Watch Your Agent Pass or Fail — As It Happens
Every response scored on four dimensions. Results stream in real time. The rubric is fully transparent — you see exactly why each score was given.
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Every Response, Four Lenses
Each dimension targets a different failure mode. Weights reflect what matters most in production deployments.
Conversation Quality
Clarity, empathy, de-escalation, tone consistency, and appropriate escalation across multi-turn conversations.
Tool Usage Accuracy
Correct API calls, accurate data retrieval, proper record creation, and integration reliability.
Output Quality
Factual accuracy, completeness, actionable guidance, proper citations, and clear formatting.
Diagnostic Accuracy
Problem identification, prioritization, honesty about uncertainty, and resistance to hallucination.
What Scores Mean
At-a-glance production readiness from 0 to 100. Every score maps to a clear deployment recommendation.
Not safe for production. Critical failures in accuracy, compliance, or safety. Do not deploy.
Significant gaps. Handles basics but fails edge cases and compliance scenarios. Fix with training assets.
Handles most scenarios correctly. Safe to deploy with monitoring and defined escalation paths.
Handles edge cases well. Stays honest about limitations. Production ready with minimal oversight.
Rare. Robust guardrails, consistent quality across all scenario types. Thoroughly trained and hardened.
No Black Box
For every scenario you see which criteria were met, which failure indicators triggered, and the exact turn where issues occurred.
Criteria Defined First
Success criteria and failure indicators are set before the test runs. No post-hoc judgment — the rubric is fixed before your agent sees the scenario.
Per-Turn Analysis
Each conversation turn is analyzed individually. You see exactly where the agent went wrong — not just a final score.
Ground Truth Comparison
See what a perfect agent would have said, side by side with what yours actually said. The answer key ships with every evaluation.
Frequently asked questions
How is the readiness score calculated?
The readiness score (0-100) is a weighted average of four dimensions: Conversation Quality (40%), Tool Usage Accuracy (20%), Output Quality (20%), and Diagnostic Accuracy (20%). Each dimension is scored per-scenario based on predefined success criteria and failure indicators.
What is a good readiness score?
Below 50 means critical failures — not safe for production. 50-69 means significant gaps requiring targeted fixes. 70-84 is production-capable with known limitations. 85-94 is a strong performer handling edge cases well. 95-100 is exceptional and rare, indicating thorough training and robust guardrails.
Can I see why each score was given?
Yes. The rubric is fully transparent. For every scenario, you see which success criteria were met, which failure indicators were triggered, and the exact conversation turn where issues occurred. You also see the ground-truth response showing what the agent should have said.
How does scoring work for agent-type scenarios?
Agent scenarios (tool usage, API calls, data retrieval) are scored on whether the agent took the correct actions in the correct order. Did it call the right API? Did it retrieve the right data? Did it create the correct record? Tool Usage Accuracy captures this dimension.
Can I export the readiness report?
Yes. The readiness report is exportable as PDF for sharing with your team, stakeholders, or compliance reviewers. Deep Eval also includes exportable training assets as a ZIP file.
See Your Agent's Score
Connect your agent and get a readiness score in under 2 minutes. Free discovery always included.
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