Skylv Agent Evaluatorv1.0.2

Before deploying a new conversational AI agent to production, use the evaluator to score its performance across the five dimensions. This ensures the agent meets quality standards and catches issues like poor safety or low accuracy early.

After making changes to an agent's prompts or underlying model, run the evaluator to detect any drops in coherence or adaptability. This helps maintain consistent user experience and quickly identify regressions.

Compare two different agent configurations (e.g., different prompts or models) using the evaluator's objective scores. I can use the results to choose which agent performs better overall or in specific dimensions like safety.

Continuously evaluate a customer support chatbot's interactions to monitor its accuracy in answering queries and its safety in handling sensitive data. This enables proactive improvements and maintains customer trust.

Use the evaluator to assess an internal AI assistant (e.g., for code generation or data analysis) to ensure it remains efficient and coherent as it learns from user feedback. This helps optimize productivity tools.

Offer the evaluator as a subscription-based API or dashboard for other companies to assess their AI agents. Revenue comes from monthly or per-evaluation fees, targeting AI startups and enterprises.

Provide a limited free tier (e.g., 10 evaluations per month) to attract users, then upsell premium features like detailed reports, batch evaluations, or integration with CI/CD pipelines. Revenue from premium subscriptions.

Offer bespoke evaluation services for large clients, including custom dimension weighting, SLAs, and integration into their existing workflows. Revenue from consulting fees and ongoing maintenance contracts.