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Improving Model Readiness and Release Confidence with Repeatable AI Validation Workflows

At a glance

  • Client
Global Product Company
  • Industry
Software & HiTech
  • Solution Provided
AI Feature Validation, LLM Testing & Evaluation
  • Technologies Used
Construct™:Synthesize, Construct™: Verdict, YAML-based test scripting, LLM-as-a-Judge, visualization dashboards
The Challenge

As the client integrated generative AI features into its platform, its QA and product teams faced mounting validation challenges:

  • LLM-generated outputs became increasingly open-ended and context-sensitive, making traditional test cases ineffective
  • The team lacked a consistent, trusted dataset to evaluate model performance across varied user intents, edge cases, and prompt structures
  • Manual validation was time-consuming, inconsistent, and subjective—leaving teams without confidence to release or improve AI-driven functionality
The Solution

To bring clarity, repeatability, and metrics to GenAI validation, Gorilla Logic deployed two purpose-built AI workflows: *Construct™: Synthesize and Construct™: Verdict.

Key solution components included:

  • Golden Dataset Generation: Construct™: Synthesize blended ground truth answers with model-generated variations to create scalable reference datasets for evaluation
  • Automated Output Scoring: Construct™: Verdict used YAML-based test definitions and an embedded LLM-as-a-Judge to score model outputs across standard QA and SME-defined metrics
  • Dashboards for Decision-Making: Verdict’s built-in visualization engine provided rich dashboards to track behavior, highlight risk areas, and align product and QA on readiness

The Results

Faster Evaluation Cycles: Reduced AI feature validation timelines from weeks to days with automated, repeatable testing
Smarter Model Selection: Enabled precise, data-backed comparisons of model performance and prompt strategies
Higher Release Confidence: Surfaced hallucinations, inconsistencies, and low-quality responses before deployment
Product-QA Alignment: Delivered a shared view of performance and coverage to inform go/no-go decisions and continuous improvement

*Gorilla Logic Construct™ is how we deliver faster—with less engineering lift and greater confidence.

It’s not a product. It’s our portfolio of delivery-tested workflows, powered by modular AI agents. Every workflow is proven in delivery, reusable by design, and capable of cutting engineering work by 30-80%.
Construct™: Synthesize is our test data generation accelerator—built to create synthetic datasets to evaluate AI-infused products against trusted, ground-truth benchmarks.
Construct™: Verdict is our AI feature validation accelerator—built to enable metrics-based evaluation and iterative visualization of AI-infused product quality.