How University of Montana Is Accelerating Reporting with Edify and AI
University of Montana's partnership with Edify
The University of Montana (UMT) initially partnered with Edify, EAB’s higher ed data management platform, in 2020 to establish a governed data foundation across reporting, analytics, and institutional decision-making. Now, UMT is testing a “bring your own AI” model where a Claude AI assistant is built on Edify to accelerate trusted ad hoc reporting.
Opportunity
UMT’s IR and IT teams faced growing demand for fast answers to ad hoc data questions, but report-building often required SQL expertise, campus-specific definitions, and multiple rounds of human validation.
Solution
UMT connected Claude to Edify’s governed data foundation, including documentation, metadata, higher ed data model, and reporting APIs, so Claude can draft SQL, interrogate Edify data, and publish reports from natural-language prompts.
Impact
UMT expects the pilot to move governed first-draft report creation from weeks to hours, giving IR and data teams more capacity to support one-off questions.
“We want to enable our Institutional Research office and also empower users that may not be native SQL developers to have a conversation with the data.”
Corey Cardoza
Enterprise & Strategic Technology, University of Montana
The Value of Edify
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Faster First Drafts
Expected to reduce report-building time from weeks to hours and help teams quickly move from request to usable starting point.
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Report-Ready AI Output
Turns natural-language questions into draft SQL and reports that can be published directly within Edify.
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Validation Built Into the Workflow
Generates validator queries alongside draft reports so humans can review logic before outputs are shared.
How Claude and Edify Work Together
AI
Reporting
AI Tool and Experimentation
Claude expertise, agentic AI/MCP exploration, and campus-led innovation.
Governed Data Foundation
Trusted institutional data structures, definitions, and reporting context.
Real Reporting Questions
High-value ad hoc questions from IR, IT, and functional users.
Metadata, Documentation, and APIs
The context Claude needs to draft stronger SQL and reports.
Natural-Language Interface
A conversational way for non-SQL users to engage with institutional data.
Publishing and Validation Workflow
Reports can be created in Edify with human review and validator queries.
“Bring Your Own AI” in Action
Ask
User enters a plain-English reporting question into Claude
Ground
Claude references Edify documentation, Quad structures, metadata, and business context
Build
Claude interrogates Edify data, drafts SQL, and checks logic
Publish & Validate
Claude publishes the report to Edify and can generate a validator query
Ready to learn more?
Find out what your institution can do with trusted, accessible data.