Based on Gartner Framework

Bad Data In, Bad AI Out

You're paying to move, store, and process garbage. What if you fixed it before it left the source?

The Three Pillars of AI-Ready Data

Gartner's framework defines three continuous processes. Expanso implements all three at the source.

Add context, meaning, and lineage at creation. Stop reverse-engineering what fields mean.

Validate schemas, detect anomalies, filter bad data before it moves. Invalid records go to dead-letter queues.

Enforce compliance at origination. PII masking, data sovereignty, regulatory requirements - automated.

By the time data reaches your warehouse, you've already paid to move and store it. If it's bad, you pay again to clean it.

Quality issues, missing context, compliance violations - fixed before data moves.

Problems caught at origin

Filter noise, duplicates, invalid data before it hits Snowflake, Databricks, or Splunk.

Lower platform costs

Data sovereignty, PII masking, regulatory requirements - enforced automatically.

Automated enforcement

Clean, contextualized data available immediately. No overnight batch jobs.

Sub-second latency

Sensor data across distributed naval assets with strict compliance.

Real-time data from thousands of IoT sensors and cameras.

GDPR, HIPAA, CCPA, data sovereignty enforced at origin.

Reduce Splunk and warehouse costs by filtering at the edge.

Alignment, Qualification, Governance - at the source where data is created.