Phinite

Enterprises building AI agents today stitch together separate tools for designing, deploying, observing, governing, and evaluating agents, and lose context at every handoff between them. As different departments build their own agents on different frameworks, organizations end up with agent sprawl: nobody can quickly say how many agents are running, who owns them, or what they cost. Each disconnected system also requires its own security review, and access rules, approval gates, and spend limits must be set up separately for every agent rather than applied consistently, leaving gaps an audit can find.

Phinite is described as an operating system for multi-agent AI that covers the full agent lifecycle in one cloud-agnostic platform: design, deploy, govern, observe, and evaluate. Agent Graph Studio provides a visual canvas to build multi-agent workflows with conditional branching, parallel paths, and human-in-the-loop checkpoints. Dev Studio lets teams build and version reusable tools, skills, and integrations, and ship the same graph across dev, UAT, and production with one-step rollback. Governance sets role-based access control, human approval gates, spend limits, and a full audit trail at the platform level, while Evaluation runs benchmarks, regression tests, and traffic replay against user-defined quality metrics before and after agents reach production. The platform also offers 80+ integrations (e.g. Slack, Salesforce, Jira, AWS) and supports deployment on AWS, Azure, or GCP with a customer's own model keys to avoid cloud or model lock-in.