Expose Data Failures Before They Break Decisions
Monitor data in real time, detect issues early, and keep analytics, AI, and operations running on trusted data
A Typical Data Incident Timeline
Data pipeline runs
Schema changes upstream
Events arrive late
Dashboard numbers drift
Business flags inconsistency
What Teams Actually Miss
- Arrival timing changes
- Partial delivery
- Distribution shifts
- Silent field drops
How Expanso Interrupts the Timeline
Incidents get shorter because discovery happens earlier
Detects freshness, volume, and schema drift in real time
Flags anomalies before dashboards update
Preserves source and timing context automatically
Pinpoints where behavior changed, not just that it did
Outcomes From Your Data Observability Platform
Real impact across analytics, AI, and operational systems
Faster detection of data failures across pipelines and streams
Reduction in time spent debugging data incidents
Data reliability for analytics, AI, and operational systems
Fewer downstream outages caused by broken or delayed data
Real-World Impact
See how leading organizations achieve data observability at scale
When 150 ms Is Too Slow
A major North American sports league lacked visibility into real-time player tracking pipelines. Silent data delays caused live graphics to lag behind gameplay. Expanso monitored data streams locally at each stadium, detecting latency and data loss immediately.
12 Million Events, 4 Analysts
A European OEM struggled to observe telemetry quality across 2.3 M connected vehicles. Data noise masked real security threats. Expanso monitored telemetry at the source, detecting anomalies and validating events before alerts reached the VSOC.
Turning 14.3 TB of Logs Into Trustworthy Signals
A top-25 US regional bank lacked visibility into log quality. Noisy data overwhelmed Splunk, and real issues surfaced late. Expanso monitored logs upstream, flagging anomalies, masking sensitive fields, and validating structure before ingestion.
Their AWS Bill Hid the Real Problem
A forestry company processed 2.7 TB/day of drone imagery without visibility into pipeline health. Failures were discovered days later. Expanso monitored extraction and processing locally, detecting data gaps and delays before cloud transfer.
Why Expanso
Observe anywhere
Cloud, on-prem, edge, and hybrid environments
Works with your stack
Integrates with existing tools without lock-in
Policy-driven monitoring
Rules replace manual checks. Observability scales without complexity
Built for real systems
From dozens to thousands of pipelines without increasing team size
Frequently Asked Questions
What is a Data Observability and Monitoring Platform?
It provides real-time visibility into data pipelines, streams, and quality, detecting failures and anomalies before they impact analytics or operations.
How is this different from logging or metrics tools?
Expanso observes data behavior itself—volume, structure, freshness, and validity—not just infrastructure signals.
Can Expanso detect silent data failures?
Yes. Schema drift, missing data, late arrivals, and partial failures are detected upstream in real time.
Where does Expanso run?
SaaS, on-prem, edge, or hybrid—with consistent observability and policies everywhere.
Does this replace my existing monitoring tools?
No. Expanso complements them by covering data-specific failures traditional monitoring misses.
Start observing your data
Reliable decisions depend on visible data.