Fractional AI x OpenAI Cookbook: Eval Driven System Design - From Prototype to Production

In collaboration with OpenAI, we recently co-authored a cookbook focused on building AI systems with evaluations at the core. The OpenAI Cookbook: Eval Driven System Design - From Prototype to Production highlights a real-world use case: a receipt analysis tool designed to extract structured data reliably from diverse, unstructured inputs.

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Why this matters:

This guide illustrates how to build high-ROI AI systems by making evaluations the foundation of your development process—embedding explicit, objective evaluators at every step of the customer-value journey. It’s how we work at Fractional AI: we believe evals aren’t just a tool, they’re the only way to do professional-grade AI development. Evals enable predictable tuning to your actual business needs, costs, and desired outcomes.

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We use receipt parsing as an example to demonstrate how to:

• Design high-quality evals that flexibly measure real-world performance across different metrics
• Tie those evals to business KPIs, enabling you to quantify ROI from prompt tweaks, model swaps, and system changes
• Drive iteration with evals, turning scores into actionable levers for labeling, prompting, and fine-tuning

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By embedding evaluations into every stage of development, you create a flywheel that transforms iteration from guesswork into a predictable and outcome-driven loop. These methods apply broadly to any AI workflow that must prove its value in production.

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What's in the guide:

The cookbook walks through a complete system—from generating test data to evaluating structured outputs—using a repeatable, eval-driven process. The techniques can be extended to other document-based workflows across industries.

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Explore the full guide here.