Harness the power of natural language to simplify complex cloud operations.
We are thrilled to announce a new way to interact with the Omnistrate platform: native Agentic AI integrations powered by our new MCP server. This innovation is set to redefine how you interact with your cloud infrastructure, making DevOps and SRE tasks more intuitive, efficient, and accessible than ever before for your distribution channels. Our MCP tools are purpose-built and deliver on the primarily value of an integration with an AI Agent: to sift through unstructured data from multiple data sources.
"Omnistrate gave us an enterprise-grade control plane without the need to hire or build one in-house. With their decade of expertise baked in, we launched faster, cut costs, and focused on growing our business from day one. Highly recommended for any team building a managed SaaS." - Peter Farkas - Co-Founder & CEO Ferret DB
Organizations today face mounting pressure to deliver AI capabilities while managing exploding infrastructure costs. GPU expenses can easily consume your AI budget, yet most organizations are unknowingly wasting massive amounts of these expensive resources through inefficient allocation strategies.
The solution lies in GPU sharing strategies that transform expensive, underutilized hardware into highly efficient, multi-tenant resources that serve multiple workloads simultaneously.
The recent stability issues at Neon provide a compelling case study of what happens when products grow beyond their initial architectural assumptions. Neon's experience—moving from a monolithic control plane to a cell-based architecture under pressure—illustrates a critical pattern in SaaS evolution: the inevitable need for horizontal scaling through cellular architecture.
Many B2B startups start their cloud journey with AWS ECS or GCP Cloud Run. It's understandable—they're familiar, quick to set up, and tightly integrated with the hyperscalers' ecosystems. Throw in some Terraform, and you have a hello-world deployment workflow that seems "good enough" to get your SaaS up and running.
But "good enough" quickly breaks down as you scale.
