01 detect
Page lands. Alertnest opens an investigation in the same thread.
Accepting 2 Pilot Partners for Q1
AI Incident Investigator That Debugs While You Sleep.
We analyze your codebase and past incidents to understand your stack, then auto-build the integrations. By the time you wake up, you have root cause + fix scripts. Just review and approve.
- Auto-learns your stack
- Everything in Slack
- No setup required to try
Cab 16 · night watch 02:14
#incidents · publish-timeoutopen
pager High · publish timeout on log ingest. 02:11
Alertnest Intake open. Querying logs, pods, last deploy. 02:12
Alertnest Root cause: shard throughput after the 01:48 config push. Retry storm. Fix script staged — scale shards, add backoff. 02:14
you Approve. 07:02
Works with 40+ integrations
PagerDutyDatadogCloudWatchCoralogixGitHubKubernetesAWSGrafanaPrometheusSentrySplunkOpsgenieJiraVault
PagerDutyDatadogCloudWatchCoralogixGitHubKubernetesAWSGrafanaPrometheusSentrySplunkOpsgenieJiraVault
See Alertnest in action
Watch the watch: alert to resolution without leaving the thread.
How the agent triages a page from detection to a ready-to-run fix. No video embed — the cab log is the demo.
02 query
Logs, pod status, metrics, and the last deploy — correlated, not guessed.
03 report
Visual report plus a fix script sitting on the sill by morning.
04 approve
You click approve. Write actions stay human-in-the-loop.
Alertnest listens to your alerts, investigates autonomously, and delivers actionable fixes. Paste a screenshot, drop a log, ask a follow-up — the thread keeps the whole watch.
How it works
From alert to resolution in minutes.
Alertnest listens to your alerts, investigates autonomously, and delivers actionable fixes. Here is what that looks like in practice.
Investigation log · 02:12
PAGE open · publish-timeout · High
→ CloudWatch 5m error spike on ingest
→ k8s: 3/3 pods Ready, CPU 41%
→ GitHub: config push 01:48 · shard=4
root cause: shard throughput exceeded · retry storm
scripts/fix-shards.sh staged · awaiting review
Follow-up · 07:04
you: “was this the same as last Tuesday?”
matched incident 08-12 · same backoff gap
attached: latency chart · 01:40–02:20
you dropped ingest-error.log · parsed 214 lines, PII redacted
recommendation unchanged · approve when ready
Remediation · approved
write gate: human-in-the-loop
→ scale shards 4 → 8
→ apply retry backoff 250ms
audit A-4418 written · rollback script beside it
error rate returning to baseline
Why we are different
AI SRE isn’t new. Making it actually work is.
Most AI SREs fail because they lack context about your systems and ask you to spend weeks building integrations. We took a different approach.
Context
On setup we read your codebase, workspace history, and past incidents, then auto-build the integrations. PII is redacted before anything reaches the model.
Never leave Slack
The thread is the console. Paste a screenshot, drop a log file, view traces — all without leaving the investigation.
Try now
No setup required for the free trial. Two pilot partners for Q1 — write the office if the cab still has a chair.
How we compare
Not a chat window. Not a black box.
vs. ChatGPT
Queries real systems
ChatGPT guesses from training data. Alertnest queries your actual logs, metrics, and deployments in real time. No hallucinations about your stack.
vs. other AI SREs
No integration hell
Other tools ask you to build MCP servers and spend weeks on setup. We auto-learn your stack and build integrations for you.
vs. AIOps platforms
Open and controllable
No black-box ML. Alertnest is open core. You see exactly what it does, control its permissions, and can self-host.
Security
Built for production environments.
The agent runs in a sandbox. Your credentials stay safe. Deploy however you want.
Architecture · your infrastructure stays on your side of the glass
Recommended
SaaS (Hosted)
We host everything. Connect Slack and your observability tools. Fastest way to get started — complete setup in 30 minutes.
Regulated
On-Prem / VPC
Deploy in your own infrastructure. Your data stays in your network. We provide support and updates.
Hackers & tinkerers
Self-Host (OSS)
Open core. Run it yourself with complete control. Community support on GitHub and Slack.
Sandboxed execution
Each investigation runs in an isolated container with its own filesystem. Scripts and artifacts never touch your infra, and they are cleaned up when the session ends.
Credential injection via proxy
API keys are injected at request time. The agent never sees raw credentials — it just makes authenticated requests.
PII redaction
Sensitive data is detected and redacted before being sent to the LLM.
SOC 2 in progress Currently undergoing Type 2 audit. Data encrypted at rest and in transit.
RBAC Fine-grained access for teams, tools, and data sources.
Full audit trail Every AI action, query, and decision is logged.
Human-in-the-loop All write actions require approval. You stay in control.
The watch
Built by engineers who sat the night desk.
We spent years on application and database infra. We built Alertnest because on-call should not be this hard — and because the person holding the pager at 2am deserves a second pair of eyes that already knows the stack.
Two chairs in the cab. One radio. You keep the approve button.
Resources
Learn how teams use AI to improve reliability.
Keep the whole incident in one place
Why the investigation should never leave the channel that woke you up.
Redact before the model, always
Logs are full of secrets. The sandbox has to strip them first.
Approve is a feature, not a delay
Human-in-the-loop for every write. Auto-mitigation later, if you want it.