abeebaCloud-to-AI Migration
AI projects stall when data is locked in legacy systems and the infrastructure was never built for GPUs. We plan and run the migration of data, services and pipelines onto an AI-ready platform, in phases, without breaking what already works.
What's included.
Readiness assessment
An inventory of systems, data sources and dependencies, scored for AI readiness and migration risk.
Data platform foundations
Lakehouse or warehouse design, ingestion pipelines and governance so models get clean, permitted data.
Phased migration
Strangler-pattern cut-overs with parallel runs, so each step can be verified and reversed.
GPU-ready landing zone
Networking, identity, storage and GPU node pools set up correctly from day one.
How the engagement runs.
Assess
Inventory systems and data, define target architecture and migration waves.
Build the landing zone
Provision the target platform with security and networking baselines.
Migrate in waves
Move workloads wave by wave with parallel runs and sign-off gates.
Retire & optimize
Decommission legacy components and tune the new platform for cost.
What you keep at the end.
- Migration plan with waves, owners and rollback steps
- Landing zone as code
- Data pipelines and catalog
- Decommission checklist for legacy systems
Tools we commonly use
We pick tools to fit your environment and team. These are the ones we use most often.
Do we have to move everything at once?
No. We migrate in small waves that each deliver value and can be verified on their own.
Can some systems stay on-prem?
Yes. Hybrid designs are common, especially where regulation keeps certain data in your own facility.
Who owns the code and infrastructure afterwards?
You do. Everything is delivered as code in your repositories and accounts.
Often combined with.
Private & On-Prem LLM Deployment
Run open-weight models inside your own servers, VPC or air-gapped network.
Learn moreGPU Infrastructure Optimization
Cut inference and training cost by raising utilization across your GPU fleet.
Learn moreMLOps Pipeline Setup
Automate training, evaluation, deployment and monitoring end to end.
Learn moreReady to run AI on your own terms?
Book a 30-minute consultation with an infrastructure engineer. You'll leave with a clear view of options, costs and next steps, whether or not you work with us.