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Relevance AI is a low-code and no-code platform for building, deploying, and managing AI agents and multi-agent workforces. Its central idea is to divide business work among specialist agents, give each agent focused tools and approved knowledge, then connect those agents through a visual Workforce canvas. A team can build an agent from scratch, describe one to the Inventor assistant, or clone a template from the Marketplace. Agents can search, reason, call APIs, run custom code, send messages, update business systems, escalate decisions, and hand work to another specialist. Workforces add fixed sequences, AI-directed handoffs, conditions, tools, triggers, schedules, task monitoring, and human approval paths. Relevance Chat provides a separate conversational surface for running agents and workforces, with browser, desktop, iOS, and Android access, while the main builder is designed for desktop browsers. The platform supports more than 2,000 app connections, custom API calls, SDK and API triggers, incoming remote MCP servers, and a Relevance MCP server for building from clients such as Claude Code, Codex, ChatGPT, Cursor, VS Code, and Windsurf. Relevance AI is model-flexible. Users can spend included Vendor Credits on supported models, while paid plans can connect their own OpenAI, Anthropic, or Google API keys to bypass platform Vendor Credits. Pricing has two separate usage units. Actions measure tool runs, while Vendor Credits cover model and selected third-party usage. Free includes 200 Actions each month and a one-time allowance of 1,000 Vendor Credits, described as a $2 bonus. Pro costs $19 per month on annual billing or $29 month to month, with 2,500 monthly-equivalent Actions, $20 in monthly-equivalent Vendor Credits, two build users, unlimited Workforces, scheduling, premium triggers, Chat Mode, and bring-your-own LLM support. Team costs $234 per month on annual billing or $349 month to month, with 7,000 monthly-equivalent Actions, $70 in monthly-equivalent Vendor Credits, five build users, 45 end users, five shared projects, calling and meeting agents, A/B testing, analytics, and priority support. Enterprise is custom and adds evaluations, work-hour controls, SSO, RBAC, audit logs, multi-organization management, enterprise triggers, custom implementation, and governance. The main buying risk is cost and reliability at scale. Plan Actions reset, top-up Actions and Vendor Credits follow different rollover rules, a complex task can invoke many tools and sub-agents, and concurrency limits can queue work. Relevance AI is strongest for teams that have a recurring process, measurable acceptance criteria, connected business systems, and an owner who will monitor failures, costs, permissions, and human escalation. It is less suitable for a vague desire to automate everything, fully local or offline work, mobile-only building, or regulated deployment that has not completed a security, retention, model, and integration review.

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