ENTERPRISE TECHNOLOGY PLATFORMS
Enterprise technology platform selection grounded in your requirements
We work across the cloud, data, AI, CRM, and automation systems organisations already run. We start with the workload, controls, integration boundaries, and operating model, then select and connect the technology that fits.
- Requirements and constraints defined before a platform is selected
- Architecture assessed across cloud, data, AI, CRM, and automation
- Delivery ownership carried from design into production
Enterprise technology platform selection starts with the decision.
We assess the workload, data boundary, integration needs, security controls, operating responsibilities, and existing estate before recommending a platform.
Where several platforms fit, we make the trade-offs explicit. The recommendation stays traceable to the requirements it must satisfy and the team that will operate it.
Six ecosystems, assessed in context.
Each page explains the capabilities we implement, where the platform fits, and how we connect it to the rest of the enterprise estate.
Microsoft
Azure, Microsoft Fabric, Power Platform, Dynamics 365, and Azure OpenAI for cloud, data, and enterprise AI.
EXPLORE02AWS
Cloud infrastructure, data platforms, and managed AI through services such as Amazon Bedrock and SageMaker.
EXPLORE03Google Cloud
Vertex AI, BigQuery, and the data and AI stack for analytics-heavy and GenAI workloads.
EXPLORE04Databricks
The lakehouse, MLflow, and Unity Catalog for governed data engineering and machine learning at scale.
EXPLORE05Salesforce
CRM, Einstein and Agentforce, and the integration work that connects customer data to action.
EXPLORE06UiPath
Robotic process automation, process mining, and agentic automation for measurable operational improvement.
EXPLOREFit comes before preference. We compare workload fit, security and data boundaries, integration effort, operating ownership, and total cost before choosing the platform pattern.
A useful platform ecosystem makes the connections, controls, and ownership clear.
One architecture, clear responsibilities, and a delivery plan across platform boundaries.
Designed as one estate
Cloud, data, AI, CRM, and automation connections are defined as one architecture, with interfaces and controls made explicit.
Ownership stays clear
We agree who owns platform configuration, integration, security decisions, release, and production support before delivery begins.
Decisions remain revisitable
Assumptions and trade-offs are recorded, so the architecture can be reassessed as demand, cost, or regulation changes.
A recommendation should be explainable. We document what was selected, why it fits, the constraints it carries, and the conditions that should trigger a review.
Bring us the decision. We will make the platform trade-offs clear.
We will define the requirements, assess the available platform patterns, and shape a delivery path your teams can review and operate.