The Use Case: Taming the Chaos of Enterprise AI
Your organization has moved beyond initial experiments. Multiple teams are now building with AI, but this has created a new set of problems: dozens of disconnected models, inconsistent security practices, no visibility into costs, and duplicated infrastructure everywhere. You’ve hit the wall of “model sprawl,” and it’s become a massive security risk and a financial black hole.
How Drizzle:AI Solves This
To solve this, you need to move from a project-based mindset to a platform-based one. Our solutions are designed to provide this centralized, enterprise-grade foundation.
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The Enterprise AI Hub is our core solution for this use case. It’s a sophisticated LLM Gateway that acts as a single, secure entry point for all AI traffic in your organization. You can manage your entire portfolio of models, enforce team-based quotas and access policies, and get a unified view of performance and costs.
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The AgentOps Framework provides the underlying standardized infrastructure. By deploying our framework, you ensure that every team is building on the same secure, compliant, and observable foundation, eliminating duplicated effort and reducing operational overhead.
Example Applications
- A “Platform for the Platform” Team: Equip your central platform or MLOps team with a turnkey solution to serve the entire organization.
- FinOps for AI: Use the AI Hub’s detailed dashboards to track and manage token and GPU costs across different business units.
- Secure AI Sandbox: Provide a safe, governed environment for all your teams to experiment with new models and build new applications.