Build trusted customer context into the stack you already run
Resolve complex customer identity, connect historical and current data, and deliver governed customer context across analytics, applications, and AI, without rebuilding the data architecture you already run.
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Build for the questions every customer decision depends on
Can every system recognize the same customer?
When each pipeline and application resolves identity differently, analytics, activation, service, and AI can act on different versions of the same person. Amperity resolves identity across online and offline sources and makes that customer identity reusable across the stack.
Is the context current enough for this decision?
Not every workload needs the same latency. Connect historical customer data with current events, profile access, warehouse sharing, and scheduled workflows so each decision receives the freshness it requires.
Can we explain why this context should be trusted?
Teams can inspect source connectivity, match categories, pairwise connections, clusters, lineage, and changes between identity runs. Permissions, consent, provenance, and intended use stay connected to the customer context people and systems consume.
Can teams act without creating another engineering backlog?
Technology defines the identity foundation, access model, and approved delivery patterns. Authorized business teams can use governed profiles, attributes, segments, and workflows without rebuilding the underlying logic or bypassing control.
Customer-data complexity should not become permanent infrastructure debt
Customer identity is often recreated inside pipelines, dashboards, activation tools, applications, and AI projects. Historical behavior lives apart from current signals. Governance is applied after data moves. Each new use case adds another definition to reconcile and another workflow to maintain. The result is slower delivery and less confidence in the customer decisions the business is trying to improve.
Work with your architecture, not around it
Amperity supports integration patterns for Snowflake, Databricks, Google BigQuery, cloud storage, source systems, and destinations that minimize unnecessary data movement. Zero-copy is available for supported workloads and environments, with reduced-copy patterns used where necessary. For supported lakehouse-native workloads, compute runs in your environment and data remains in storage you govern. Real-time and activation workloads remain Amperity-managed.
Create context that stays dependable from signal to action
Connect fragmented records to the right person or household, then combine transactions, events, service activity, loyalty, preferences, and engagement history. Persistent identifiers and transparent identity workflows help teams use, validate, and explain the result.
What changes when customer context becomes shared infrastructure
Customer decisions become more relevant and appropriate
People and systems can interpret a current signal against resolved identity, relationship history, permissions, and business goals before deciding what to do next.
New use cases stop creating new identity debt
Resolve identity upstream and reuse the result. Engineering teams spend less time reproducing joins and more time delivering capabilities the business can use.
Business velocity and technical control reinforce each other
Authorized users can explore, segment, and activate customer data through approved workflows. Technology retains control of identity, lineage, access, and delivery.
AI initiatives gain context they can actually use
Ground models, assistants, and agents in accurate, current, and governed customer context. This helps AI recommendations and actions stay more relevant to the customer and aligned with business rules.
Technology teams building trusted customer context at enterprise scale
Alaska Airlines and Hawaiian Airlines
After the Hawaiian Airlines acquisition, Alaska Airlines unified customer data across Hawaiian's Snowflake and Alaska's Databricks environments in two days: 105 data feeds, 27 destinations, 164M AmpIDs resolved.
Read the customer story
Global retailer
Amperity helped resolve more than one million previously inaccurate profiles and reduced customer-data latency 86%, moving from a seven-day delay to fresh data every day.
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BECU
BECU unified 37 data sources and stitched 297 million records into 4.1 million known members, saving more than 50 hours each week on outbound execution.
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Seattle Seahawks
The Seattle Seahawks uncovered 5,000 previously unidentified fans and achieved a 61.5% deduplication rate across all records.
Read the customer storyQuestions technology leaders ask before they evaluate
Evaluate your customer-context architecture
Map Amperity to your warehouse, identity requirements, latency needs, governance model, and first priority use case with an Amperity solution consultant.
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