Turn fragmented retail data into one operating truth.
Ekyam resolves conflicting identities, values and business definitions across retail systems and publishes one governed answer for analytics, AI and agents.
Discuss your Data
Centralized data can still produce conflicting answers.
Works alongside Snowflake, BigQuery, Fabric & Databricks.
Your warehouse remains the analytical store while Ekyam governs operating meaning.
ERP, WMS, OMS and commerce each hold part of the truth.
Ekyam resolves the entity, source authority and operating definition behind one governed answer.
Your ERP remains the system of record
Ekyam reads from operational systems and never writes back without an explicit, approved path.
How Ekyam governs retail data.
Resolve identities, definitions and lineage once.
Reuse the context across BI, AI, agents and workflows.
Deterministic rules, retail attributes and governed AI-assisted matching connect source records to canonical entities.
- Products, SKUs, styles, colors and UPCs
- Vendors, orders, customers, locations and channels
- Confidence thresholds and human review for ambiguous matches
Separate source facts from the rules that define their operational meaning.
- Source authority by entity, field and state
- Governed definitions for available, late, complete and at risk
- Rules for reservations, holds, channel fences and timing, shared across BI and AI
Store the answer with the evidence required to explain it.
- Source systems and records
- Transformation, reconciliation and timestamp
- Ontology rule and approved business definition
Publish retail entities, relationships, rules and provenance through APIs, MCP and governed tools.
- Model-independent context for enterprise AI
- One operating model for dashboards, copilots and agents
- Trusted context for recommendations and workflows
The result is more than cleaner data.
Ekyam creates a shared operational understanding that can be used consistently by people, systems and agents.
REPORTINGConsistent operational answers.
Dashboards and analysts use the same resolved identities and governed definitions, reducing manual reconciliation outside the data platform.
ENTERPRISE AIContext agents can reason from.
AI receives explicit retail relationships, rules and provenance instead of inferring business meaning from disconnected rows and fields.
OPERATIONSA foundation for action.
Teams and agents can move from a trusted answer to an approved workflow without rebuilding the underlying data logic for every use case.
