Know your performance.
You cannot tune, size, or trust what you cannot see. We build observability into every platform from day one, and rebuild it for teams whose tooling has become too expensive or noisy.
Informed by years of running the Grafana LGTM stack in high-scale production, at tens of millions of active series.
For inference, the numbers that matter
A GPU is too expensive to guess about. These signals tell you whether a model is fast enough, whether the hardware earns its keep, and when to add capacity.
Latency where users feel it
Time to first token and tokens per second, tracked per model and per endpoint.
Utilization you can act on
GPU memory, queue depth, and saturation, so you know when to burst and when to buy.
One trail per request
Metrics, logs, and traces linked from the gateway through the model server, so a slow answer has an explanation.
How we approach it
Open standards first
Instrumentation built on OpenTelemetry, so your telemetry is portable and no vendor owns it.
Off costly tooling
We have moved large production estates from commercial monitoring to an open stack to control the bill, without losing visibility.
Tracing people use
We work with your developers to instrument their services, so traces exist where the problems are.
Alerts worth waking for
Fewer, better alerts, with AI-assisted summaries that turn a night of noise into a short morning briefing.