Enterprise AI Adoption Platform

Every large enterprise is investing in AI, yet most initiatives stall between demo and deployment. The gap is not model capability, it is the absence of a platform to deploy, govern, evaluate, and scale AI across the organization safely.

• Pilots don't reach production. Promising prototypes fail to clear security, compliance, and reliability bars.
• No governance layer. Enterprises lack a way to set policy, manage access, and audit how AI is used across teams.
• Evaluation is missing. Without systematic measurement, teams cannot prove an AI system is accurate or safe enough to trust.
• Fragmented adoption. Each team adopts its own tools and models, creating shadow AI, duplicated spend, and inconsistent risk.

• Evaluation has matured. Teams can measure quality, safety, and regression as a first-class system.
• Governance is a board-level concern. Regulation and risk are forcing centralized oversight of AI usage.
• Agents raise the stakes. As AI begins to take actions, the need for control, observability, and rollback becomes non-negotiable.

• AI control planes. Platforms for deploying, permissioning, and observing AI and agents across the enterprise.
• Evaluation and monitoring. Systems that measure quality, detect drift and regression, and gate releases.
• Governance and compliance. Policy, audit, and access infrastructure for responsible enterprise AI usage.

We back founders building the platforms that turn enterprise AI from scattered experiments into governed, measurable production systems, the connective infrastructure on which large organizations standardize their AI.