Every computing era
scaled on trust.

When Anthropic released MCP, it was déjà vu — the same trust boundary problem from my PhD — just a new era.

At HPE and Splunk, I saw hundreds of customers prepare for AI to transform their businesses, with tools, processes, guardrails. The pattern is always the same: it's not the technology that stalls projects. It's operational details — safety, security, governance. Teams try to DIY, stretch IAM to cover new agentic use cases, or add more tools to their arsenal. Neither scales, and all ignore the core problem.

So we went back to first principles — we imagined something deterministic, easy to use, and pervasive. My PhD thesis introduced authenticated system calls — cryptographic proof at every trust boundary. We've extended this to the AI stack: not just invocations, but context, prompts, and deterministic controls that work before harm happens.

AI is the future, but right now, it's dangerously unproven. Prompt injections, tool misuse, runaway agents — headlines don't lie. Previous infrastructure had decades to evolve. Today, we don't. So, with MACAW, what worked before still works. Your policies still apply. Your tools still function. We're not replacing your stack — we're making it safe, with you in control.

Trying something that actually works should be a no-brainer. That's why we offer a generous free tier for POC and R&D. For enterprises that need support and services — we have you covered too.

Come give it a try. I'd love to hear what you think.