Self-hosted AI observability

What's happening
in production?

It's too easy for anyone
to understand now!

Ask in plain English. Get real answers from your logs, traces, and metrics. Self-hosted.

Try the Demo How it works →
Logsurface observability dashboard
Who it's for

Built for the people
who need answers.

Support Lead

Resolve escalations faster

When customers report issues, check production health yourself. No waiting for an engineer to context-switch from their sprint work.

"Are there any payment failures in the last hour for customers in Europe?"
Marketing Manager

Know if your drop was a hit or a disaster

You spent weeks building hype. Now see what actually happened — traffic surge, queue times, checkout success, payment failures. All in plain English.

"What percentage of users dropped off during checkout in the first 5 minutes of the Yeezy release?"
Engineering Manager

System health without the dashboard maze

Get a system overview before standup. Understand incidents without digging through monitoring tools. Ask the question, get the summary.

"Give me a health summary of all services for the last 24 hours."
How it works

One Docker image.
Live in minutes.

01
Run it
$ docker run logsurface
02
Connect it
Send OTLP data directly — it's a collector itself. Or point your existing collectors at it. Already using tools that export traces, logs, or metrics? That just works.
03
Use it
Browser, terminal, or your editor. Same engine behind all of them.
Done? Shut it down. Need it again? Spin it back up.
It's a tool, not a commitment.
Yours

Built around your team.

Your data stays on your servers.
Your costs stay predictable.
Your whole team has access — not just the SREs.
Your choice when to run it — and when not to.
Under the hood

Open by design.

Self-hosted
runs on your infrastructure
Bring your own LLM
use any model you want
Standard collectors
no proprietary agents to install
Pluggable
connect any data source
Multiple interfaces
web, CLI, IDE plugin, API — same engine
Ephemeral
spin up many, investigate in parallel, tear down when done
Fine-tuned models
trained on your data, runs inside the same container — nothing leaves your infrastructure
Your data  →  logsurface  →  answers
↓
IDE  ·  Web  ·  CLI
Custom engagement
We can fine-tune a model on your data and ship it inside your logsurface instance. Your telemetry never touches an external LLM provider. Fully in-house, fully private.
Get in touch →
Don't take our word for it

Try our demo.
It's enterprise scale.

500+ Million
synthetic spans loaded into a single container — modeled after a production sneakers platform. This is the demo. Ask it anything.
Try the live demo →
This is one Docker image on one machine.
No cluster. No managed service. No vendor.
Early Access

Be the first to try
LogSurface.

We're onboarding a small group of teams for early access. Pricing will be simple, predictable, and nothing like the per-host, per-GB model you're used to.