Most quality programmes run for months and fix the wrong things first. Thousands of issues, no ranking, no owner. Meanwhile every AI initiative you launch inherits the same vague definitions and broken data, and quietly amplifies them.
Metagem turns that into a short list of findings with evidence attached — like the ones surfaced in a live deployment.
3 new insights
Customer domain
Sales is chasing 30 open deals on products not in stock.
Evidence: 30 Salesforce opportunities tied to SKUs with 0 ERP inventory and no inbound PO.
'Active customer' has four contradicting definitions across systems.
Evidence: ERP, CRM, Billing, BI each use a different rule. 11% population delta.
ERP and CRM customer reporting diverges for 21,000 customers.
Evidence: Monthly active customer count differs by 14% between SAP and Salesforce.
Step 1
The Context Engine reads your systems and documentation, and builds a map of what things mean and where the physical data lives.
Step 2
We look for gaps, inconsistencies and conflicts. Every broken rule becomes a finding with evidence attached, ranked by business impact and what it costs you.
Step 3
Your experts get an overview of the highest-priority findings and concrete steps to fix them.
Clear priorities from week one.
Drafted from your systems and documents, not a generic best-practice list.
Each one weighed by business cost, with the evidence that proves it.
Who fixes what, in which system, and in what order.
A finding closes on a passing check, never on a status update.
Common questions about auditing data quality.
We run a scoped audit on one domain and walk through the findings with you.
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