Nine cloud and DevOps services engineered around the workload and run as one a migration factory that finishes what it starts, 24/7 managed operations, pipelines that ship daily, and cloud spend governed as unit economics rather than explained after the invoice.
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Individually consumable, designed to run as one. Pick a service to explore what’s inside.
From business case to landing zone to live — a migration factory that moves workloads in waves and finishes what it starts, instead of stalling at thirty percent.
Platform ecosystem: Azure Migrate · AWS MGN · Google Migrate · Device42 · CloudEndure · Turbonomic
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The estate run properly after go-live: 24/7 operations, patching, capacity, backup and incident command under one SLA with AIOps finding problems before your users report them.
Platform ecosystem: Azure Monitor · AWS CloudWatch · Datadog · ServiceNow · Ansible · Terraform Cloud
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Delivery pipelines engineered so releases become boring: automated build, test, security and deploy with a rollback path that has actually been used. CI/CD pipeline design & build
Platform ecosystem: Azure DevOps · GitHub Actions · GitLab · Jenkins · Argo CD · Harness · Nexus
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An internal platform your developers actually choose to use: Kubernetes, golden paths and self-service environments with guardrails already inside them.
Platform ecosystem:AKS · EKS · GKE · OpenShift · Argo CD · Backstage · Istio · Helm
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A 24/7 security operations center detecting and responding to cloud threats in real time — automated threat hunting, incident response orchestration and evidence-chain compliance built in.
Platform ecosystem: Microsoft Sentinel · Splunk · CrowdStrike · Datadog · Rapid7 · Wiz · IBM QRadar
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Reliability engineered rather than hoped for: SLOs, error budgets and telemetry that explains an incident instead of merely announcing it.
Platform ecosystem: Datadog · Dynatrace · Grafana · Prometheus · New Relic · OpenTelemetry · PagerDuty
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Security inside the pipeline and the platform shift-left scanning, posture management and compliance evidence produced as a by-product of delivery.
Platform ecosystem: Microsoft Defender for Cloud · Wiz · Prisma Cloud · Snyk · SonarQube · Trivy · Entra ID
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Cloud spend converted into unit economics: visibility by team and service, rightsizing, commitment strategy savings that still exist two quarters later.
Platform ecosystem: Azure Cost Management · AWS Cost Explorer · CloudHealth · Apptio Cloudability · Turbonomic
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One operating model across cloud, colocation and on-premise with recoverability tested on a schedule rather than described in a document.
Platform ecosystem: Azure Site Recovery · AWS Elastic DR · Veeam · Commvault · Zerto · VMware · Cisco
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Teceze AI-Driven Cloud & Operations Management Accelerate deployment and cloud governance with AI-powered intelligence. AI-driven cloud analytics and automation frameworks optimize resource provisioning, automate CI/CD pipeline bottlenecks, detect operational anomalies, and provide real-time FinOps insights to support high-performing, cost-efficient multi-cloud environments.
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A single release touches architecture review, a provisioning ticket, a security sign-off, a change board and a deployment window and every hand-off is where velocity, accountability and margin quietly leak. The business asked for speed. What it bought was a bigger bill and the same lead time.
The easy workloads move, the dependent ones don’t, and the business ends up funding two estates at once indefinitely.
No tagging, no owner, no unit economics. Finance sees a rising invoice; engineering sees no signal to act on.
Cloud-native platforms operated with ticket-era processes: environments take weeks, releases wait for windows, engineers wait for both.
Findings raised after build means rework, delayed releases and audit evidence assembled by hand under deadline.
Certified architects and engineers across Azure, AWS and GCP who build the landing zone, write the Terraform and hold the pager — the same team that designs it operates it.
Migration, platform engineering and 24/7 operations sit in one contract with one governance forum, so nobody gets to blame the hand-off. SLOs sit alongside SLAs: we’re measured on whether the service worked, not whether the ticket closed.
FinOps is part of the operating model from day one: tagging, showback, rightsizing and commitment strategy reviewed monthly with savings reported as unit economics your CFO can use.
4,500+ technical professionals, physical presence in 40+ countries and delivery capability across 135+ with security, evidence and change discipline built for healthcare, financial services and utilities.
Discovery and dependency mapping first, then a wave plan that groups workloads by application boundary rather than by server list. Each wave is rehearsed in a dry-run cutover with a tested rollback, and the first wave is deliberately a low-risk lighthouse that proves the runbook. Most business systems move inside a maintenance window; the ones that can’t use replication with a short switchover which is how a 480-workload manufacturing estate moved with zero unplanned downtime.
All three, plus hybrid and colocation estates. We run multi-cloud under a single operating model one landing-zone standard, one observability stack, one governance forum so multi-cloud doesn’t become multiple ways of working. Where a client has a strategic platform, we optimise for it rather than arguing for portability nobody will use.
FinOps as an operating discipline, not a one-off clean-up: tagging and showback so every team sees its own spend, rightsizing and idle reclamation as a monthly routine, commitment strategy managed against forecast, non-production scheduled off, and cost engineered at architecture review. Savings are reported as unit economics cost per customer, per transaction, per environment. Typical run-rate reduction is 25–35% in the first two quarters, and it holds because the routine continues.
Yes most engagements are exactly that. Three models: embedded engineers inside your squads, a platform team that gives your developers self-service golden paths, or fully managed run while your team focuses on product. Ownership boundaries, on-call rota and escalation paths are agreed before day one, in writing.
Security moves into the pipeline and the platform: SAST, SCA, container and IaC scanning at commit, policy as code blocking non-compliant infrastructure before it exists, cloud security posture management across the estate, least-privilege identity by default, and audit evidence generated as a by-product of delivery rather than assembled by hand before an audit.
Weeks 1–4: discovery, dependency mapping, cost and DORA baselines, risk register. Weeks 5–8: target architecture, landing zone, pipeline and observability foundations, lighthouse workload live. Weeks 9–12: first migration wave or first automated release train in production, governance cadence running, and a costed roadmap ranked by business impact rather than technical tidiness.
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