The information behind one business decision
A question about gross margin can depend on customer pricing, invoices, product costs, and fulfillment. Those details often live in different systems.
Copacati brings the relevant records together while preserving the links back to the original data.
Connected business context
Financial data
Orders, costs, inventory
Customer data
Accounts, pricing, opportunities
Service data
Cases, fulfillment, documents
Source links and data permissions remain available when a team needs to check the result.
Copacati makes JD Edwards data easier to use
JD Edwards holds important financial and operational information, but its codes, dates, and field names often require specialist knowledge. Copacati uses JD Edwards definitions to present that data in terms business users can understand.
The same data can then be analyzed alongside CRM, support, and other operational systems, while retaining a link back to the original JD Edwards records.
See JD Edwards supportAs JD Edwards stores it
ABAT1 · C
115234
ABAN8
As Copacati presents it
Customer type
August 22, 2015
Address number
Questions leaders can answer with connected data
Copacati is most useful when the answer depends on information that currently lives in several systems.
What changed gross margin in a region?
Finance leaders can look across customer pricing, product mix, invoices, costs, and freight to understand what changed and where to investigate next.
Which accounts are buying less than last year?
Sales leaders can compare account activity, orders, opportunities, service history, and product details without waiting for separate reports.
Where are service and cost problems connected?
Operations leaders can connect fulfillment, inventory, support, and financial data to understand the business impact of a recurring issue.
How Copacati tracks an answer back to its data
The diagram shows Salesforce and JD Edwards records moving into an answer that a team can check.
The controls behind reliable answers
Technical teams can govern data access, understand how an answer was produced, and choose how Copacati is deployed.
Multiple Deployment Options
Run Copacati on your own infrastructure for maximum control, or choose our hosted option for a fully managed experience. Either way, your data stays secure, isolated, and under your ownership.
Rapid Implementation
Our goal is four to six weeks from kickoff to production. A structured implementation connects to your existing systems and gets your team running real queries while most vendors are still in discovery.
Built-In Governance
Full audit trails, role-based access controls, and data lineage tracking come standard. Know exactly who asked what, when, and which data sources informed every answer.
Business questions without SQL
People can ask business questions in familiar language while Copacati handles the underlying data work and makes the supporting evidence available.
Cost Transparency
Every AI action is tracked and attributed. See exactly what your AI spend delivers across teams, projects, and use cases. Optimize costs before they surprise you.
Model choice for technical teams
Use OpenAI, Anthropic, Mistral, Google Gemini, or self-hosted models. Technical teams can choose the model that fits the work and change providers as needs evolve.
Talk through the questions your data should answer
We can help identify a focused use case and show what a reliable answer would require.