AI agents are becoming robots for the digital world. Give them a world model for live telemetry
Agents reason over code and text — but not live system state. Langotime turns telemetry into a model of what's happening, why, and what happens if you act.
Request early accessBuilt on a Time Series World Model
Langotime is not a generic LLM. It runs on a Time Series World Model (TSWM) — a model built to understand operational systems, not to chat about them. It learns:
From raw telemetry to a safe next action
Connect
Pull metrics, logs, traces, topology and deploys into one live operational state.
Explain
Trace the causal chain behind a KPI change or incident — root cause, not just correlated alerts.
Simulate
Project what happens if you scale, roll back, shift traffic or wait — before anyone acts.
Act
Hand agents and engineers a safer next action, grounded in telemetry, with a human in the loop.
Start with the problem you're feeling right now
Kubernetes Autoscaling
Are we overprovisioning Kubernetes just to feel safe?
Reads live telemetry, anticipates load, and moves replicas and resources before cost or latency bite — keeping service-level checks green.
Agents are brilliant. They're also blind.
LLMs reason over code, text and runbooks. They can't see live telemetry, trace a cascade, or tell you what happens if they act. Langotime is the layer they're missing — and it works with the agents you already use.
If you…
Langotime is for you.