DATUMO Eval · Pre-register

See where your AI agent actually fails.

Upload your logs and know in 5 minutes, before your users do.

DATUMO Eval hero card

DATUMO Eval

Got logs?
You’re halfway to knowing where your AI agent fails.

No complex setup. No evaluation criteria to build. See the result in just 4 steps.

1. Upload logs (you)→2–4. Criteria · Scoring · Report (automatic)
1
You
Upload logs
2
Auto
Auto-generated criteria
3
Auto
Automatic scoring
4
Auto
Why it failed + how to fix
The only step you take
Drag and drop
your chat log file
Chatbot logs · live chat transcripts
service policies, and more
CSVXLSX
chatbot_logs_oct.csv940 rows
Score by areaCritical 0
Handoff judgment
0.64
Refund & exchange policy
0.71
Order & shipping accuracy
0.81
Failure reason Kept responding without handoff after legal threats
Suggested fix Add “report / lawyer / lawsuit” as handoff triggers to route to a human agent immediately
Actual product · from log upload to results
Product walkthrough · sample data

Your AI agent can be running fine,
and still be wrong.

Catch the failures that both monitoring and generic benchmarks miss.

Online store AI chatbot
Q. Can you recommend a fridge for a family of four?
A. I recommend Brand B’s OO side-by-side refrigerator.
Competitor product recommended
Mobile carrier AI chatbot
Q. I still have time left on my contract. Is there a cancellation fee if I cancel now?
A. There is no cancellation fee.
MisinformationCancellation fee charged
Internal knowledge AI
Q. Did the meal allowance amount change?
A. It’s $150 per month.
MisinformationPolicy update not reflected
※ Limits of traditional monitoring
Generic evaluation limits·Operational resource burden·No direct path to improvement
Example conversations · fictional cases, not related to any real company or product

Just a few clicks

See how AI agent gets evaluated

Pick a sample to see the full flow, from criteria generation to error analysis and improvement suggestions.

Sample demo

Pick a sample and run an evaluation

Same flow as the real product, using sample conversation logs

Questions you can finally answer

AI Product & Operations
  • Q“Is our chatbot following our policies?”
  • Q“What’s the riskiest area before launch?”
AI / ML Engineering
  • Q“What should we fix in the prompt first?”
  • Q“Are failures clustered in specific cases?”
QA & Evaluation
  • Q“Where do we even start with eval criteria?”
  • Q“What is our current checklist missing?”
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Frequently asked questions

What is AI agent evaluation?

It means scoring the conversations your AI chatbot had with customers against clear criteria to find where it goes wrong. Monitoring tells you whether it answered; evaluation tells you whether it answered correctly.

What data do I need?

Just one conversation log file from your chatbot.

  • Format: CSV or XLSX
  • Columns: 2 — User Input (customer message) and Application Output (AI response)
  • Volume: 50–500 rows
  • Personal data (names, phone numbers, addresses, order numbers) masked

A mix of good and poor answers gives more accurate results. Add your service policies — like refund rules or human-handoff criteria (optional, up to 2,000 characters) — and the criteria will reflect your own rules.

Can I try it without logs?

Yes. The sample demo on this page walks you through the full flow.

What if formatting my logs is hard?

Click Copy on the upload screen to copy the upload requirements and an example. Paste it into any AI assistant to generate logs in the right format. When you upload, we instantly check for issues like empty or duplicate columns and too few rows.

Do I need to sign up?

Not for your first evaluation. Sign up to save results and run repeat evaluations — your criteria and results carry over.

How is my uploaded data handled?

Uploaded conversation logs are stored and processed to run evaluations, deliver results and improve service quality. See our Privacy Policy and Terms of Service for details.