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Predictive Maintenance

Stop Shutting Down Healthy Equipment Because of Bad Data

Stop drift, delays, and duplicate signals from distorting predictive maintenance.

No infrastructure replacement. No pipeline rewrites.

The Problem

Scenarios That Trigger Unnecessary Shutdowns

Every one of these conversations happens because the data reaching your systems can not be trusted.

Vibration Trend Doubt

"That vibration trend looks off... but before we touch the pump, can someone check if the PLC dropped samples or the historian ingested late?"

With Expanso

Expanso validates every vibration sample at the source, detecting dropped readings and ingestion lag before the data reaches your historian or model.

Pressure Spike Confusion

"Pressure spiked for three minutes. Is that real process drift, or did the controller retransmit and create duplicates upstream?"

With Expanso

Expanso detects duplicate and retransmitted telemetry in real time, suppressing redundant events before they distort pressure trends.

Timestamp Distrust

"I'm not shutting down a line over data that might be out of sequence. Confirm the timestamps before we make that call."

With Expanso

Expanso enforces timestamp and sequence validation at the edge, ensuring telemetry is complete and time-consistent before ingestion.

The Solution

How Expanso Protects Predictive Maintenance

Every integrity gap feeds directly into your models, dashboards, and decisions. Expanso closes those gaps at the source.

The Gap

5-15% duplicate telemetry under retry distorts trends

Expanso Fix

Removes duplicates at source before ingestion

The Gap

Seconds of ingestion lag create false spikes

Expanso Fix

Enforces timestamp accuracy at the edge

The Gap

Batch delays shift models by minutes

Expanso Fix

Detects lag in real time before data enters pipelines

The Gap

Incomplete windows increase false positives

Expanso Fix

Ensures complete data windows before analytics

Real Deployment

14,847 Distributed Endpoints

A major US city deployment validated Expanso's approach to edge-first data integrity at scale.

Before

  • 4.7PB/month centralized
  • 7-day retention limit
  • 3-day investigations
  • $4.3M/month quoted

What Changed

  • Moved validation closer to sources
  • Raw data kept local
  • Only metadata sent upstream

After

  • 47GB metadata + 230GB flagged clips
  • 5-year retention
  • 4-hour investigations
  • Pilot: 8 weeks, Full: 5 months

"Don't We Already Have SCADA and Predictive Analytics?"

Yes, you do. And they work well for what they were designed to do. SCADA visualizes process data. Historians store it. Predictive analytics models consume it.

The problem is what reaches them. None of these systems enforce that the incoming sensor and PLC telemetry is complete, time-consistent, or free of duplicates. They trust the signal. And when the signal is distorted, the output is distorted.

Expanso validates sensor and PLC telemetry before ingestion - detecting drift, duplication, and ingestion lag in real time so your existing systems operate on clean, trustworthy data.

Your SCADA and analytics stay exactly where they are. The difference is, now they run on verified signals.

Built For Energy Infrastructure

  • Works across SCADA, PLCs, and sensor networks
  • Vendor-agnostic - fits any existing stack
  • No disruption to existing operations
  • Deploys incrementally, site by site

Why Deploy Expanso

  • Runs where your assets operate - at the edge
  • Does not replace your analytics - makes them accurate
  • Reduces false maintenance alerts
  • Improves model accuracy across the board
  • Scales across distributed infrastructure

If the Signal Isn't Clean, Neither Is the Decision

Fix the signal. Take control.