Your team spends hours on incidents that should take 20 minutes. Archer fixes that — inside your VPC.
Autonomous AI SRE that triages, isolates root causes, and resolves incidents — without your production telemetry ever leaving your boundary. Get a guided demo with the SRE team.
Integrates with the stack you already run
The hidden cost of an 'always-on' engineering culture
The tools to observe production have multiplied. The humans paid to interpret them haven't. Here's where the money goes.
Your best engineers are glorified log parsers
2–4 hours per incident spent gathering data across Grafana, Sumo Logic, AppDynamics, and Datadog — before anyone even starts solving the problem.
Every P1 escalates to the same 3 people
Senior engineers pulled from strategic work for routine triage. Burnout climbs, roadmaps slip, and the bus factor stays at three.
Your SaaS AI tools can't touch production data
Compliance, data sovereignty, and security teams block multi-tenant AI platforms. Your telemetry can't leave the VPC — and shouldn't.
And it's getting worse.
We hear the same story from CTOs across regulated industries and high-growth startups alike.
“We tried Datadog Bits AI, but our security team shut it down. We can't send production telemetry to a third-party SaaS.”
VP Engineering · Fortune 500 Healthcare
“Our offshore team falls apart when incidents deviate from the runbook. Every Sev1 still escalates to the US team at 2 AM.”
SRE Director · Enterprise Tech
“MTTR is dominated by data gathering, not problem-solving. We're drowning in observability tools but still flying blind.”
CTO · Series C Startup
of MTTR is spent gathering and correlating data — not fixing the problem.
escalation rate for incidents that occur outside business hours.
average annual cost per senior SRE spent on routine triage.
Archer: the autonomous SRE that lives in your infrastructure.
Not another SaaS dashboard. A deployable digital worker that operates entirely within your cloud boundary — with full data sovereignty, zero vendor lock-in, and true autonomy.
Compresses 4 hours of data gathering to 15 minutes
- Auto-correlates logs, metrics, and traces across your observability stack
- Identifies causality — not just timestamps
- Hands engineers a finished investigation, not a haystack
Handles incidents autonomously — no hand-holding
- Maintains interaction memory of your team's risk tolerances
- Takes action without waiting for approval on routine fixes
- Escalates with 90% of the investigation already complete
Deploy in your VPC. Own your data. Control your stack.
- Runs entirely in your AWS / Azure / GCP environment
- GDPR, HIPAA, and FedRAMP ready out of the box
- Air-gappable for highest-security environments
A Major Airline reduced MTTR by 60% in production.
When the on-call rotation became the bottleneck for one of the world's most operationally complex airlines, Archer was deployed inside the existing observability stack — no telemetry ever left the boundary.
- Full integration with Grafana, Sumo Logic, AppDynamics — no rip-and-replace
- Routine triage handled autonomously, with human-in-the-loop on Sev1 hand-offs
- Senior engineers returned to roadmap work within the first quarter
Source: Major Airline pilot · Q1 2026
Reduction in Mean Time To Repair
Incidents escalated to senior engineers in first 90 days
Integration with existing Grafana, Sumo Logic & AppDynamics
From container to autonomous SRE in days, not quarters.
Deploy Archer in your environment
Container deployment to your AWS/Azure/GCP account. Connects to your existing observability tools via read-only credentials.
Archer learns your runbooks & wikis
A custom RAG brain trained only on your documentation. No model training on your data, no external knowledge bleed.
Incidents trigger autonomous triage
Real-time log analysis, causality mapping, and root-cause isolation — within seconds of the first alert firing.
Archer resolves or escalates with full context
Takes action within your stated risk tolerances, or hands off to humans with 90% of the investigation complete.
Can your team use a multi-tenant SaaS AI tool that processes production telemetry outside your VPC?
SaaS platforms are faster and cheaper.
Datadog Bits AI or Cleric.ai are great options. We'll cheerfully tell you so — Archer is built for teams where SaaS isn't a viable path.
Archer is the only path to autonomous SRE that meets your compliance and security requirements.
Production telemetry never leaves your boundary. Your security team can audit the agent, the model weights, and every action it takes.
| Requirement | SaaS AI | Archer |
|---|---|---|
| Data stays inside your VPC | ||
| Air-gappable / FedRAMP-ready deployment | ||
| Trained only on your runbooks (no cross-tenant model) | ||
| Acts autonomously within your risk tolerances | ||
| Integrates with Grafana, Sumo, AppDynamics, Datadog | ||
| Deployable in any cloud (AWS / Azure / GCP / on-prem) | ||
| No per-seat subscription required |
Questions security teams ask first.
Does any telemetry leave our environment?+
No. Archer runs inside your VPC and connects to your observability tools with read-only credentials. Production data never crosses your boundary.
Can it be air-gapped?+
Yes. Archer supports fully air-gapped deployments for the highest-security environments, and is GDPR / HIPAA / FedRAMP-ready.
How does it take action safely?+
Archer acts only within the risk tolerances and blast-radius limits you define. Anything outside those bounds is escalated with the investigation already complete.
How long is deployment?+
Container deployment to your cloud in days, not quarters — it learns your runbooks and wikis via a private RAG brain trained only on your docs.
Book a call with our SRE team.
30 minutes with the engineers who built Archer. They'll walk through your stack and answer your toughest observability questions.
- SOC 2 Type II (in progress)
- HIPAA / GDPR / FedRAMP ready
- Air-gappable deploy
Not sure it fits your stack?
Ask the engineers who built it