Cartha — Agent Operations Platform

What it does

Most teams get AI agent traces. Almost nobody gets governance. Cartha is the ops layer for agent fleets: full run timelines, scoped memory enforced on the server (user/agent/team/org), hard spend budgets that fail closed, attenuated multi-agent delegation, policies, and human-in-the-loop. Instrument in a few lines (Python SDK): @trace, @tool, wrap_openai, then see agents, costs, and memory in one dashboard. Not another chatbot builder. You bring the agents; we keep them accountable.

Cartha is the governance-first agent operations platform. Trace AI agent reasoning, manage multi-agent memory with time-travel recall, enforce hard budget ceilings, and maintain a full audit trail for enterprise compliance. Python & TypeScript SDKs, live dashboard. Built in Mumbai, India.

Runtime governance for autonomous agents — observability, policy enforcement, and a decision trace you can hand to risk. Two lines to instrument. Stops a tool call before it lands. customer_data.export never executed. Waiting on human approval. It has a goal, a model, and tools. Nothing watches the side effects yet. AI in production is a black box. When things break, you're left guessing. Between your agents and production — so they're governable, predictable, and auditable. Init and instrument. Two lines against the stack you already run — LangGraph, CrewAI, OpenAI Agents, and the rest. Every LLM call, tool, and memory access lands in one event graph. Cost, latency, and agent health…from cartha.in

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