Automation discovery
Discovery helps teams identify candidate automations before they build by ranking opportunities by effort, value, and readiness, then showing the expected impact and complexity.
Multi-agent platform for building and managing AI agents
CrewAI is a multi-agent platform for building, deploying, managing, and optimizing AI agents across an organization. The site positions it as an open platform that supports the full agent lifecycle, from identifying what to automate to running and improving production workflows.
It combines no-code and code-first tooling so different teams can work in the same system. Public pages describe visual workflow building, CLI and API options, tracing and governance features, and a control plane designed for enterprise agent operations.
Discovery helps teams identify candidate automations before they build by ranking opportunities by effort, value, and readiness, then showing the expected impact and complexity.
The platform supports no-code visual building as well as CLI and API-based development, so both business users and technical teams can work from the same platform.
CrewAI’s Control Plane sits in the execution path of every workflow and provides tracing, observability, compliance controls, and reversibility for agent actions.
The platform includes RBAC, audit trails, enterprise IAM, human-in-the-loop approval gates, and runtime hooks for policy checks and PII redaction.
CrewAI supports automated and human-guided training, multi-LLM testing, evaluation workflows, and performance tracking to improve production runs over time.
The pricing page lists workflow deployment and management capabilities such as deployment history, usage dashboards, token counts, hallucination scores, cron scheduling, and Slack/Teams workflow chat.
Use Discovery to surface business processes that are worth automating, then review the suggested impact and complexity before starting implementation.
Use the visual editor, CLI, or API to create multi-agent workflows that fit different skill levels and implementation preferences.
Use tracing, RBAC, audit trails, and approval gates to operate agents in production with oversight and intervention points.
Use evaluation, multi-LLM testing, and training tools to review how a workflow performs and tune it as new runs generate data.
Use the platform to support teams across sales, marketing, finance, HR, engineering, and other business functions that need shared agent infrastructure.
CrewAI is presented as an open platform for building, deploying, managing, and optimizing enterprise AI agents. The site describes it as a multi-agent platform with both no-code and code-first options.
The pricing page shows a Free Basic plan with a visual editor, AI copilot, GitHub integration, and 50 workflow executions per month, plus a custom Enterprise plan with private infrastructure and support.
Yes. The pricing page lists a visual editor, AI copilot, GitHub integration, and export options, while the product pages also mention CLI, APIs, tracing, and role-based access control for broader deployment workflows.
The site emphasizes observability, guardrails, human-in-the-loop approval, RBAC, audit trails, deployment history, and workflow management, but it does not provide a complete public list of all supported external integrations.
CrewAI Discovery is described as a way to identify automation opportunities by matching business context against patterns observed across production agent runs. It is available to CrewAI users and can connect internal data sources such as documents, knowledge bases, and existing systems.
Traffic data is for reference only.
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