Cloud Platform Services
Your cloud platform is the foundation everything else runs on. Decision Foundry delivers cloud platform engagements across Azure, GCP, and AWS. From greenfield builds and migrations to managed services with certified engineers across all three platforms.
The Reality
Your cloud environment has grown organically with no clear architecture or governance behind it
You are going through a merger or acquisition, and two cloud environments need to become one
Your current platform is falling behind on AI capabilities and a move is starting to make sense
Post-acquisition infrastructure is carrying duplicated resources and unoptimized spend
Nobody knows what half your cloud resources do or who owns them
Your teams are paying for compute they are not using because nobody is monitoring costs
Three Platforms. One Expert Partner.
We work across all three major cloud platforms, recommending the right one for your situation and delivering across whichever you choose.
Azure is the natural home for organizations already running Microsoft 365, Dynamics, or Salesforce with Azure integrations. It is the strongest platform for hybrid cloud deployments connecting on-premises infrastructure with cloud workloads and has the deepest compliance certifications of any cloud provider, making it the default choice for financial services, healthcare, and government organizations.
What we deliver
AI capabilities
Azure OpenAI Service brings GPT-4, DALL-E, and other OpenAI models into your governed Azure environment. Azure AI Studio enables custom model fine-tuning and deployment. Copilot Studio allows organizations to build custom AI agents on Azure that connect to your data, workflows, and Microsoft applications.
GCP is the strongest platform for organizations where data and analytics are the primary workload. BigQuery, Google's serverless data warehouse, is one of the most powerful and cost-effective analytics engines available, and the native integration between BigQuery, Looker, Vertex AI, and Google Workspace makes GCP compelling for organizations that want their entire data and AI stack on one platform.
What we deliver
AI capabilities
Vertex AI is Google's unified ML and AI platform covering everything from AutoML to custom model training and the deployment of large language models. Gemini integration across BigQuery, Looker, and Workspace brings conversational AI into your data environment. NotebookLM and Gemini for Workspace extend AI capabilities to every knowledge worker in the organization.
AWS is the most mature and feature-rich cloud platform, with the broadest service catalog of any provider. It is the right choice for organizations with technically capable engineering teams who want maximum control and flexibility, and for high-volume workloads where AWS's global infrastructure and availability guarantees matter.
What we deliver
AI capabilities
Amazon Bedrock provides access to foundation models from Anthropic, Meta, Mistral, and others deployable within your governed AWS environment. Amazon SageMaker covers the full ML lifecycle from data preparation to model monitoring. Amazon Q is AWS's enterprise AI assistant connecting natural language querying to your AWS data sources, documents, and applications.
What We Do
We audit your current cloud environment: architecture, costs, resource utilization, security posture, and governance gaps. You leave with a clear picture of where you are, what is costing you unnecessarily, and a prioritized roadmap for what to fix first.
For organizations moving to the cloud for the first time or establishing a new cloud environment. We design and build from scratch: architecture, data layer, governance, security, and CI/CD optimized for your workloads from day one.
We manage end-to-end cloud migrations using a blue-green methodology: your current environment stays live throughout, the new one is built and validated in parallel, and cutover happens in a controlled maintenance window. We handle tenant-to-tenant migrations (same platform, different instance) and platform-to-platform migrations (Azure to AWS, AWS to GCP, and all combinations).
For organizations running workloads across more than one cloud provider. We design the integration layer, data flows, and governance model that makes multi-cloud coherent rather than chaotic.
Compute credits, storage costs, and unused resources that have accumulated without visibility. We audit your cloud spend, identify waste, and implement governance controls that keep costs tied to actual usage.
Ongoing cloud operations: monitoring, performance tuning, incident response, security patching, and a dedicated engineering partner across your cloud environment.
Not sure which cloud platform is right for your organization? We will assess your current environment, your workloads, and your roadmap and give you a straight recommendation before you commit to anything.
Book a Free Cloud AssessmentThe Process
We audit your current environment. Every workload, resource, dependency, and cost driver. For migrations, we specifically identify orphan resources: systems or workloads with no clear owner that create hidden risk during any transition.
We recommend the right platform and design the target architecture: data flows, security configuration, governance model, and compute strategy. For migrations, we design the parallel running strategy before any build begins.
We provision and configure the target environment: data layer, compute, storage, networking, security, and governance. For migrations, the new environment is built alongside the existing one. Nothing is disrupted during the build phase.
We migrate workloads, data, and pipelines to the new environment and validate thoroughly: testing data integrity, security, and functionality before any cutover is approved.
For migrations, cutover happens in a planned maintenance window, typically a weekend or off-peak period. Downtime is minimized to hours. The old environment stays available as a fallback.
Post-launch, we monitor performance, audit costs, remove unused resources, and provide ongoing engineering support as your cloud environment evolves.
Typical timeline: 6 weeks for a focused migration of 100 to 120 resources. Larger and more complex environments are scoped accurately during assessment.
At a Glance
| Azure | GCP | AWS | |
|---|---|---|---|
| Best for | Microsoft ecosystem, regulated industries, hybrid cloud | Data and analytics workloads, Google ecosystem | High-volume workloads, technically mature teams |
| Data warehouse | Azure Synapse, Microsoft Fabric | BigQuery | Amazon Redshift |
| ML and AI | Azure ML, Azure OpenAI, Copilot Studio | Vertex AI, Gemini | SageMaker, Bedrock, Amazon Q |
| Compliance certifications | Strongest, ideal for regulated industries | Strong | Strong |
| Pricing model | Pay-as-you-go, reserved instances | Pay-as-you-go, committed use | Pay-as-you-go, savings plans |
| Migration tools | Azure Migrate, Azure Data Factory | Database Migration Service | AWS Migration Hub, DMS |
| Decision Foundry partnership | Individually certified engineers | Individually certified engineers | Individually certified engineers |
Why Us
Our engineers hold specialist-level certifications across Azure, GCP, and AWS: individual certifications that reflect hands-on delivery experience, not just training completions.
We never migrate by switching off one environment and switching on another. We build in parallel, validate thoroughly, and cut over in a controlled window, every time. For a migration of 100 to 120 resources this means approximately 6 weeks of active work with downtime measured in hours.
Decision Foundry's core strength is data. Cloud migrations are not just infrastructure moves. We understand how your data flows, what your pipelines depend on, and what needs to be preserved and validated in the new environment. Most infrastructure-only partners miss this.
Orphan resources, systems with no clear owner and no documented purpose, are present in almost every cloud environment we assess. They create hidden dependencies that surface as failures during migration. We identify and resolve them before anything moves.
If a migration does not make commercial sense for your situation, we will tell you before you commit. A cost difference of less than 30% rarely justifies the cost and complexity of a platform migration. We would rather give you the right advice than win the wrong project.
Decision Foundry has been delivering data and engineering projects for over 20 years. Cloud platform work is an extension of the same data-first, outcome-driven methodology we apply across every engagement.
Who Benefits
Buyers
Users
Influencers
Ready to start?
Whether you are building on cloud for the first time, migrating between platforms, or optimizing an environment that has grown beyond your control, the starting point is the same.
Book a Free Cloud AssessmentCommon Questions
The right choice depends on your existing technology stack, your primary workloads, your team's technical capabilities, and your compliance requirements. We assess all of these during the discovery phase and give you a recommendation with clear reasoning before you commit.
Blue-green means running your old environment (blue) and new environment (green) in parallel throughout the migration. Nothing is switched off until the new environment is fully validated. Cutover happens in a short, controlled window. The old environment stays on standby as a fallback. This is how we protect your operations throughout every migration.
Orphan resources are systems, services, or workloads in your cloud environment that have no clear owner and no documented purpose. They are common in organizations that have grown quickly or been through previous transitions. They create hidden dependencies that only surface when something breaks in the new environment. We identify and resolve them in the assessment phase.
Rarely, unless the cost difference is substantial. Migration costs typically offset modest savings. A cost difference of less than 30% rarely justifies the investment. We assess this during discovery and will tell you honestly if it does not stack up.
For an organization with 100 to 120 resources, active migration work typically takes around 6 weeks. Larger, more complex environments take longer. We scope timelines accurately during the assessment phase.
Yes. Multi-cloud architecture is increasingly common. We design the integration layer, data flows, and governance model that makes multi-cloud coherent rather than an unmanaged sprawl of separate environments.
Yes. Our managed cloud services cover ongoing monitoring, performance tuning, cost optimization, and incident response across Azure, GCP, and AWS.