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Bottom Line
As Vertiva moves AI operations in-house, it takes on a responsibility managed AI vendors used to absorb: knowing exactly what the system is doing and what it costs. A dedicated operations layer traces every model call, evaluates quality continuously, and attributes cost down to the individual tenant.
What the Platform Delivers
| Capability | What It Gives the Business |
|---|---|
| LLM / Agent Tracing | Full trace tree of every model call, exported to a standard dashboard stack |
| Evaluations Platform | Automated offline (CI-gated) and online (sampled) evaluation |
| Token Economy | Per-org, per-user, per-workspace budgets, quotas, and chargeback |
| Cost-Aware Model Routing | Requests routed to the cheapest model that still meets the bar |
| Semantic Cache | Repeat or near-duplicate questions answered without re-running the pipeline |
Observability Is a Requirement of Every Detail
Every component must ship with its own metrics, logs, and traces flowing into the same dashboard stack, and its own cost model and per-tenant attribution — nothing is allowed to become a blind spot.
The Economics Behind the Philosophy
Cost-aware routing and semantic caching are the mechanisms that make self-hosting economically defensible. Cache hits must produce a measurable reduction in cost and latency, not just a theoretical one.