As enterprises confront AI agent sprawl, xpander wants them to own their own control and context layer

As enterprises accumulate AI agents at a rapid pace, a new infrastructure challenge emerges: the need for a centralized control and context layer to govern these agents. Gartner predicts that by 2028, the average Fortune 500 company will manage over 150,000 AI agents, compared to fewer than 15 in 2025. However, only 13% of organizations currently have adequate AI agent governance in place, according to Gartner's research.

This gap is driving the growth of infrastructure solutions that work above individual models and agents, managing execution, permissions, observability, memory, access to enterprise systems, and lifecycle management. xpander.ai, a startup founded by three former AWS principal engineers, aims to fill this gap by providing a vendor-neutral control plane for building, running, and governing AI agents across various models, frameworks, and infrastructure environments.

CEO and co-founder David Twizer highlights three key problems enterprises face: agents running locally without centralized governance, isolated agent workflows, and vendor lock-in. xpander's Universal Harness provides a model-, framework-, and cloud-agnostic runtime for executing agents as portable enterprise workloads, allowing companies to use the platform's hosted environment or self-deploy on Kubernetes or on-premises infrastructure.

The startup also supports multiple frameworks, including LangChain, Strands, and Agno, and enables enterprises to bring agents built with these frameworks.