Zahara

Zahara is a control plane and harness for building, running, observing, controlling, and optimizing swarms of AI agents. It provides a unified platform where teams can specify agents via JSON, define identity and scope, build using four methods (chat, flow, code, or import), and deploy through a runtime gateway. Key capabilities include a graph-first observability layer that streams real-time knowledge graphs of agent runs, runtime governance with budget caps, guardrails, human-in-the-loop gates, and an immutable audit log. Zahara also offers an eval harness for version comparison, automated rollback, and continuous improvement. It integrates with major model providers like OpenAI and supports import from MCP, LangGraph, and other frameworks. The platform is designed for production reliability, addressing the gap between a working demo and a deployable agent.

Key Benefits

• Graph-first realtime agent tracking
• Built-in governance with guardrails and HITL
• Multiple build modes (vibe, flow, code, import)
• Eval-driven optimization with version control and rollback