Reliable Foundations for Growth
Platform Engineering
Organisations need cloud platforms that scale without operational headaches. Our Platform Engineering services deliver zero-downtime data operations, stable ingestion, and end-to-end Azure stack implementation.
Platform engineering, built on Microsoft Azure
Infrastructure (Azure) 
Digital App Innovation (Azure) 
Data & AI on Azure 
Microsoft Fabric Featured Partner 
Security Key Capabilities
Data Discovery & Ingestion
Comprehensive data discovery, ingestion, modelling, and transformation services that bring structure and reliability to your data operations across the Azure ecosystem.
Optimised Analytics Environments
Purpose-built Databricks, Synapse, and Azure Data Lake environments tuned for performance, cost efficiency, and your specific analytical workloads.
Continuous Delivery Pipelines
Pipelines built for continuous delivery and change, enabling rapid iteration and reliable deployments across your data and application estate.
Cloud-Native Data Pipelines
Azure Cloud-Native Data Pipelines for real-time and batch processing, ensuring data flows seamlessly from source to insight without interruption.
Hybrid Data Engineering
Hybrid data engineering solutions that bridge on-premises and cloud environments, enabling unified data operations regardless of where your data resides.
Governed Platform Architecture
Governed, scalable Azure platform architecture designed with security, compliance, and organisational standards built in from the foundation.
Deployment & Performance Optimisation
Deployment and performance optimisation with ongoing managed services to ensure your platform continues to operate at peak efficiency as demands evolve.
AI, ML & Advanced Analytics
AI and ML integration, IoT analytics, and advanced analytics capabilities that unlock deeper insights and drive intelligent decision-making across your organisation.
Faster environment provisioning with self-service
Reduction in manual platform toil
From concept to an internal developer platform MVP
Golden-path paved road for product teams
Where Platform Engineering drives value
Internal developer platform
Give engineering teams self-service templates for apps, data and AI workloads so they ship faster without reinventing compliance each time.
Azure landing zone at scale
Operate a CAF-aligned landing zone across dozens of subscriptions with consistent networking, identity, security and policy.
Zero-downtime data pipelines
Engineer reliable batch and streaming pipelines with Databricks, Synapse or Fabric that survive failures without manual intervention.
Container platform engineering
Run AKS as a product — with ingress, service mesh, policy, observability and developer tooling baked in.
Observability and SRE practices
Introduce golden signals, SLOs, error budgets and on-call so reliability is measured and continuously improved.
Platform ops for data and AI
Operate data and AI platforms as a shared service with capacity, cost, security and governance handled centrally.
A proven delivery approach
- 01 Step
Discover
Understand developer and data-team workflows, current pain points, and the highest-value paved roads to build.
- 02 Step
Design
Define target platform capabilities, self-service templates, security and compliance guardrails and operating model.
- 03 Step
Build
Deliver the platform iteratively — templates, pipelines, observability and documentation — and onboard the first product teams.
- 04 Step
Run
Operate the platform with clear SLOs, continuous improvement and a product backlog driven by consumer feedback.
Frequently asked questions
What is platform engineering, practically?
Treating your internal cloud, data and AI infrastructure as a product with paved roads, templates and self-service — so product and data teams get what they need quickly, without giving up on security, reliability or cost control.
How long does it take to build an internal platform?
A useful MVP with a handful of paved roads and real consumers typically takes 10–16 weeks. Mature internal developer platforms are a long-running product investment rather than a one-off project.
Do we need a large platform team?
No. Many clients start with a small core platform team (4–6 people) and scale as consumption grows. Synapx can run the platform team on your behalf, or work alongside yours to uplift capability.
How do you balance self-service with security?
Paved roads are secure by default. Templates bake in networking, identity, encryption, policy-as-code and monitoring, so product teams get safety without having to become security experts themselves.
Does platform engineering include data and AI?
Yes. We extend the same paved-road thinking to Fabric, Databricks, Azure ML and Azure AI Foundry so data and AI teams benefit from the same developer experience and guardrails as application teams.
Can Synapx run the platform long-term?
Yes. Synapx-as-a-Service covers ongoing platform operations, enhancement, SLO management and consumer support — leaving you free to focus on what runs on the platform rather than the platform itself.
Ready to Get Started?
Let's discuss how we can help your organisation unlock the full potential of your technology.
Book Your Free Assessment