AI SRE / DevOps agent
Rause
AI-Powered Root Cause Remediation
- Runs in your infrastructure
- Reads your code — not just logs
- Human-verified before any fix
See it work
From a customer's symptom to the line of code — in one minute.
The explainer below walks through how the two-agent system finds root cause, and why a human always signs off the fix.
60-second explainer — coming soon
Why it's different
Everyone else ships your logs to their cloud. We put the agent inside your walls.
The whole AIOps market is SaaS and telemetry-only. Rause runs in your environment and reads your source — so it names the line that broke, and nothing sensitive ever leaves.
Private by design
Runs in your cloud, your data centre, or on infrastructure we manage for you. Read-only. Air-gap supported. Your code and logs never train anyone else's model.
Root cause, not just alerts
It reads your codebase alongside your logs — correlating symptom to evidence to the exact file, function and commit. A hypothesis, not another anomaly to chase.
Humans stay in charge
The agent proposes; your engineers verify and apply. Nothing autonomous ever touches production — the only posture a serious, regulated team can trust.
How it works
Two agents. One human in charge.
A fast, cheap agent watches everything; a deep, code-aware agent investigates only what matters; your engineer signs off the fix.
- 01
Connect — read-only
Wire it to your repositories, your server/container/application logs, and your support tool. Scoped, least-privilege, entirely inside your environment.
- 02
Triage — fast & cheap
A lightweight agent reads every incoming ticket, alert and log anomaly. Deduplicates, classifies, filters noise, and escalates only what matters.
- 03
Diagnose — code-aware
A deep, code-aware agent traces symptom → evidence → code path and drafts the root-cause analysis, naming the file, function or commit, with a proposed fix.
- 04
Verify — your engineer
Your engineer confirms the cause and applies the fix. The agent proposes; a human disposes. Nothing autonomous ever touches production.
Deployment models
Three ways to run it.
Same software. Choose where it lives and who operates it.
- 01
In your cloud
Volorai installs into your Azure, AWS, or GCP subscription using Terraform modules we provide. You pay compute; Volorai charges a fixed subscription. Your data never leaves your environment.
- 02
In your data centre
Kubernetes (AKS, EKS, GKE, OpenShift, K3s) or a single host. Air-gapped supported. For sovereign, regulated, or sensitive estates — local model inference available so no signal ever crosses your perimeter.
- 03
Managed by Volorai
We run it on UK-sovereign infrastructure on your behalf. Single invoice, faster onboarding, a dedicated isolated environment, and a data processing agreement provided.
Frequently asked questions
-
Does our code or data leave our environment?
No. Rause runs entirely inside your environment — your cloud, your data centre, or infrastructure Volorai manages on your behalf. Code, logs and tickets never leave your boundary, and nothing you share trains a third party's model.
-
Does it change anything in production automatically?
No. Rause is read-only by default — no write access to production, no deployment, no config change, no data mutation. The agent proposes a root-cause analysis with a suggested fix; your engineer verifies and applies it. This is a hard product rule, not a setting.
-
How is this different from Datadog, New Relic, or other observability tools?
The mainstream AIOps and observability market is SaaS — your telemetry (and increasingly your source) ships to a vendor's cloud, priced per host or per gigabyte, and it's telemetry-only. Rause runs inside your infrastructure and reads your actual codebase, so it names the line that broke rather than flagging "an anomaly in service X".
-
What can we try first?
Incident Replay — a fixed-fee, read-only pilot from £5,000. We connect Rause to a handful of incidents you've already solved and let it produce its own root-cause analyses. You compare its answer to the one you already know. Low-risk, two to three weeks, and if it convinces you, it scales.
-
Where does it run?
Three ways, identical to our Knowledge Assistant deployment model: in your cloud (Azure, AWS, GCP), in your data centre (Kubernetes or a single host, air-gapped supported), or managed by Volorai on UK-sovereign infrastructure. Same software, three ways to run it.
-
What does it need access to?
Read-only access to your repositories, your server/container/application logs, and your support or ticketing tool — scoped to the systems in scope, least-privilege throughout. Volorai never holds standing production access on the customer-hosted model.
Prove it on your own incidents.
We connect Rause read-only to a handful of incidents you've already solved — and show you it re-derives the cause faster, from the evidence. Low-risk, fixed-fee, two to three weeks. If it convinces you, it scales.