Every AI-native product needs the same substrate underneath it: memory, model routing, prompt management, caching, and retrieval. AI Infra is that substrate — the components our Services team builds your product on, so the work goes into your features instead of the plumbing beneath them.
What it is
An LLM call on its own forgets every turn, speaks in one fixed voice, and costs the same whether or not it has answered the question before. AI Infra supplies what turns those calls into a product — durable memory, capability routing, versioned prompts, and caching — through one API our teams reach for on every build.
The components
Working, episodic, and long-term memory over a hybrid vector and graph store — so an application remembers the user, the domain, and what has already been discussed across sessions.
Route by capability, not by model name. Move between providers without touching application code, with per-tenant overrides, so a product stays resilient as the model landscape shifts.
Prompts managed as versioned artifacts with evaluation, so a change to how the system talks is deliberate, reviewable, and easy to roll back.
Response and retrieval caching that keeps latency and cost down as usage grows — the difference between a demo and something that runs in production.
Grounding an application in your own content, so answers are anchored to what's true for your domain rather than the model's general prior.
Memory, routing, prompts, and evaluation behind a single surface — cloud-managed or deployed into your own environment when data residency requires it.
AI Infra
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.