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Evaluation · Run evals on your assistant chat logs

Measure quality from
real conversations

Run evaluations directly on your assistants' chat logs. Score responses for accuracy, faithfulness, and hallucination rate to understand how your AI assistant is actually performing in the wild.

Ejento — Evaluation Runs
5 assistants · last run 4 min ago
Eval Sets 12
Avg Accuracy 87.8%
Avg Faithfulness 90.3%
Assistant Eval Set Accuracy Faithfulness Hallucinations Result
SA Sales Analyst
Sales QA v2 94.2% 96.1% 3 / 200 Pass
HR HR Assistant
Policy QA 88.7% 91.3% 8 / 180 Pass
LG Legal Advisor
Contract QA 79.4% 82% 14 / 150 Fail
SB Support Bot
Support QA v3 91.1% 93.7% 6 / 220 Pass
FA Finance Agent
Finance QA 85.6% 88.2% 11 / 160 Fail

Catch regressions before your users do

Ejento runs a full evaluation suite on every deploy. You always know if a model swap or prompt change hurt quality before it reaches your users.

Quality Scores Sales Analyst · last run
Accuracy 94.2%
Faithfulness 96.1%
Relevance 91.7%
All metrics above threshold — passed

Faithfulness Scoring

Score every response against your knowledge base — accuracy, faithfulness, and relevance in one view.

Hallucination Rate −75% vs 6mo ago
8 %

Hallucination Detection

Track hallucination rates over time and get alerted before they spike above your threshold.

Regression Detected GPT-4o swap · 3h ago
Accuracy dropped 14.8 pp after model swap. Deploy blocked.
Accuracy
94.2% 79.4%
Faithfulness
96.1% 80.7%
Hallucinations
1.5% 7.2%

Regression Alerts

Automatic before/after comparison on every model swap or prompt update. Deploy with confidence.

Metric Claude 3.5 GPT-4o
Accuracy 94.2% ✓ 91.7%
Faithfulness 96.1% ✓ 93.4%
Hallucinations 2.1% ✓ 3.8%
Avg Latency 1.2s 0.9s ✓
Cost / 1k tok $0.003 ✓ $0.005
Claude 3.5 Sonnet wins 4 / 5 metrics

A/B Model Testing

Run two LLMs side-by-side on the same eval set and pick the winner on your own metrics.

Human Feedback Loop

Capture thumbs up/down from users and surface low-rated responses for review and retraining.

Ready to measure quality?

Run evaluations against your live assistants and surface regressions before your users do.