Remylar AI: Context Infrastructure for Enterprise AI

We're building an AI-native AI Infrastructure for Enterprise agents to operate in messy environments. Today, Agents fail not because they're not capable but because of organizational bottlenecks like data and context. There's a huge foundation gap that we're bridging by providing real time data and context for agents to operate in real time. This layers extracts, cleans and governs data that agents can query and get minimal but complete context to finish their task.

We’re already using this infrastructure to build a peer-to-peer (P2P) agent for FinOps, because finance operations are one of the clearest examples of where agents break today. FinOps is messy. The data is spread across systems, changes constantly, and usually shows up incomplete, stale, or out of context. That makes it hard for agents to do anything reliably, even when the model itself is capable. We built this infra to solve exactly that problem. It gives agents access to real-time, governed, task-ready context so they can actually operate inside messy enterprise environments instead of failing on missing or outdated information. FinOps is where we’re starting, but the bigger goal is to power enterprise agents anywhere context quality is the bottleneck.