AI Observability for
Production LLM Apps
On the same platform as tracing, evals, and the gateway, metrics, saved views on logs and traces, and threshold monitors.
Know the moment things change.
Track requests, errors, cost, latency, and tokens on one dashboard, and get alerted the moment any of them crosses a threshold you set.
An alert the instant a metric crosses its limit
Watch cost, errors, latency, or tokens over any window, and the alert reaches Slack, email, or a webhook the moment it breaches.
Every metric on one dashboard
Requests, errors, cost, latency, and tokens across all your traffic, sliced by model, key, or user, so a spike is easy to spot.
See what moved, and why.
Requests, errors, cost, latency, and tokens are counted as they arrive, and every figure on the chart still opens the runs underneath it.
Everything arrives on one pipe
One SDK call, or a POST from the pipeline you already run, and each request feeds metrics, logs, and traces together.
Counted the moment it lands
Requests, tokens, errors, latency, and cost roll up as traffic arrives, split by model, key, and user rather than one total.
Still openable, one run at a time
A chart is never a dead end: the same filters sit behind the logs and traces, so a spike opens as the requests that caused it.
You monitor apps, not models.
Standard monitoring covers requests and errors, so a model that gets slower or more expensive never trips an alert.
One total, and nothing under it
The bill arrives as a single number each month, with no way to see which model, feature, or customer is the one that actually moved it.
The same filters, typed again
Every incident starts by rebuilding the same conditions from memory, and two people looking at the same outage rarely end up on the same set.
Only the crashes raise an alarm
A model can answer every request successfully while cost doubles and replies slow to a crawl, and nothing built around errors will notice.
Alerts nobody reads any more
One threshold covers all traffic, so it fires on somebody else's model or environment until the whole channel gets muted as noise.
A window too wide to see it
A five minute spike averaged across an hour barely registers, so the alarm stays quiet while the incident comes and goes underneath it.
A chart you cannot open
The line moves and that is where it ends, because nothing connects the number to the individual requests that made it move.
Send the data, then set the limit.
One SDK call, or a POST from your own pipeline, puts every request on the dashboard, and a monitor watches whichever number matters.
import jsonimport requests messages = [{"role": "user", "content": "Where is my order?"}]reply = {"role": "assistant", "content": "Checking that now."} requests.post( "https://api.respan.ai/api/request-logs/", headers={"Authorization": "Bearer YOUR_RESPAN_API_KEY"}, json={ "model": "claude-opus-4-8", "log_type": "chat", "input": json.dumps(messages), "output": json.dumps(reply), "customer_identifier": "user_123", },)import jsonimport requests messages = [{"role": "user", "content": "Where is my order?"}]reply = {"role": "assistant", "content": "Checking that now."} requests.post( "https://api.respan.ai/api/request-logs/", headers={"Authorization": "Bearer YOUR_RESPAN_API_KEY"}, json={ "model": "claude-opus-4-8", "log_type": "chat", "input": json.dumps(messages), "output": json.dumps(reply), "customer_identifier": "user_123", },)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.”
Read how Retell builds next-gen voice agents that scale->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.”
Read how Mem0 builds reliable self-improving AI memory layer->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.
