From AI Uncertainty to Enterprise Confidence: Building Trustworthy Enterprise AI Through Structured Evaluation

How Insight Global Developed 500 Golden Queries to Improve Enterprise AI Search Performance and Readiness

The Client

A Fortune 100 global technology company providing cloud computing, productivity software, AI, and enterprise technology solutions sought to strengthen the performance and enterprise readiness of its AI-powered search capabilities. As organizations increasingly rely on retrieval-augmented generation (RAG) systems to surface trusted answers from vast amounts of enterprise data, the company needed a more effective way to evaluate how those systems performed in real-world business scenarios.

The Challenge

Enterprise AI is only as effective as the information it retrieves.

The client was focused on improving AI search performance for retrieval-augmented generation use cases involving complex financial datasets, including regulatory filings and large document repositories. While the underlying technology continued to evolve, the organization lacked sufficient visibility into how its search platform performed against realistic enterprise scenarios. This created challenges around accuracy, consistency, reliability, and readiness for broader enterprise adoption.

Like many organizations investing in AI, the client faced a critical challenge: understanding whether their systems could consistently retrieve the right information before those outputs reached users. Without a structured evaluation framework, identifying retrieval gaps, validating search quality, and prioritizing product improvements at scale became increasingly difficult. The organization needed a repeatable approach that would transform AI testing from a tactical exercise into a strategic capability.

The Solution

Insight Global partnered with the client to design and implement a structured evaluation framework for enterprise RAG performance.

Rather than focusing solely on outputs, our team developed a scalable methodology capable of providing consistent, actionable insights to engineering and product teams. The solution centered around golden-query testing, structured evaluation criteria, and feedback mechanisms designed to surface retrieval and relevance gaps before they could impact end users.

To support this effort, Insight Global developed a comprehensive set of enterprise-focused test scenarios built around real-world financial datasets, including 10-K filings and SEC documentation. These queries were intentionally designed to challenge retrieval systems across a variety of use cases, helping uncover opportunities for improvement that traditional testing methods might not identify.

The result was a repeatable evaluation framework capable of systematically measuring search performance, accelerating feedback loops, and strengthening confidence in enterprise AI readiness.

How We Changed the Game

Many organizations view AI evaluation as a one-time validation activity.

Insight Global helped transform it into an ongoing operational capability.

By combining human expertise, structured testing methodologies, and scalable delivery processes, we enabled the client to move beyond isolated testing events and establish a repeatable model for continuous improvement. Instead of relying on anecdotal observations, stakeholders gained a consistent framework for identifying performance gaps, prioritizing enhancements, and informing future development decisions.

This approach helped create a stronger foundation for enterprise AI adoption by introducing a disciplined, repeatable process for evaluating search quality and performance before customer-facing implementations.

Outcomes and Impact

The engagement delivered measurable results while establishing a long-term foundation for AI quality improvement.

Key outcomes included:

• Developed 500 golden queries in three months to evaluate enterprise search performance across realistic business scenarios.
• Tested outputs against large financial document repositories, including 10-K reports and SEC filings.
• Identified actionable retrieval and relevance gaps that could be prioritized by engineering teams.
• Established structured feedback loops to accelerate product-improvement cycles.
• Created a repeatable evaluation framework that strengthened enterprise AI readiness and product confidence.

Most importantly, the client gained greater visibility into how its AI systems performed in real-world conditions, creating a stronger foundation for reliable, scalable, and trustworthy AI experiences.

The Insight Global Difference

It takes both technology and people to create trusted AI.

While many organizations focus exclusively on models, infrastructure, and algorithms, Insight Global understands that successful AI initiatives require the right combination of technology, expertise, governance, and operational rigor.

Our team helped bridge the gap between technical evaluation and business outcomes by creating a framework that enabled stakeholders to understand where performance challenges existed and how they could be addressed. Rather than simply identifying issues, we built a scalable capability for continuous improvement, empowering teams to make more informed decisions and accelerate innovation with confidence.

How We Did It

Evaluation Strategy

We designed a structured framework for evaluating AI search performance against real-world enterprise scenarios, ensuring testing aligned with business requirements and user expectations.

Structured Testing

Insight Global developed and executed a comprehensive golden-query program that provided repeatable and measurable performance testing across complex financial document datasets.

Continuous Feedback

By implementing formal feedback mechanisms, we helped accelerate product-improvement cycles while creating a scalable process for ongoing performance optimization.

Areas of Expertise

• Artificial Intelligence & Generative AI Solutions
• Enterprise AI Readiness, Evaluation, and Validation
• Retrieval-Augmented Generation (RAG) Evaluation and Optimization
• AI Governance and Quality Assurance
• Enterprise Search and Knowledge Systems
• Data Strategy and Content Intelligence
• Product Engineering and Continuous Improvement
• Digital Transformation and Innovation Consulting
• Managed Services and Scalable Delivery Models
• Operational Excellence and Process Optimization
• Human-Centered AI Enablement
• Technology Talent and Consulting Solutions

Our People Approach

At Insight Global, we believe successful AI transformation starts with people.

Technology may power innovation, but people drive outcomes. That’s why we bring together consultants, technical specialists, delivery leaders, and subject matter experts who understand how to translate complex challenges into practical business solutions. Whether we’re helping organizations evaluate AI systems, optimize enterprise platforms, or scale transformation initiatives, our people-first approach ensures every engagement is grounded in expertise, collaboration, and measurable value.

Ready to Elevate Your Business?

Building enterprise AI isn’t just about implementing new technology. It’s about creating systems people can trust, scaling them with confidence, and continuously improving them as business needs evolve.

That’s where Insight Global comes in.

As a people-first partner, we help organizations turn emerging technologies into measurable business outcomes. From AI strategy and evaluation to delivery, optimization, and operational support, we bring together the right expertise, processes, and technology to help organizations move faster while reducing risk.

Whether you’re exploring generative AI, improving customer experiences, modernizing critical business processes, or building a foundation for long-term innovation, our teams help translate complex challenges into practical, scalable solutions.

The result is better technology, stronger business performance, more confident decision-making, and solutions designed to deliver value long after implementation.

Ready to build more trusted, scalable AI solutions? Let’s start the conversation.