Industries / Oil & Gas
Predictive intelligence for remote and distributed industrial assets
Remote assets, harsh environments, and sparse telemetry demand a monitoring approach built for operational reality — not laboratory conditions.
The operating challenge
Oil and gas operations face unique monitoring constraints that legacy predictive systems were never designed to handle.
Remote assets
Equipment distributed across hundreds of miles. Physical inspection is expensive and infrequent. Problems develop between visits.
Rotating equipment
Compressors, pumps, and turbines operate under variable loads with complex failure modes that require high-resolution mechanical sensing.
Sparse telemetry
Connectivity constraints limit data transmission. Legacy SCADA systems provide coarse readings at infrequent intervals.
Costly downtime
Unplanned shutdowns cost hundreds of thousands per day. The difference between planned maintenance and emergency response is measured in millions annually.
Flexible deployment model
Integrity combines multiple data sources into a unified intelligence layer — regardless of what exists on-site today.
Field instrumentation
Custom Integrity sensor stacks for assets that lack adequate monitoring — vibration, power, temperature, and environmental sensing.
Existing site infrastructure
Augment what you have with higher-resolution capabilities without replacing operational SCADA or DCS systems.
Gateway ingestion
Edge gateways collect and forward data from field devices, bridging connectivity gaps in remote installations.
API and queue-based delivery
Ingest from REST APIs, OPC-UA, MQTT, Kafka, file drops, and industrial protocol adapters — whatever the site supports.
Cross-system failure detection
The platform reasons across multiple signal types to identify failure modes that single-domain monitoring misses.
Mechanical signals
Vibration patterns, bearing wear signatures, and rotational anomalies in compressors, pumps, and rotating equipment.
Power signatures
Electrical load patterns, phase imbalances, harmonic distortion, and transient events in motor drives and power systems.
Temperature and pressure
Process conditions, environmental factors, and thermal trends that indicate developing operational issues.
Maintenance and operational history
Work orders, configuration changes, and operational events correlated with sensor data for accurate root cause analysis.
Why evidence matters
In remote operations, operator trust is everything. Evidence-based intelligence makes the difference between action and ignored alerts.
Operator trust
Every alert includes the evidence that produced it. Field operators can evaluate recommendations against their own experience before acting.
Maintenance workflow integration
Evidence packs integrate with existing CMMS and work order systems, providing documented justification for planned interventions.
Defensible interventions
When maintenance decisions need justification — for safety reviews, insurance claims, or regulatory audits — the evidence trail is already built.
Expansion path
Start with a focused pilot, prove value, then expand across the network.
Pilot cluster
Deploy on a critical compressor station or pump group. Validate detection accuracy against known failure signatures and maintenance history.
Site expansion
Extend monitoring across the full site — rotating equipment, electrical systems, environmental sensors — with proven baselines.
Network learning
Cross-site pattern recognition improves predictions as the platform learns from a broader fleet of assets and operating conditions.
Industry guidance
Skip Alvarado — Board Member
Senior-level relationships across oil and gas and advanced nuclear deployment. Deep experience in hydrocarbon-sector operations and energy infrastructure.
Drew Donahoe — Advisory Board Leader
Oil and gas deal diligence, contracts, and transaction risk expertise. Commercial depth strengthening Integrity's positioning in energy-sector engagements.
Review your remote asset monitoring architecture
See how Integrity applies to your specific asset fleet, connectivity constraints, and operational requirements.