Smarter AI Starts with Smarter Evaluation

Get real-time visibility into every interaction with built-in AI performance evaluation. Detect issues, measure accuracy, and resolve problems fast so AI stays on track.

Explore AI Performance

Flexible AI Model Serving

Choose the right AI model for every task. Synoptix AI supports external models, Microsoft-hosted models, and thoroughly custom AI agents from scratch. The platform makes it easy to deploy and test AI models, with full control over how they run across the enterprise.

AI Performance and Efficiency

Monitor key metrics like latency, token usage, and system behavior to understand AI model performance. Get real-time visibility into incoming and outgoing tokens, detect issues early, and optimise AI outputs for reliable performance.

User Feedback and Interactions

Monitor how the AI model performs and how users respond to it. From response speed to user behavior and feedback, get a clear view of what is working and where improvements are needed.

Find and Fix Issues Faster

Monitor the quality of AI's responses using key metrics to check if answers are accurate, relevant, and aligned with the user's data. Stay ahead of issues like hallucinations by keeping a close eye on groundedness and similarity scores.

Actionable AI Monitoring for Enterprise Performance

AI performance evaluation should not be a black box. Track, measure, and optimize key insights in real time to ensure every response is fast, accurate, and aligned with expectations.

•Query Count: Track the total number of processed requests in real time. Gain visibility into AI workload and system efficiency.

•Response Time: Measure how fast AI processes and delivers responses. Identify and eliminate latency issues for seamless AI performance.

•User Feedback: Monitor approval and rejection rates from real users. Understand AI effectiveness and refine outputs for better engagement.

•Accuracy Score: Evaluate how well AI-generated responses align with expectations. Ensure precision, relevance, and reliability in every interaction with ongoing AI evaluation.

AI performance evaluation should not be a black box. Track, measure, and optimize key insights in real time to ensure every response is fast, accurate, and aligned with expectations.

•Query Count: Track the total number of processed requests in real time. Gain visibility into AI workload and system efficiency.

•Response Time: Measure how fast AI processes and delivers responses. Identify and eliminate latency issues for seamless AI performance.

•User Feedback: Monitor approval and rejection rates from real users. Understand AI effectiveness and refine outputs for better engagement.

•Accuracy Score: Evaluate how well AI-generated responses align with expectations. Ensure precision, relevance, and reliability in every interaction with ongoing AI evaluation.

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