The AI-native platform sits between an organization’s people, applications, and agents, and every AI model the organization uses, giving enterprises one place to govern, secure, operate, and optimize AI. Built from the ground up, the platform easily integrates with any OpenAI-compatible models, the ecosystem of AI client tools, and 3rd party platforms, meeting the demanding needs of modern enterprises. The company’s hosted platform is now in Early Access through its Design Partner Program.
The Actualyze platform’s integrated approach, where every request flows through a governed path, allows enterprises to adopt and scale AI. Each inference request is tied to the person, team, and application behind it, then access checked, inspected, charged to the callers’ budget, and recorded before it reaches a model provider. The platform abstracts provider credentials, to provide intelligent routing and ensures the governed path is the only path while maintaining agnostic access to the rapidly changing model provider landscape.
“It’s clear that AI has become a new layer of the enterprise stack,” said Rafi Khardalian, CEO and co-founder of Actualyze AI. “A model call looks like any other API request, a key, an SDK, an invoice at month’s end, but the resemblance is the trap. The systems that govern the rest of an enterprise’s request traffic can authenticate a model call and count it, but not read the prompt inside it, know if data is leaking, know the best place to route it, or charge the call to the team behind it.
So anyone with a key can call a model, and all that spend pools into one bucket with no visibility into who spent it or accountability for it. Agents raise the stakes, fanning a single task into dozens of autonomous calls. That’s the problem we built Actualyze to solve”
The platform is organized around four pillars:
- Govern. Access, approvals, budgets, and spend policy for every team and every model, defined once and enforced on every call.
- Secure. Inference scanning, guardrails, and audit trails applied inline, so sensitive data is protected before it leaves the organization.
- Operate. Curate, stage, and deploy every model in the catalog, with visibility into what’s running, where, and how it performs.
- Optimize. Virtual models route each request to the best eligible model by capability, cost, and quality, with automatic failover.
“You bet on a market this big by betting on the people who’ve already tamed one like it,” said Sean Lynch, CTO and co-founder of Actualyze AI. “We built Actualyze because enterprises need one governed path for every AI request, and this is the team that’s spent a career building the infrastructure entire businesses run through. The market is ready, and so are we.”
Khardalian and Lynch previously founded Metacloud, the managed private cloud company acquired by Cisco. They spent the past year in conversations with platform, security, and finance leaders at large enterprises, and built Actualyze around the problems those teams described.
