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AI Evals built for
Production LLM Quality

Evaluators and datasets regression-test every prompt and model change. Online evals and alerts when production scores drop.

Respan eval view: trace with faithfulness, tone, and format eval scores

Ship the version that scores best.

Score every output against the bar you set, so you know it holds up on a test set and in production, instead of just hoping it does.

Every way to grade an output, in one evaluator

An LLM judge, a deterministic code check, or a human reviewer, composed into one evaluator that turns any output into a single score.

Production traffic

Sampling 2% of 12,480 requests

support_replies· 240 rows
{ "ques": "refund the duplicate charge" }Refund issued to card ending 4242
{ "ques": "cancel my subscription" }Downgraded to the Free plan
{ "ques": "where's my order #4021?" }Shipped Monday, arriving Tuesday

Test cases sampled straight from production

Pull real requests from your logs by filter and sampling rate, or upload a CSV, so every case is one your users actually sent.

support_agent· d7b2e94

See which version scores better, before you ship

Run a model or prompt against the dataset, then compare their score distributions side by side, so you ship the change that measurably wins.

Faithfulness

Scoring 5% of production spans

SpanInputScoreCost
support_agenttrack my package status0.95$0.0004
draft_replychange my delivery address0.63$0.0005
classify_intentis the invoice tax included0.91$0.0003
retrieve_docshow do I reset my password0.88$0.0006
draft_replyi was double charged this month0.58$0.0005
support_agentupdate my payment method0.94$0.0004
draft_replywhy was I charged twice0.61$0.0006
classify_intentcancel my subscription today0.92$0.0003
support_agentapply my discount code0.93$0.0003
summarize_threadthe agent never resolved my issue0.55$0.0007
retrieve_docswhere is my refund0.86$0.0007
draft_replythis is the third time asking0.66$0.0005

The same evaluator, now scoring live traffic

Deploy an evaluator on production spans, filtered by status, customer, or thread and sampled to control cost, so regressions surface in real time.

Quality is still an opinion.

Without a fixed set of cases and a grader you trust, a release comes down to whoever read the outputs most recently.

One number for every failure

A single quality score blends format errors, wrong facts, and the wrong tone together, so it moves without telling you which of them moved.

Nobody ever checked the judge

A model grades the answers and its verdicts get taken as truth, with no set of human-scored examples to say whether it agrees with you.

The judge changes under you

Providers retire and replace the model doing the grading, so a score that moved overnight might mean the work changed, or only the grader did.

Test cases nobody kept current

Examples written at launch, or invented wholesale, drift away from what users actually send, until passing them stops meaning very much.

Nothing stops a worse version

A prompt or model change goes out on judgement and a couple of spot checks, because nothing compares it against what is already live.

A score you cannot act on

The number says quality fell, and there is no way to open the runs behind it, so what actually changed stays a matter of guesswork.

Start with your own traffic.

Sample real requests into a dataset, chain the graders you need, and run it against any prompt or model variant.

Learn more
grader.py
import json
def main(eval_inputs):
"""Pass when the output is JSON with the keys we need."""
output = eval_inputs["output"]
if isinstance(output, str):
try:
output = json.loads(output)
except (ValueError, TypeError):
return False
if not isinstance(output, dict):
return False
required = {"category", "priority", "sentiment"}
return required.issubset(output.keys())

The AI observability platform behind 80 trillion+ tokens.

Loved by world-class founders, engineers, and product teams.

“Imagine jumping to a log immediately after every LLM call. This is the dream for debugging.”

Daniel Wolf

Product Lead, AlphaSense

“We scaled from 5M to 500M+ monthly API calls quickly. Respan gave us the debugging layer to resolve production issues 10x faster.”

Zexia Zhang

CTO, Retell AI

“Respan legit has some of the best UX/DX I’ve ever seen in my life. I truly don’t think I’ve ever integrated a product that was as easy.”

Rahul Behal

Co-founder, Gumloop

“This one felt pretty nice.”

Fabian Hedin

CTO, Lovable

“Such a no brainer choice over LangSmith or anything else and super easy to set up.”

Andy Wang

CEO, Finta

“Respan has been key in helping us scale to trillions of tokens reliably with real-time observability.”

Deshraj Yadav

CTO, Mem0

“Great product - really love the metrics dashboard.”

Esha Dinne

CTO, Giga

Certified where it counts.

Built to meet the security and privacy standards that enterprise and healthcare teams require.

ISO 27001

The internationally recognized standard for information security management.

SOC 2

Secure, compliant management of your data across all of our systems.

GDPR

Operated under GDPR, the world's strictest standard for data privacy.

HIPAA

HIPAA compliant, with a BAA available for healthcare teams.

Works with your entire stack

Use Respan with your favorite frameworks and tools.

AnthropicAI21 LabsxAIVercel AI SDK
LangChainOpenRouterAssemblyAICursor
LiteLLMGroqBasetenMem0
CohereCogneeLlamaIndexFireworks
DeepSeekLinkupHaystackTogether AI
PerplexityInference.netPostHogRubyLLM
SlackMastraAzure OpenAIMistral
AWS BedrockMoonshotHyperspellBAML
ModaInstructorGoogle GeminiParasail
ReductoZapierAgnoNebius
OpenAINovita AIReplicateSuperagent

Built for AI agents.
Break less.
Ship more.