Overview
Relevance AI is a low-code platform for building AI agents, tools, and collaborative workforces that automate business processes. Teams can connect thousands of apps, add knowledge and custom APIs, schedule tasks, monitor agent activity, and deploy agents for sales, support, marketing, operations, and research.
Our take
Relevance AI is for building and operating AI agents and multi-agent teams without writing the orchestration yourself, and it is one of the more considered products in a category full of demos. The questions to bring to it are the ones that apply to any agent platform: what the agents can touch, where a human approves an irreversible action, and whether you can audit a completed run step by step.
Worth it if
Operations teams automating multi-step work that varies too much for rule-based tooling.
Look elsewhere if
Simple, predictable integrations — a conventional automation tool will be cheaper and easier to debug.
✨ Features
Unlimited Agents & Tools
Builds specialist agents and reusable tools without per-agent limits.
AI Workforces
Combines multiple agents into coordinated teams for end-to-end processes.
2,000+ Integrations
Connects business apps, triggers, APIs, and custom workflows.
Operations & Governance
Adds schedules, escalations, analytics, evaluations, and enterprise controls.
⚖️ Pros & Cons
Pros
Cons
💰 Pricing
Free
$0 /mo
- 200 actions monthly
- $2 bonus vendor credits
- Unlimited agents and tools
- One workforce and user
Pro
$29 /mo
- 2,500 actions monthly
- $6 vendor credits
- Unlimited workforces
- Scheduling and smart escalations
Team
$349 /mo
- 7,000 actions monthly
- $70 vendor credits
- Five build users
- Analytics and higher concurrency
Enterprise
Custom
- Unlimited users and projects
- Agent evaluations
- Enterprise security
- Dedicated implementation
Categories
❓ Frequently Asked Questions
How do I control what an agent is allowed to do?
Through scoped credentials and approval steps rather than through the prompt. Give integrations read-only access wherever possible, require human confirmation before anything irreversible — sending, deleting, paying — and confirm the platform gives you a full trace of every step a run took. A run you cannot reconstruct cannot be debugged after a mistake.
Why do agent costs vary so much month to month?
Because agents choose their own number of steps. The same task can resolve in three tool calls or loop twenty times recovering from a bad intermediate result. Per-run step limits and spend caps affect your bill far more than the subscription tier, so set them before you put anything into production.