Platform to build, run, and manage AI agents at scale — includes runtime, models, integrations, knowledge, and enterprise controls to put agents into production and keep them th...
Browse 1,000+ free AI agents for sales, marketing, support & operations; clone and deploy in minutes — no coding required.
What customers say
“It just felt like we had control in that platform to do stuff and set some guardrails and it was, you know, enterprise ready. And it just wasn’t another tool. It was something that was going to help us build like a workforce,”
CustomerRelevance AI customer
“We were approving everything, like every email that was going out to all the leads at first, we would feed Toni five leads a day for the first week, then the following week it was 10 leads and there was 15 leads. We were just to get comfortable with what Toni was saying,”
CustomerRelevance AI customer
“Instead of a conversation being, hi, could you provide me your invoice? We’ll run a review. It was, hi, we got your invoice. You spoke to my colleague Toni. The result is X savings. And it made for a much more fluid process and customer journey.”
CustomerRelevance AI customer
Relevance AI Platform
Send Payments partnered with Relevance AI to build agents for customer service and compliance workflows. The vendor reports 40 hours saved weekly, round-the-clock global operations coverage and thousands of automated…
Zembl used Relevance AI to build Toni and supporting agents for lead research, bill collection and Salesforce updates. The vendor-published story reports a 30% increase in customer conversion without expanding the…
SafetyCulture deployed a customized Relevance AI agent to answer customer questions and book meetings. Relevance AI reports threefold meetings booked, an 83% reduction in cost per meeting and a 200% increase in qualified…
Relevance AI Launches Evals for AI Agent Testing and Quality Monitoring
Relevance AI has introduced 'Evals,' an automated testing and evaluation feature for AI agents and workforces. The tool allows users to create scenario-based test sets, define custom evaluation criteria using 'Checks' (such as LLM performance, output content, and tool usage), and monitor the quality of live agent interactions through dashboards. Evals aims to provide a reliable command center for testing agent behavior and performance before deployment, with the ability to block publishing if evaluation scores do not meet predefined pass-rate thresholds.
