Relevance AI

Relevance AI is a platform for building and running teams of AI agents that complete tasks on autopilot. Instead of automating a single workflow, you assemble multiple agents that work together — for example, one agent preparing pre-meeting briefs, another nurturing qualified inbound leads, and a third escalating at-risk renewals. The company positions the product around the idea of an "AI workforce" that handles repetitive operational work so people can focus on more strategic tasks.

The platform's flagship feature is Invent 2.0, described as a "24/7 AI solutions engineer." Invent helps your team identify what to automate, turn internal expertise into reliable agent systems, and improve those systems over time. According to the site, even non-technical teams can stand up their own AI workforces in hours using Invent, with enterprise-class AI practices built in — including evaluation, monitoring, and governance.

Relevance AI also offers an embedded deployment team for enterprise customers. The onboarding process follows a structured timeline: in weeks 1–2, the team helps you map workflows and identify the best agent use cases; from week 3 onward, you deploy your first team of customized agents, with some use cases taking as little as a few hours to set up; from week 4 onward, you evaluate the pilot, make it production-ready, and begin building higher-impact use cases independently — including what the company calls Level 3 and Level 4 autonomous agent workforces.

The site publishes several customer case studies with specific numbers. Qualified reports generating $7M in pipeline with 35+ AI agents across the organization and a 10x increase in output. Send Payments says it saves 40 hours weekly by going AI-first across global operations, with thousands of conversations automated. Zembl reports a 30% increase in customer conversions with 24/7 AI sales coverage and 60% faster average call times. Other companies shown on the homepage include Canva, Databricks, Confluent, Autodesk, Lightspeed Commerce, Rakuten Advertising, Freshworks, Aveva, and Employment Hero.

Best for

• Operations teams that want to automate recurring tasks like contract review, invoice matching, and meeting briefs
• Sales and marketing teams looking to nurture inbound leads or run 24/7 AI sales coverage
• Customer-facing teams handling high volumes of conversations across time zones
• Non-technical teams that want to build agent workflows without writing code, using Invent
• Enterprises that want a guided deployment with an embedded team and governance, monitoring, and evaluation built in
• Companies scaling from a single pilot agent to multi-agent workforces across departments

Frequently asked questions

What is Relevance AI?

Relevance AI is a platform for recruiting and managing teams of AI agents that complete tasks automatically. It combines a no-code agent builder (Invent) with enterprise features like evaluation, monitoring, and governance.

Do I need technical skills to use it?

The site says non-technical teams can stand up their own AI workforces in hours using Invent. Some use cases, per the company's onboarding timeline, can be deployed in as little as a few hours.

How long does it take to see results?

The company's onboarding plan targets your first team of agents by week 3, with pilot evaluation and independent building of new use cases from week 4 onward. Actual timelines will depend on your use cases.

How much does Relevance AI cost?

The homepage doesn't list pricing. There's a sign-up option for the app and a "Talk to sales" option for booking a demo, so pricing details likely come from the sales team or the app itself.

What kinds of tasks can agents handle?

Examples shown on the site include detailed pre-meeting briefs, nurturing qualified inbound leads to demo, escalating at-risk renewals, contract review, and invoice matching. The platform supports multi-agent teams working together on these workflows.

Is there an enterprise offering?

Yes. There's a dedicated Enterprise page, and the site describes an embedded deployment team that gets enterprise customers live and trains their teams to build agents on their own.

Alternatives

• Wordware — an AI assistant that learns your context and anticipates tasks; better if you want a personal AI assistant rather than a multi-agent workforce.
• Supermemory — infrastructure for continuous learning and memory for AI agents; better if you're building your own agents and need a memory layer rather than a full platform.
• ArangoDB — a unified data platform for graph, vector, document, and search; better if your need is the data backend behind AI systems rather than the agents themselves.