Make Production Decisions Without Second-Guessing the Data
Bad data drives unnecessary shutdowns, wasted investigations, and rising operational risk. Expanso validates production telemetry at the source, so your analytics reflect what's actually happening in the field.
No infrastructure replacement. No system overhaul. Works alongside your historian and SCADA.
False signals cost more than real failures
Duplicated telemetry, ingestion lag, and schema drift don't just add noise - they drive unnecessary shutdowns on equipment that's running fine, and mask failures that are actually developing.
5-20% of production telemetry is duplicated during retries
When a wellhead sensor retransmits data after a network hiccup, those duplicate readings enter your historian and get consumed by analytics as if they were independent observations. Pressure trends spike. Flow baselines shift. Your team investigates equipment that never had a problem.
Seconds of ingestion lag distort time-series analytics
Batch data that arrives late shifts your time-series baselines. Real events look like false alarms and genuine anomalies get buried in the noise.
Schema changes break analytics without warning
When field equipment firmware updates change data formats, your historian stores the readings but your dashboards stop making sense. Teams discover the problem days later.
Storage costs rising 30-50% year over year
Raw, unfiltered telemetry floods centralized platforms with duplicate and redundant data. You're paying to store noise that should have been filtered at the source.
Production data integrity, enforced before ingestion
Expanso validates every wellhead reading, pipeline SCADA signal, and refinery process stream at the source. Your historian and analytics only receive data that passes validation.
What we validate
Sample completeness - every wellhead reading in the window is accounted for
Duplicate suppression - retransmitted readings stripped before ingestion
Timestamp accuracy - sequence and timing validated against physical constraints
Schema enforcement - field data structure verified against expected formats
What your systems receive
Complete data windows with no gaps or dropped samples
Deduplicated streams that reflect actual production behavior
Time-consistent records that align with physical process timelines
Schema alerts that arrive before broken data reaches your dashboards
Large-Scale Deployment
14,847 distributed endpoints. 4.7 PB/month. $4.3M quoted for analytics.
A major U.S. deployment across 14,847 endpoints validated Expanso's approach to edge-first data integrity. Processing moved to points of presence, raw data stayed local, and only metadata and flagged events flowed upstream.
"Isn't this what our data platform already does?"
Your data platform aggregates and stores production telemetry from across your operations. That's what it was built to do. But it doesn't verify that the data reaching it is complete, time-consistent, or free of duplicates.
Expanso validates at the source before ingestion. Your platform stays exactly where it is - the difference is it now runs on inputs you can trust.
Built for oil & gas operations
Vendor-agnostic across all major OT/IT systems
Supports upstream, midstream, and downstream operations
Deploys site by site without disruption to production
No changes to existing production systems required
Why teams deploy Expanso
Runs at the field edge, not in the cloud
Doesn't replace production systems - makes them reliable
Reduces storage costs by eliminating redundant data
Scales across distributed assets globally
If the production data isn't clean, the shutdown decision isn't safe
Validate at the source. Operate with confidence.