AI-native engineering · UK
Autonomous operations. Uncompromising engineering.
We build AI agents that triage incidents, review infrastructure changes and heal Kubernetes clusters — on top of the GitOps, observability and SRE foundations that make autonomy safe.
- alertErrorBudgetBurn 14x · checkout-api
- queryrate(container_memory_working_set_bytes[5m])
- correlateargocd: synced v2.14.3 · 19m ago
- policykyverno: rollback allowed (L3)
- actgit revert → argocd sync v2.14.2
- verifyburn rate 0.8x · SLO healthy ✓
Standards
Engineered to the standards of global cloud-native leaders
- aligned with · CNCF landscape
- aligned with · SLSA L3 supply chain
- aligned with · NIST SP 800-190
- aligned with · CIS Kubernetes Benchmark
- aligned with · OWASP Top 10 for LLM Applications
- aligned with · OpenTelemetry
- aligned with · Google SRE practices
Why
Why AI-native operations need serious engineering
Agents need ground truth
An agent is only as good as the signals it reads. We instrument first — Prometheus, Loki, Tempo, eBPF — so every decision is grounded in real telemetry, not guesswork.
Every action goes through Git
Agents don't kubectl apply into the dark. They open pull requests, ArgoCD reconciles them, and every change is reviewable, revertible and audited.
Autonomy is earned, not switched on
We raise autonomy one level at a time — suggest, approve, act within guardrails — gated by Kyverno/OPA policies and SLO burn rates.
Faster recovery, fewer pages
Machines handle the 3 a.m. triage. Your engineers handle the architecture. The goal is lower MTTR and on-call your team can live with.
Services
Four practices, one operating model
AI & Agentic Operations
CoreAgents that triage, diagnose and remediate — under policy, through GitOps.
- AIOps incident triage over Prometheus, Loki and Tempo
- CI/CD agents: IaC inspection and automated PR review
- LLM tool-calling against your infrastructure APIs (MCP)
- Kubernetes
- vLLM
- AWS Bedrock
- MCP
- Prometheus
- Loki
- Argo Events
Platform & Kubernetes
Hardened, self-service platforms your developers actually want to use.
- Internal Developer Platforms (Backstage, golden paths)
- Zero Trust and policy-as-code on EKS, AKS, GKE and Talos
- Advanced GitOps and container lifecycle
- Cilium
- eBPF
- Kyverno
- Talos
- ArgoCD
- Flux
- Backstage
DevOps & IaC
Infrastructure as code that is modular, governed and boring in the best way.
- Terraform / OpenTofu module libraries with policy checks
- Secure CI/CD pipelines (DevSecOps, SBOMs, signed artefacts)
- Automated migration and legacy refactoring
- Terraform
- OpenTofu
- Crossplane
- GitHub Actions
- Sigstore
- Trivy
SRE & Cloud Architecture
Systems designed to fail gracefully — and to tell you before they do.
- High-availability, multi-cloud and serverless architecture
- Full-stack observability with SLOs and error budgets
- Chaos engineering and proactive incident readiness
- AWS
- Azure
- GCP
- OpenTelemetry
- Grafana
- Chaos Mesh
- Lambda
Simulation · reference scenario, not a customer engagement
A memory leak on EKS, resolved in 45 seconds
- $ waiting for signal… press Play or Step
Memory per pod
—Checkout SLO burn rate
—Current step
Not started
The agent mitigated. A human fixes the root cause. That's the division of labour we design for.
Find out how close you are to autonomous operations
The AI & Infrastructure Assessment is a fixed-scope, two-week review of your platform, observability, delivery pipeline and AI-readiness. You get a written report, a maturity score from L0 to L4, and a prioritised 90-day roadmap.
- Kubernetes & security posture
- Observability & SLO coverage
- CI/CD & IaC governance
- Where agents can safely act first