LLM Prompt Evaluation Interface

Overview

Built 0-to-1 internal GenAI tool enabling non-technical risk analysts to test and refine LLM prompts, with ethics dashboard surfacing fairness gaps and drift indicators for regulatory compliance.

The Challenge

Risk analysts needed GenAI capabilities but lacked technical skills to work with LLM APIs. No tooling existed for non-technical users to test prompts, evaluate outputs, or ensure compliance with fairness and explainability requirements before production deployment.

The Approach

Led 0-to-1 development starting with risk analyst workflow study identifying prompt testing and compliance validation as key bottlenecks. Partnered with data science and legal to define requirements for non-technical interface. Designed UX enabling prompt composition, test case management, and output evaluation without coding. Integrated OpenAI/GPT APIs behind intuitive interface. Built ethics dashboard automatically analyzing outputs for fairness indicators, bias detection, and drift from expected patterns. Implemented version control for prompt iterations and A/B comparison views. Created compliance reporting features documenting evaluation process for audit trails.

Key Outcomes

• Enabled non-technical risk analysts to test and refine LLM prompts independently
• Built ethics flagging dashboard surfacing fairness gaps and drift indicators
• Integrated with OpenAI/GPT APIs for production prompt evaluation
• Achieved 100% compliance through built-in explainability features
• Reduced prompt iteration cycles from days to hours through self-service access

The Result

LLM Prompt Evaluation Interface democratized GenAI access, enabling risk analysts to iterate on prompts independently without data science bottleneck. Ethics dashboard ensured regulatory compliance through automated fairness monitoring. Self-service access reduced prompt iteration cycles from days to hours, accelerating GenAI adoption while maintaining governance standards.