A Path for Each Workload
Every application gets its own decision: rehost, replatform, refactor, repurchase, retire, or retain, based on business value, technical fit, and the risk of changing it.
Cloud Solutions
Cloud Migration Services
Move to the Cloud With a Plan, Not a Leap
Cloud Intelligence Solutions moves applications, databases, and infrastructure to Azure, AWS, or Google Cloud for organizations that cannot afford a disruptive cutover. We plan each workload individually, build the landing zone first, and migrate in tested waves.
What We Deliver
Where We Make the Difference
Most troubled migrations trace back to missed dependencies or one approach applied to every workload. We start with discovery and dependency mapping, choose the right path for each application, and prove the playbook on a pilot wave before touching anything critical.
Dependency Mapping and Waves
Discovery tools such as Azure Migrate and AWS Application Discovery Service map servers, network flows, and integrations so related systems move together in the same wave.
Data Integrity Checks
Pre-migration and post-migration reconciliation, row counts, checksums, and parallel runs for data-heavy systems confirm that what arrives in the cloud matches what left.
Landing Zone First
Identity, network segmentation, security baselines, and policy guardrails are in place before the first workload lands, so the environment is ready for production from the start.
Our Approach
How We Deliver Cloud Migration Services
Step 1: Discover and Assess
Automated discovery inventories applications, servers, databases, and dependencies, and each workload is scored for cloud readiness, complexity, and the migration path that fits it.
Step 2: Build the Landing Zone
We set up the target environment and a repeatable migration factory with infrastructure-as-code, automated testing, and monitoring before any production workload moves.
Step 3: Prove It on a Pilot
A pilot wave of representative, lower-risk workloads tests the playbook end to end, and we refine runbooks and rollback steps before scaling up.
Step 4: Cut Over and Stabilize
Production waves follow an agreed schedule with rehearsed cutovers and rollback plans, then a hypercare period where we resolve issues and tune performance.
Should we lift and shift or modernize?
Usually both. Rehosting is the fastest way to exit a data center, while refactoring pays off for applications you plan to keep investing in. We recommend a path per workload rather than one approach for everything.
How do you limit downtime during cutover?
We use continuous replication where the platform supports it, rehearse each cutover, and run it in an agreed window with a tested rollback plan. Some legacy systems still need a short outage, and we identify those during assessment.
Which cloud should we migrate to?
We work across Azure, AWS, and Google Cloud and recommend one based on your existing licenses, skills, applications, and data strategy. If running more than one cloud makes sense for you, we design for that.
What happens after the last wave?
A hypercare period follows each wave to fix issues and tune performance. After that, your team can take over with our runbooks, or we can keep running the environment under a managed services agreement.
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