A large manufacturer needed a faster, more reliable way to assess its business intelligence reporting portfolio ahead of a platform migration. With approximately 125 Tableau and Power BI reports to review, the organization faced a time-intensive discovery effort that could slow planning, increase costs and create risk from incomplete migration insight.
Through our partnership, the manufacturer used an AI-enabled assessment approach to rapidly identify report dependencies, data sources, calculations, integrations and other migration-relevant details. The AI-enabled approach accelerated discovery and synthesis, helping compress what could have been a nine- to ten-week manual assessment into a four-week engagement.
The challenge: Building clarity across a complex reporting landscape
Business intelligence migrations require more than moving reports from one platform to another. Teams need to understand what each report depends on, where its data comes from, how calculations work, where hard-coded values exist and which risks may affect migration decisions.
For this manufacturer, much of that information was spread across Tableau and Power BI assets. A traditional assessment would have required team members to manually open each report, document its structure, review data sources and validate findings across the portfolio.
This created several challenges:
- A lengthy discovery process
- Risk of inconsistent documentation
- Limited visibility into report dependencies
- More effort required to support placement recommendations
- Added complexity around data semantics, governance and context
The client needed a practical way to centralize this information and move faster without losing quality.
Accelerating discovery with agentic AI
The manufacturer partnered with us to conduct a focused business intelligence migration assessment. Our team applied Codex and agentic AI techniques to accelerate discovery and synthesis across the reporting portfolio.
Rather than relying only on manual review, we used AI-enabled methods to extract and organize metadata from Tableau and Power BI assets. The team converted key findings into standardized JSON-based templates, creating a structured evidence repository for sources, calculations, transformations, dependencies and risks.
This repository made the assessment more searchable and reusable. It also allowed the team to query the portfolio more quickly, helping answer questions such as how reports connect to data sources, where dependencies exist and which assets may require additional attention during migration.
Creating a stronger foundation for migration decisions
The assessment gave the client a clearer view of its reporting environment before moving forward with migration planning. By organizing report-level details into a structured format, the team could analyze the broader portfolio and support placement recommendations with stronger evidence.
The approach also helped demonstrate a practical use case for agentic AI. Instead of positioning AI as a broad concept, this work showed how it can reduce manual effort, improve consistency and help teams make faster decisions during complex technology modernization efforts.
Tangible outcomes at a glance
The AI-enabled assessment delivered measurable value for the manufacturer, including:
- Faster assessment: Compressed a likely nine- to 10-week manual assessment into four weeks
- Strong return: Delivered an estimated 125%–150% ROI against the engagement spend
- Better migration insight: Created a reusable evidence repository for sources, calculations, transformations and risks
- Practical AI adoption: Demonstrated how agentic AI can support cost-effective business intelligence migration planning
Reduced cost: Avoided an estimated U.S. $62.5K–$75K in cost
A repeatable path for AI-enabled modernization
The project showed how AI-enabled assessments can help organizations address a common modernization challenge: making sense of fragmented data, reporting logic and business context before migration begins.
For the manufacturer, the work created a clearer path forward. For future initiatives, it also provides a repeatable approach to accelerate discovery, reduce manual review and strengthen confidence in modernization planning.
By combining business intelligence expertise with practical AI delivery, we helped the client move from a complex reporting landscape to a more organized, evidence-based view of its migration needs.
