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ValidAnytime

A guaranteed false-alarm budget across your whole fleet, valid no matter how often you look.

Made by Compiled Intelligence — a frontier AI lab working on quantitative finance from first principles; ValidAnytime is the monitoring we built for our own model fleets, productized.

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  • For LLM engineers
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  • LLM eval regression
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Every alarm ships with its guarantee_tag and theorem_ref.

All comparisons

ValidAnytime vs Threshold dashboards (Datadog / Grafana-style)

Dashboards & APM

APM dashboards are excellent at showing you what happened and pulling everything into one pane; ValidAnytime is not a dashboard — it is the trustworthy alarm layer that sits alongside one. The gap is the alerting: a fixed line on a metric, checked continuously, is a false-alarm machine.

Capability comparison between ValidAnytime and Threshold dashboards (Datadog / Grafana-style).
CapabilityValidAnytimeThreshold dashboards (Datadog / Grafana-style)
Valid under continuous monitoring (unlimited peeking)
YesAnytime-valid by construction — Ville's inequality bounds the false-alarm rate at every look at once.
NoFixed thresholds and fixed-n tests inflate false alarms the more often you check.
Fleet-wide false-alarm control (online FDR)
YesA false-discovery budget shared across every stream, not per-alert luck.
NoAlerts are configured per-metric; no global bound on false discoveries.
Per-alarm statistical certificate
YesEvery alarm ships a guarantee tag and a theorem reference — you can audit why it fired.
NoAn alert tells you a line was crossed, not what its error guarantee is.
Prove it on your own history before committing (backtest gate)
YesReplay your past data: a config only ships if it stays quiet on normal history and fires on a real regression.
PartialYou can chart history, but there is no gate that validates a detector's error behaviour before it goes live.
Metric dashboards & visualization
PartialFocused reports on what we monitor — not a general-purpose dashboarding product.
YesBest-in-class charts, boards, and drill-downs.
Infra / APM / log integrations
PartialStream any numeric metric in; deep infra integrations are on the roadmap.
YesHundreds of first-party integrations across the stack.
Anomaly detection on stable noise
YesStays quiet on stable noise however often you look; fires once when evidence is real.
PartialAnomaly monitors exist but are tuned by hand and lack a formal error guarantee.

Where Threshold dashboards (Datadog / Grafana-style) is genuinely stronger

We are not trying to be a dashboard, a tracer, or a platform. If you need these, reach for the right tool — often alongside ValidAnytime.

  • Vastly broader integration and data-source coverage.
  • Mature, flexible dashboards and drill-down analytics.
  • Full APM, tracing, and log management in one product.
  • Larger ecosystem, community, and enterprise support.

A comparison table is claims; behavior is measurable. The honest drift-detector benchmark replays every detector we ship — including the classical control-chart rules most monitoring stacks alert with — against labeled synthetic breaks, and the detector guides explain each rule, where it wins, and where it lies.

Don’t take our word for it — prove it on your data.

Replay your own history through the backtest gate and see whether — and at which point — ValidAnytime would have caught your regression. Free, in minutes.

Prove it on your dataTry the detector in your browser

Comparison based on public documentation as of July 2026; corrections welcome — email hello@validanytime.com. Source: Threshold dashboards (Datadog / Grafana-style) docs