AI Observability, Monitoring and Evaluation Tools
Shipping an AI feature is the easy part. Knowing whether it still works next month is harder. These products give your team that visibility. They trace agent steps, log workflows, test quality before changes go live, and track usage and spend by team. When something drifts or breaks, you find out from a dashboard, not from a customer.
Products in this category
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Observability & EvaluationAI Agent Monitoring Platform
Monitors agent health, failures and drift in production.
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Observability & EvaluationAI Agent Observability
Traces every agent step, tool call and outcome for debugging.
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Observability & EvaluationAI Evaluation System
Builds test sets and automated evaluations for your AI features.
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Observability & EvaluationAI Model Evaluation Platform
Runs ongoing evaluations across models and prompts with regression alerts.
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Observability & EvaluationAI Model Performance Dashboard
Compares model quality, latency and cost across workflows.
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Observability & Evaluation
AI Usage Monitoring Platform
Tracks AI usage by team, workflow and model.
What goes wrong without observability?
AI systems fail quietly. A prompt change lowers answer quality. A model update slows responses. An agent calls the wrong tool and nobody notices until a complaint arrives. Costs creep up in one workflow while everyone watches another. Without logs, traces and tests, your engineers end up guessing. These products replace guessing with evidence.
- Quality drops after prompt or model changes
- Agent failures with no trace of what happened
- Rising AI spend with no clear owner
- No way to compare models on quality, speed and cost
Which products should you combine?
Start with visibility. AI Agent Logging adds structured logs to existing AI workflows, and AI Agent Observability traces every agent step, tool call and outcome for debugging. The AI Agent Monitoring Platform watches health, failures and drift in production. Together they tell you what happened and when, which is the foundation for everything else.
Then add quality checks. The AI Evaluation System builds test sets and automated evaluations for your features. The AI Model Evaluation Platform runs ongoing evaluations across models and prompts with regression alerts, and the AI Model Performance Dashboard compares quality, latency and cost. For budgets, AI Cost Monitoring alerts on spend, and the AI Usage Monitoring Platform tracks use by team, workflow and model.
Questions buyers ask
Do we need to rebuild our AI features to use these?
No. AI Agent Logging is built to add structured logging to AI workflows you already run, and the monitoring products work alongside them. The Scope Card lists what each product needs from your setup, such as access to logs or model providers, so your engineers can confirm the fit before ordering.
What is the difference between evaluation and monitoring?
Evaluation checks quality on purpose, using test sets before or after a change. The AI Evaluation System and AI Model Evaluation Platform do this. Monitoring watches what happens in production, such as failures, drift and spend. The AI Agent Monitoring Platform and AI Cost Monitoring cover that side. Most teams want both.
Where do the logs and traces live?
In your own accounts. Every Upmark Labs product runs inside infrastructure you control, so traces, evaluation results and cost data stay with you. The Scope Card spells out what is captured and where it is stored, which helps if your security team has rules about AI inputs and outputs.
Choosing between Observability & Evaluation products?
Tick Compare on up to four products to see scope, price and delivery side by side. If you would rather talk it through, an expert can help you pick the one that fits how you work.