Give every team a governed, self-serve path to models and agents, with access, cost, and guardrails handled by the platform. Enable AI instead of gatekeeping it.
Teams want to build with AI faster than any central group can review models, keys, and integrations one at a time, so the platform team turns into a queue.
Teams wait on platform or security to vet each model, key, and integration. AI ships at the speed of the backlog.
Blocked teams wire up their own keys and tools. You inherit a sprawl you can't see, support, or secure.
Every team re-solves auth, routing, logging, and limits. Duplicated effort slows everyone down.
Feature requests now come from every product, support, and ops group at once, not a single ML team you can serve by hand.
New providers and models land constantly. Hard-wiring any one of them into apps ages badly and slows the next switch.
When usage is ungoverned, the cost, security, and compliance exposure lands on the platform team regardless of who shipped it.
Put one governed path in front of every model, and let teams self-serve inside the guardrails you set, without re-platforming each one.
Curate a marketplace of vetted models and apps in the Staging Area, then let teams stage and deploy them in minutes: self-serve, inside the policy you define once.
Apps call a single endpoint. The inference gateway routes across OpenAI, Anthropic, Azure, and Bedrock, with failover and routing policy handled centrally: no per-provider rewiring.
Access maps to your org via identity integration. Budgets, data rules, and policy are enforced and logged on every call, so enabling a team doesn't mean trusting it unconditionally.
Each part of Actualyze removes a job you'd otherwise build and maintain yourself, so you enable AI without re-solving the infrastructure.
Stand up one governed control plane and let every team build on it, safely and without waiting on you.
