Build the trusted data and cloud foundations required for modern digital and AI products.
StrykerFox brings cloud architecture, data engineering, and modernization together to help organizations turn fragmented technology into reliable platforms for analytics, AI, and growth.
Disconnected data, legacy infrastructure, and inconsistent operating practices make it harder to deliver reliable insights and scale new products. We connect architecture, engineering, governance, and operations around the outcomes your business needs.
Bring critical information together with clear ownership, quality controls, and access policies.
Prioritize changes around business value, dependencies, continuity, and cost.
Create governed foundations that can support analytics, enterprise knowledge, and intelligent applications.
Define a practical cloud direction that connects business priorities with secure, scalable foundations.
Evolve legacy platforms through manageable changes that improve agility and operational readiness.
Build a coherent platform for trusted analytics, data products, and AI workloads.
Connect enterprise systems and deliver dependable data to the people and applications that need it.
Make data understandable, accessible to the right users, and suitable for its intended use.
Build visibility and operational discipline into the platform so teams can make informed decisions as usage grows.
We design each layer around your use cases, existing estate, security requirements, and operating model.
Data flows upward from sources and enterprise systems, through ingestion and integration, into a trusted data platform, and then to analytics and AI. Cloud and operations sits underneath as a supporting foundation for every layer.
Applications, operational databases, files, and external feeds.
Batch, streaming, APIs, and orchestration.
Storage, processing, quality, metadata, and curated data products.
Reporting, decision support, enterprise knowledge, and intelligent applications.
Identity, networking, infrastructure automation, observability, and cost controls.
Security, governance, and ownership span every layer.
Understand business priorities, workloads, data flows, dependencies, and current constraints.
Define the target architecture, governance model, success measures, and a sequenced roadmap.
Establish cloud foundations, engineer data pipelines, and implement the first useful platform capabilities.
Check quality, security, performance, recovery, and operational readiness before moving workloads.
Improve reliability and economics, enable teams, and expand using what the first releases teach us.
We agree on relevant baselines and success measures at the start of the engagement.
More dependable data for decisions
Faster access to analytics and AI foundations
Greater platform resilience and visibility
Clearer ownership and cloud cost accountability
Clarify the current state, critical gaps, and priorities.
Define the target platform and an achievable sequence of change.
Build, integrate, and operationalize the agreed foundations.
Let's explore how your cloud and data architecture can support the next stage of your business.