enables the platform to tackle workflows that would overwhelm a single agent, distributing cognitive load across specialized agents.

Pre-built agent templates accelerate deployment for common sales and GTM use cases.

The BDR Agent automates prospect outreach and lead qualification, the Account Research Agent gathers comprehensive company intelligence before sales calls, the SEO Agent handles keyword research and content optimization briefing, and the Customer Support Agent answers FAQs and routes tickets to human agents when escalation is required.

These templates can be deployed immediately or used as starting points for custom configurations.