Klavis AI provides sandboxed environments for training LLMs on tool use and manages secure, authenticated enterprise integrations for deploying AI applications.
Klavis AI provides the MCP (Model Context Protocol) infrastructure layer that connects AI models to real-world tools and data in a controlled, secure way. It offers sandboxed environments where LLMs can safely learn, test, and refine tool usage, while also supplying production-ready integrations for enterprise AI applications with authentication and access control built in. The primary purpose of Klavis AI is to simplify and standardize how developers expose APIs, internal systems, and third-party services to AI agents without compromising security or reliability.
Klavis AI includes isolated sandboxes for tool-use training, allowing teams to simulate complex tool interactions, validate prompts, and debug agent behavior before deployment. It supports enterprise-grade integrations with common identity providers and authorization workflows, enabling secure connection to CRMs, databases, internal APIs, and other business systems. The platform manages credentials, permissions, and rate limits, reducing the operational burden of wiring multiple tools into AI workflows. Its MCP-focused design ensures consistent interfaces and predictable behavior across different models and runtimes.
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