AI Observability for Critical Systems
From infrastructure to AI —
Pulse connects the stack.
The operational intelligence platform that monitors, correlates, explains, predicts, and recovers — across every critical system you run.
All data sources are transparently labeled as REAL, HYBRID, or SYNTHETIC.
<50ms
Health check latency
∞
Systems supported
24/7
Continuous monitoring
5
Intelligence layers
Why It Matters
Critical systems are flying blind.
Pulse fixes that.
Without Pulse
- Power grids degrade without warning
- AI models drift without detection
- Traffic systems fail without explanation
- Cascading failures stay invisible until it's too late
With Pulse
- Every system monitored in a single command center
- Cross-system correlation catches cascading failures
- AI explains what happened — in plain English
- Predictive intelligence warns before failures occur
Data Transparency
Every data point is labeled by source.
Pulse never hides where its data comes from. Every metric carries a provenance badge so you always know what's real, what's modeled, and what's simulated.
Live External APIs
Live upstream feeds — currently TomTom Traffic Flow API and Open-Meteo Weather API. Verified, timestamped, and continuously refreshed.
Real Context + Modeled Telemetry
Real weather and environmental data blended with domain-specific synthetic telemetry — drones, sewer, EV charging. The real context drives realistic modeled behavior.
Simulated Telemetry
Statistically realistic simulated data for domains where live integration is not yet connected or not appropriate (e.g., healthcare, defense). Always clearly labeled.
How It Works
Five layers of operational intelligence.
Raw signals become actionable intelligence. Each layer builds on the last.
One operational view across domains
Health telemetry and operational signals across AI models, infrastructure, sensors, and software. Live upstream feeds where available; hybrid enrichment and synthetic scenarios stay clearly labeled. One command view for provenance-labeled data.
Connect what others miss
Cross-system event correlation that links anomalies across power grids, traffic networks, weather data, and AI agents — revealing cause chains invisible to single-system tools.
Understand in plain language
Human-readable explanations of system behavior, decisions, and anomalies. Not dashboards of numbers — narratives your team can act on.
Know before it breaks
Time-to-failure forecasting and degradation modeling. Pulse tells you what will fail, when, and what to do about it — before the alert fires.
Bounce back faster
Recovery intelligence that tracks resolution patterns, suggests playbooks, and calculates estimated recovery timelines for every incident class.
Advanced Capabilities
Intelligence that compounds.
Time to Failure Prediction
PredictiveMachine learning models trained on your system's baseline behavior predict component failures hours or days before they occur. Maintenance windows become strategic, not reactive.
System Health Baselines
AdaptivePulse learns what "healthy" looks like for every system it monitors — latency curves, throughput patterns, resource utilization norms. Deviations are flagged against your system's own fingerprint, not generic thresholds.
Recovery Intelligence
ResilienceEvery incident builds institutional memory. Pulse tracks what worked, how long recovery took, and which playbooks applied — then surfaces that intelligence automatically during the next event.
Cross-System Correlation Engine
ConnectedWhen a weather event impacts grid load, which triggers traffic signal failures, which cascades into autonomous vehicle rerouting — Pulse traces the full chain. One root cause. Every downstream effect. Connected.
Where Pulse Operates
Built for systems that can't afford to fail.
Smart Cities
Energy & Grid
Aviation & FAA
Weather & NOAA
Healthcare
Cybersecurity
Autonomous Systems
Financial Systems
See Pulse in action.
Six monitored domains, AI-powered risk scoring, cascade failure detection, and provenance-labeled data throughout. Live upstream feeds where available; hybrid and synthetic telemetry clearly labeled where demos require it.
Transparency by default.
Public health endpoints, open proof surfaces, and JSON APIs you can verify independently. Every metric carries a provenance label — REAL, HYBRID, or SYNTHETIC — so reviewers, evaluators, and integration partners always know exactly what they are looking at.