PLATFORM EXPERTISE # Platform Engineering The right platform doesn't just support your technology strategy. It's the foundation every application runs on, every data pipeline flows through, and every AI system depends on. We design, build, and operate it at enterprise scale. TRUSTED BY LEADING COMPANIES ## Trust Starts at the Platform Layer As the **2025 Confluent Enablement Partner of the Year**, we hold more certified data streaming engineers in the Americas than any other partner. That credential wasn't given to us. It was earned in production environments, for enterprise clients. WHAT WE DO ## The Platform Decision Shapes Everything That Follows AI initiatives, data pipelines, and application modernization all depend on what's underneath them. We build the platform layer first, so your AI scales, your data flows reliably, and your applications hold under enterprise load. ### Cloud Platform (Hyperscalers) → Azure, AWS, and Google Cloud are where enterprise platform decisions start. We design cloud architectures, migrate workloads, and build the infrastructure your AI, data, and application teams depend on, with advanced partnerships across all 3 hyperscalers. ### Data & Analytics Platform → Snowflake, Databricks, Confluent, and Microsoft Fabric aren't interchangeable. We help you choose the right combination for your workloads, build the lakehouse or warehouse architecture that fits, and operate it in production. ### AI Platform & Infrastructure → The models are only as good as the infrastructure running them. We build and operate the MLOps pipelines, agent orchestration frameworks, and AI runtime environments that keep your AI systems performing at enterprise scale, not just in a demo. ### Integration & Application Platform → Your applications, data systems, and AI tools only deliver value when they work together. We design the integration layer that connects them, with modern observability built in so you know when something breaks before your users do. HOW PLATFORM CONNECTS EVERYTHING ## Platform Is the Glue That Makes AI, Data, and Applications Work Together Most AI initiatives, data programs, and modernization projects get the headline work right and fail underneath it. Weak cloud infrastructure, poorly designed data platforms, and underpowered AI runtimes are where promising work stalls. We build the platform layer first, so everything above it has a foundation worth building on. - The right **cloud platform** is what makes AI deployments production-ready, not just proof-of-concept - The right **data platform** is what makes machine learning run on your proprietary data, not generic models - The right **integration platform** is what makes your applications communicate cleanly across the enterprise OUR PARTNER ECOSYSTEM ## Built on Earned Credentials, Delivered in Production Every partnership on this page was validated through real delivery, not just a logo agreement. KUBERNETES CERTIFICATIONS ##### 74 Certified Kubernetes Engineers 51 CKA, 4 CKS, and 19 CKAD certified engineers across three specialization levels, built through real delivery engagements for enterprise clients around the world. KUBECON · 2025-26 ##### **Co-Chairs of KubeCon India** Improving practitioners co-chaired KubeCon India in 2025 and upcoming in 2026, with multiple speakers across both editions and contributions to the CNCF Platform Engineering Maturity Model. MICROSOFTAMAZON WEB SERVICESGOOGLE CLOUD ### Building Enterprise Solutions on Microsoft Azure _Cloud infrastructure, AI, data, and application delivery_ Microsoft Azure is the foundation for Improving's largest and longest-running enterprise engagements. From Azure AI and Azure OpenAI Service to Microsoft Fabric and Power Platform, we design and operate Azure environments that support AI, data, and application workloads at enterprise scale. QUESTIONS WE'RE HELPING YOU ANSWER - How do you design an Azure architecture that supports AI workloads at scale? - What does a Microsoft Fabric data platform look like for your organization? - How do you migrate to Azure without recreating the problems of your legacy environment? EARNED CREDENTIALS **Microsoft Azure Solutions Architect Expert — validated expertise in enterprise cloud architecture and AI-ready infrastructure design** TYPICAL DELIVERABLES #### AI Readiness Assessment #### Cloud Strategy #### Team Model Design #### 90-Day Roadmap CLIENT OUTCOME ##### **NCLH — Since 2019** 40+ person team modernizing a reservation platform serving 2M+ passengers annually ### Enterprise Delivery on Amazon Web Services _Cloud infrastructure, ML, DevOps, and data services_ AWS is the platform behind some of Improving's most complex cloud-native and ML infrastructure engagements. From AWS Bedrock and SageMaker to enterprise DevOps and data pipelines, we design and operate AWS environments that hold at enterprise scale and meet the demands of regulated industries. QUESTIONS WE'RE HELPING YOU ANSWER - How do you build an ML infrastructure on AWS that operates reliably in production? - What does a cloud-native DevOps practice look like on AWS at enterprise scale? - How do you migrate legacy workloads to AWS without introducing new technical debt? EARNED CREDENTIALS **AWS Solutions Architect Professional — validated expertise in designing distributed systems and enterprise-scale cloud architecture on AWS** TYPICAL DELIVERABLES #### Data Architecture #### Lakehouse Design #### Governance Model #### Streaming Pipelines CLIENT OUTCOME ##### Berkshire Hathaway Energy — 60% Faster Legacy-to-cloud migration on AWS; significant reduction in deployment time ### AI and Data Delivery on Google Cloud _Vertex AI, BigQuery, and public sector delivery_ Google Cloud is the platform behind Improving's AI and analytics work in healthcare and public sector. From Vertex AI and BigQuery to Healthcare API and Looker, we design and implement Google Cloud environments for organizations where data quality, AI reliability, and compliance are non-negotiable. QUESTIONS WE'RE HELPING YOU ANSWER - How do you implement AI search and summarization on healthcare data with Google Vertex AI? - What does a BigQuery data platform look like for an organization managing large clinical datasets? - How do you build on Google Cloud in regulated environments without slowing delivery? EARNED CREDENTIALS **Google Cloud Professional Data Engineer — validated expertise in designing and building data processing systems and ML models on Google Cloud** TYPICAL DELIVERABLES #### Custom AI/ML Models #### Agentic MVP #### MLOps Pipelines #### AI/ML Deployment CLIENT OUTCOME ##### PHSA — AI-Powered Patient Records Next-generation semantic search and summarization for Provincial Health Services Authority of BC on Vertex AI CLIENT RESULTS ## Platforms That Reach Production. And Hold ### 33 Minutes Deployment time, down from 4 to 6 hours ### 29 Distribution centers deployed simultaneously ### 100% DSCSA regulatory compliance met on deadline ### Automated Deployment Across 29 Distribution Centers McKesson's manual deployment process for their Drug Serialization Repository took four to six hours per location across 29 distribution centers, making DSCSA regulatory compliance nearly impossible to achieve on time. Improving automated the entire deployment pipeline using GitHub Actions, Kubernetes, Confluent Kafka, and MongoDB, reducing deployment time to 33 minutes per location and hitting the federal compliance deadline. FROM OUR PRACTITIONERS ## Our Practitioners Teach What They Build. Watch Them Do It From cloud architecture to real-time streaming to AI infrastructure, the same practitioners building enterprise platforms for clients teach live sessions every week. Open to everyone. No registration wall. Platform in Days, Not Weeks Diagramming to IaC With AI - YouTube Tap to unmute [Platform in Days, Not Weeks Diagramming to IaC With AI](https://www.youtube.com/watch?v=o_E3e2yNrzI) [Improving](https://www.youtube.com/channel/UCp3IAAMb13i1bkNx-39OWig) Improving1.47K subscribers OCTOBER 24, 2025 ##### **Platform in Days, Not Weeks Diagramming to IaC With AI** ###### Aman Juneja _Solutions Architect_ From Cloud to OmniChannel Fullstack Modernization - Improving Talks Series - YouTube Tap to unmute [From Cloud to OmniChannel Fullstack Modernization - Improving Talks Series](https://www.youtube.com/watch?v=IaLOJHtOess) [Improving](https://www.youtube.com/channel/UCp3IAAMb13i1bkNx-39OWig) Improving1.47K subscribers JULY 31, 2025 ##### From Cloud to OmniChannel Fullstack Modernization - Improving Talks Series ###### Josh Harrison _President, Improving Columbus_ From Fragmented Knowledge Power of Clean Data - Improving Talks Series - YouTube Tap to unmute [From Fragmented Knowledge Power of Clean Data - Improving Talks Series](https://www.youtube.com/watch?v=kYTYNu3TYac) [Improving](https://www.youtube.com/channel/UCp3IAAMb13i1bkNx-39OWig) Improving1.47K subscribers MARCH 28, 2025 ##### From Fragmented Knowledge to the Power of Clean Data ###### **Juan Cruz Fortunatti** _Solutions Architect_ IMPROVING TALKS ## **Improving Talks Runs Every Wednesday** Live sessions from our practitioners on real technical challenges. Open to everyone, no registration wall. [SEE UPCOMING SESSIONS →](https://www.improving.com/thoughts/webinars/) START A CONVERSATION ## Ready to Move from Platform Initiative to Platform Impact? Tell us where you are and we'll tell you exactly how we can help. No generic proposals, no sales pitch, just a direct conversation about your situation. PLATFORM PRACTICE LEADS ##### Michael Slater _VP of Technology_ ##### Brian van der Voort _VP of Consulting_ ##### Kevin Jourdain _Technical Director_ Name \* Email \* Phone Tell Us More \* 0/500 Subject utm\_source utm\_medium utm\_campaign utm\_content utm\_term referrer ga\_client\_id imp\_utmsource imp\_utmmedium imp\_utmcampaign imp\_utmcontent imp\_utmterm imp\_referrer ClearSubmit