Introducing a new enterprise category: the AI Operations Layer. Currently in internal production MVP testing — looking for investors to move into pilot

Most enterprises are still stuck between impressive AI agent demos and systems that actually hold up in real operations. The agents themselves are improving quickly. The bigger gap is the missing layer above them — the system responsible for orchestration, governance, state management, monitoring, and reliable execution across multiple agents and existing enterprise systems. I’m calling this the AI Operations Layer: a new enterprise category that sits horizontally above existing tools and agents to make AI operationally viable at scale. We’ve built an early version and are currently in internal production MVP testing, running it against realistic operational scenarios where reliability, auditability, and recovery matter. The next step is moving into structured pilot deployments with real enterprise environments. I’m looking to speak with investors who: * See the gap between current agent frameworks and production-grade operational systems * Are interested in the emergence of a new infrastructure layer in the enterprise AI stack * Want to help take a production MVP into the pilot stage. Happy to share more on the architecture, current testing approach, and the category thesis. Open to direct conversations.