[ Product ] EdgeTelemetry · v.0.9

The control layer for autonomous data centers.

EdgeTelemetry ingests heterogeneous telemetry from GPUs, hosts, cooling, power, and network systems, normalizes it into a unified schema, and validates system readiness — turning weeks of fragmented onboarding into hours of automated validation.

weeks → hrs
GPU rack onboarding
Time from rack landing to operational status, automated end-to-end.
unified
Schema across vendors
One operational view across GPU, host, cooling, power, network telemetry.
claude-ready
Reasoning layer integration
Architected for autonomous diagnosis and remediation via Claude tool use.
→ The architecture

Five sources. One schema. One control plane.

Modern GPU and data center environments stream telemetry from a fragmented vendor stack — GPU drivers, host OS metrics, cooling sensors, power systems, network fabric. Each in its own schema, sample rate, and reliability profile.

EdgeTelemetry ingests them in real time, normalizes them into a single operational schema, validates system state against readiness criteria, and exposes everything to a reasoning layer that turns telemetry into decisions.

// pipeline
SOURCES
gpu_telemetry · host_metrics · cooling_sensors · power_systems · network_fabric
UNIFIED SCHEMA
normalize · validate · enrich · stamp_lineage
READINESS VALIDATION
check_thresholds · check_dependencies · gate_for_operations
REASONING LAYER (CLAUDE)
interpret_state · explain_anomaly · plan_remediation
ACTION
diagnose · remediate · escalate
[ 01 ] Ingestion

Heterogeneous telemetry, one pipeline.

Real-time ingestion from GPU drivers, host metrics, cooling, power, and network fabric. Resilient to source variability. No vendor lock-in.

[ 02 ] Normalization

One unified operational schema.

Normalization into a consistent schema across vendors and source types. Validation, enrichment, lineage tracking. Queryable in real time.

[ 03 ] Readiness validation

Automated rack onboarding.

Validates system state against readiness criteria before declaring operational. Catches misconfigurations before they cost cluster time.

[ 04 ] Reasoning layer

Claude-powered autonomous ops.

Architected for a reasoning layer (typically Claude) that interprets state, hypothesizes root causes, plans remediation, and escalates with full context.

The right time to invest in unified telemetry isn't after your first major incident. It's before the rack ever powers on. EdgeTelemetry exists because we got tired of building this layer from scratch on every engagement.
DehazeLabs · Engineering Team
gpu_data_centers Operators standing up new GPU clusters who can't afford weeks of manual onboarding per rack — and whose customers expect immediate operational readiness.
colocation_providers Colos serving AI workloads where customer SLAs depend on telemetry transparency and validated infrastructure state.
hyperscaler_capacity_partners Partners building capacity for hyperscalers where audit-grade telemetry, validation, and lineage are contractual requirements.
industrial_data_environments Manufacturing and industrial environments where the same fragmentation problems apply — heterogeneous sensors, vendor schemas, validation requirements — and the agentic operations vision is the same.

Get a briefing on EdgeTelemetry.

EdgeTelemetry is currently deployed with select customers. We're working with a small number of additional operators on early access. If your environment fits, we'd like to talk.