Operately vs Rhythms AI

Operately is open-source goal and project management software for connecting OKR tracking with project execution and built-in check-ins. Teams can manage cascading goals, review progress, and organize work through projects, kanban boards, message boards, documents, and workflows. The codebase is licensed under Apache 2.0. Operately runs on the web, through an API, or as a Docker self-hosted deployment that takes about five minutes to set up. It provides an external API and CLI, plus MCP connections for Claude, ChatGPT, Cursor, and other AI clients. API endpoints require tokens, with read-only tokens unable to make mutations. Security features include HTTPS/TLS in transit, encryption for sensitive data at rest, role-based controls, monitoring, and automated backups. When AI features are enabled, content may be sent to OpenAI, and those features can be disabled in account settings. Plans include Free at free, Pro at $49 a month, Business at $149 a month, and Unlimited at $249 a month.

Rhythms AI helps organizations create and manage objectives and key results (OKRs). It drafts measurable, aligned goals using company strategy, peer-team objectives, and prior-quarter performance, then updates progress from connected tools, flags risks, runs playbooks, and generates reviews. The service connects to more than 200 tools for progress rollups from team goals to company objectives; named integrations include Jira, Salesforce, HubSpot, GitHub, Tableau, Linear, Google Sheets, and Microsoft Planner. Its AI agent can prompt owners about stale goals, track team adoption, and surface process issues. Rhythms for Slack supports check-ins, meeting summaries, approvals, and follow-ups; the Microsoft Teams integration is marked “Coming soon.” The REST API reads and writes OKR data, but support must issue tokens. A web workspace starts with a 14-day trial of paid features and then continues on the limited Free plan. Rhythms states that AI operations use zero data retention and customer data is not used to train models.