The problem
An AI-native product wants one substrate, not four integrations.
An AI-native product leans on a handful of moving parts at once — memory, model routing, prompts, evaluation. When each arrives as its own integration, most of the early effort goes into wiring them together and keeping them in step, rather than into the product itself.
One coherent surface changes that. The same call shape everywhere means the team reasons about the product, not the plumbing underneath it.
How it works
One surface, two languages, wherever your data lives.
AI Infra puts memory, routing, prompt management, and evaluation behind a single API. The Python and TypeScript surfaces mirror each other — the same methods, the same parameter shapes, the same typed responses — so a change reads the same in either language and stays safe to evolve.
It runs cloud-managed by default, and deploys into your own environment when data residency requires it — the same surface either way, so where the runtime lives is a deployment choice, not a rewrite.
- Memory, routing, prompts, and evaluation reached through a single, consistent API
- Python and TypeScript share the same surface — the same methods and shapes in both
- Typed end to end, so the integration is legible and safe to evolve
- Cloud-managed by default, or deployed into your own environment when data residency requires it
- One integration point as the product grows, rather than a widening set of them
Build on one substrate.
AI Infra is one of the accelerators our Services team builds on. Tell us what you're building and we'll stand it up on a runtime that's ready for production.