// Delivery process

Four phases.
No surprises.

Full transparency on what happens, when, and what you receive — with realistic timelines built on 18 years of delivery experience, not wishful thinking.

01ASSESS
Assessment
We learn your world before we touch anything.
1–2 weeks

Structured audit of your current infrastructure, tooling, developer workflows, team skills, AI ambitions, and business constraints. Results in an honest maturity scorecard and a clear gap analysis — including your AI readiness level. Available as a standalone engagement with no obligation to proceed.

We examine
  • Infrastructure, CI/CD, and tooling audit
  • Developer experience survey (DORA baseline)
  • AI workload requirements & readiness
  • Security, compliance & cost posture
  • Team skills vs. platform engineering requirements
You receive
  • Platform Maturity Scorecard
  • AI Readiness Assessment
  • Current-state architecture diagram
  • Prioritised gap analysis & risk register
  • Honest go/no-go recommendation
📄 Assessment Report 📊 Maturity Scorecard 🤖 AI Readiness Report ⚠️ Risk Register
02PLAN
Planning
Architecture first. Code second. Always.
2–3 weeks

We design your target-state platform with the AI layer fully integrated — not as an afterthought. Tool selection, golden paths for both standard and AI workloads, cost modelling including GPU and LLM token spend. Nothing gets built until you've signed off on the plan.

We design
  • Target architecture (platform + AI layers)
  • CNCF tool selection with rationale (ADRs)
  • AI infrastructure design (model serving, vector DB, gateway)
  • Golden paths for standard & AI workloads
  • Phased delivery roadmap with milestones
You receive
  • Full architecture documentation
  • Technology decision log (ADRs)
  • Cost model (cloud + GPU + LLM token spend)
  • Delivery roadmap with realistic timelines
  • Estimated DORA improvement projections
🏗️ Architecture Docs 📋 ADR Log 🗓️ Roadmap 💰 Cost Model (incl. AI)
03BUILD
Build
Production-grade. GitOps-first. AI-ready from day one.
6–16 weeks

Hands-on delivery in your environment, alongside your team. Platform layer first, AI layer integrated as the second track. Weekly sprint demos — you see progress every week, not just at the end. Everything lives in Git from the first commit.

Platform track
  • Kubernetes + GitOps foundation (ArgoCD/Flux)
  • Backstage developer portal + service catalogue
  • Self-service infra via Crossplane
  • Observability: Prometheus, Grafana, OTel
  • Vault secrets + OPA/Kyverno policies
AI track
  • GPU node pools + NVIDIA device plugin
  • Model gateway (LiteLLM) + serving (KServe)
  • Vector database deployment & integration
  • RAG pipeline infrastructure
  • AI observability (Langfuse / Phoenix)
  • AI golden paths inside Backstage

⚡ Honest note: Timeline varies based on starting point and scope. A greenfield IDP on AWS for a 50-person team is typically 8–10 weeks. Adding the AI layer adds 4–6 weeks. Migrating a complex legacy environment can be 12–16 weeks. We tell you upfront — never padding estimates to look safe.

⚙️ Live IDP + AI Layer 📁 All IaC in Git 📖 Runbooks 🔐 Security Docs 📈 Weekly Reports
04ENABLE
Train & Enable
Your team owns this. Not us.
2–4 weeks

Structured training across both the platform and AI layers — tailored to your team's actual roles. Ops engineers get platform operations depth. Application engineers get AI infrastructure patterns. Everyone gets the runbooks and confidence to act independently. Includes a 30-day post-handover support window.

Platform training
  • Day-2 Kubernetes operations
  • GitOps workflows & ArgoCD management
  • Backstage extension & catalogue maintenance
  • Incident response & troubleshooting drills
AI infra training
  • LLMOps fundamentals & model lifecycle
  • Model gateway operations & routing
  • AI observability & cost monitoring
  • Onboarding new AI services to the platform
🎓 Workshop Materials 📹 Recorded Sessions 📘 Extension Guide 🆘 Escalation Runbook 30-day support window
// Typical end-to-end — medium scope AI + IDP project

A full engagement from first call to trained team typically runs 16–24 weeks. IDP-only (no AI layer): 12–18 weeks. Standalone assessment: 1–2 weeks.

W1–2
W3–5
W6–20
W21–24
Assessment
Planning
Build (Platform + AI tracks)
Enable
★ Honest note: These are realistic estimates based on 18 years of delivery experience. We never commit to a timeline we can't keep — and if something unexpected comes up, you hear it from us first.
// Start with phase 01

The Assessment is available
with no obligation to continue.

Understand your current platform maturity and AI readiness in 1–2 weeks. No commitment required beyond that.

Book a Free Intro Call →