Run your test cases against every prompt and model change. PromptLens compares the candidate to your baseline and shows exactly which cases broke — and why.
Support triage release check
Baseline v16 vs candidate v17 · 50 cases · same model, same dataset
Regression detected
11 cases passed the baseline but fail the candidate.
Prompt changes · v16 → v17
model gpt-5.4 · temperature 0.2 · unchanged
Cases that flipped · pass → fail
"The checkout page is down and we are losing orders every minute."
urgent ✓technical ✗
JudgeMissed the urgency signal on a production outage with revenue loss.
"I was charged twice and my card closes tomorrow."
urgent ✓billing ✗
JudgeDouble charge with deadline pressure should escalate as urgent.
"Can you send me the invoice for last month?"
billing ✓The message is about billing. ✗
JudgeReturned prose instead of the required single lowercase category.
Recommendation: Block the release. Restore the escalation rule in v17, then rerun the suite.
Start with a demo preset, then run release checks across the model providers your organization approves.
Compare a candidate AI change against a known-good baseline. PromptLens shows what got worse, what likely changed, and whether to ship, block, rollback, or rerun.
Decision ledger
Catch a quality drop
See what changed
Share the release decision
Next step: ship, block, rollback, or rerun.
The shared report keeps failed examples, score shifts, and the recommendation attached to the decision.
A regression report only earns trust when raw output, score shifts, failure reasons, likely causes, and the recommendation stay attached to the same run.
What the report carries
Every output stays beside the prompt version, dataset row, scorer, score, and run metadata.
PromptLens shows which AI changes fall below the release bar before they reach production.
See exactly which cases passed the baseline but fail the candidate, with the judge's reason for each, next to the prompt diff.
Send one report URL to a teammate, stakeholder, or PR with the conclusion attached.
Team evaluations use approved provider access instead of personal scripts or hidden shared keys.
Every plan includes evaluations with LLM judge scoring, baseline comparisons, and unlimited shared regression reports. Live runs use encrypted organization provider keys so model choice and spend stay under your control.
Choose by volume
Plans scale by projects, daily evaluation runs, dataset size, and provider controls.
Run real regression checks today. No card, no setup, no provider keys required.
Bigger test suites, more projects, and higher daily volume for weekly AI releases.
Higher volume, organization provider keys, and a security review for your team.
Projects
Prompts
Evaluation runs
Test cases per dataset
Playground calls
LLM judge scoring
Shared report links
Model access
Support
Billing note
Live evaluations use your organization's provider keys. PromptLens records provider-reported or estimated usage so every comparison shows quality, latency, and model cost.
Common questions about PromptLens and how it compares to the tools you're already using.
Compare a candidate against a known-good baseline and share the evidence behind the release decision.
Run your test cases against every prompt and model change. PromptLens compares the candidate to your baseline and shows exactly which cases broke — and why.
Support triage release check
Baseline v16 vs candidate v17 · 50 cases · same model, same dataset
Regression detected
11 cases passed the baseline but fail the candidate.
Prompt changes · v16 → v17
model gpt-5.4 · temperature 0.2 · unchanged
Cases that flipped · pass → fail
"The checkout page is down and we are losing orders every minute."
urgent ✓technical ✗
JudgeMissed the urgency signal on a production outage with revenue loss.
"I was charged twice and my card closes tomorrow."
urgent ✓billing ✗
JudgeDouble charge with deadline pressure should escalate as urgent.
"Can you send me the invoice for last month?"
billing ✓The message is about billing. ✗
JudgeReturned prose instead of the required single lowercase category.
Recommendation: Block the release. Restore the escalation rule in v17, then rerun the suite.
Start with a demo preset, then run release checks across the model providers your organization approves.
Compare a candidate AI change against a known-good baseline. PromptLens shows what got worse, what likely changed, and whether to ship, block, rollback, or rerun.
Decision ledger
Catch a quality drop
See what changed
Share the release decision
Next step: ship, block, rollback, or rerun.
The shared report keeps failed examples, score shifts, and the recommendation attached to the decision.
A regression report only earns trust when raw output, score shifts, failure reasons, likely causes, and the recommendation stay attached to the same run.
What the report carries
Every output stays beside the prompt version, dataset row, scorer, score, and run metadata.
PromptLens shows which AI changes fall below the release bar before they reach production.
See exactly which cases passed the baseline but fail the candidate, with the judge's reason for each, next to the prompt diff.
Send one report URL to a teammate, stakeholder, or PR with the conclusion attached.
Team evaluations use approved provider access instead of personal scripts or hidden shared keys.
Every plan includes evaluations with LLM judge scoring, baseline comparisons, and unlimited shared regression reports. Live runs use encrypted organization provider keys so model choice and spend stay under your control.
Choose by volume
Plans scale by projects, daily evaluation runs, dataset size, and provider controls.
Run real regression checks today. No card, no setup, no provider keys required.
Bigger test suites, more projects, and higher daily volume for weekly AI releases.
Higher volume, organization provider keys, and a security review for your team.
Projects
Prompts
Evaluation runs
Test cases per dataset
Playground calls
LLM judge scoring
Shared report links
Model access
Support
Billing note
Live evaluations use your organization's provider keys. PromptLens records provider-reported or estimated usage so every comparison shows quality, latency, and model cost.
Common questions about PromptLens and how it compares to the tools you're already using.
Compare a candidate against a known-good baseline and share the evidence behind the release decision.