Platform Services
The Right Platform Changes Everything.
Platform isn't a supporting layer. It's the decision that determines whether your AI initiatives scale, your data flows reliably, and your applications hold under enterprise load. Every engagement starts here.
Cloud Platform (Hyperscalers) →
Executive AI strategies, team readiness assessments, use case prioritization, and the roadmap that connects your AI ambition to your actual data and engineering reality. Delivered in weeks, not quarters.
Data & Analytics Platform →
Team enablement, AI workshops, adoption programs, and the change management that ensures your people understand, trust, and actually use the AI systems you've invested in. Not just tolerate them.
AI Platform & Infrastructure →
Agentic AI MVPs that connect to your live data and act autonomously, from scoped proof of concept to enterprise-grade deployment. GenAI, NLP, custom LLM development, and the production engineering that keeps agents performing.
Integration & Application Platform →
Custom ML model development, intelligent automation, and MLOps infrastructure built on your proprietary data. This is the work that separates firms that do real AI from firms that wrap an API, and we have the case studies to prove it.
Platform Is the Glue That Makes AI, Data, and Applications Work Together.
The technology industry focuses on AI models, data pipelines, and application architecture — but most initiatives fail not at the surface layer, but underneath it. Weak cloud infrastructure, poorly designed data platforms, and underpowered AI runtimes are where promising work stalls. Improving builds the platform layer first, so everything above it has a foundation worth building on.
1. Anchor
Establish the foundation for a successful partnership. Align on goals, assess current state against the IOS maturity model, and define what success looks like before a single line of code is written.
2. Consistency
Deliver sustainable, repeatable value between Improving and the client. Regular cadences, transparent progress, and governance infrastructure that keeps teams aligned as the engagement evolves.
3. Transition
Demonstrate value through measurable outcomes and leave the client fully equipped to operate independently. Documentation, knowledge transfer, and a clear handoff — not a dependency.
Our platform practice is built on the world's leading cloud, data, and AI platforms. Here's how our partnerships with Microsoft, AWS, and Google Cloud translate into real delivery capability.
The Right Partner at Every Stage of Your Platform Journey
We don't just hold partner status with the world's leading cloud platforms. We've earned credentials, built practices, and delivered outcomes that validate every claim on this page.
Enablement Partner of the Year
Awarded to the partner that best equips enterprise teams to operate Confluent in production, not just implement it. Improving holds more certified data streaming engineers in the Americas than any other partner.
Most certified data streaming engineers in the Americas
Canada Partner of the Year — Public Sector
Recognized for delivering measurable outcomes on Google Cloud for public sector clients across Canada — validated by Google based on technical delivery, client impact, and certification depth.
Validated across technical delivery, client impact & certification depth
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.
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?
Microsoft Azure Solutions Architect Expert — validated expertise in enterprise cloud architecture and AI-ready infrastructure design
AI Readiness Assessment
Cloud Strategy
Team Model Design
90-Day Roadmap
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.
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?
Databricks Certified Data Engineer Associate — certified expertise in lakehouse architecture, data pipelines, and ML-ready data platforms
Data Architecture
Lakehouse Design
Governance Model
Streaming Pipelines
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.
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?
Microsoft Azure AI Engineer Associate — certified expertise in building and deploying AI solutions on Azure including OpenAI, Cognitive Services, and ML pipelines
Custom AI/ML Models
Agentic MVP
MLOps Pipelines
AI/ML Deployment
PHSA — AI-Powered Patient Records
Next-generation semantic search and summarization for Provincial Health Services Authority of BC on Vertex AI
Platforms That Reaches Production - And Sustain
Agentic AI Lead Qualification — From Pilot to Production in 90 Days
Lakeshore Learning needed to qualify high-intent prospects at scale without adding headcount. Improving built an Agentic AI system that connects to live data, qualifies leads autonomously, and hands off to sales with full context — deployed in 90 days.
> "Improving didn't just build the agent — they made sure our team understood it, trusted it, and could build on it."
Our Practitioners Teach What They Build - Watch Them Do It
Every session is led by an Improving practitioner, the same people delivering platform engagements for enterprise clients. Deep technical content, real delivery experience, open to everyone.
Building Trust at Scale for Growth and AI: What to Do First, Next, and Later in Data Governance
Preston Mesarvey
Technical Director
Governance That Actually Works: How Well-Designed AI Systems Make Responsibility Visible
Devlin Liles
Chief AI Officer
Define the Need, Solve the Problem: An AI-First Playbook for Developers
Claudio Lassala
Technical Director
Ready to Move from AI Initiative to AI 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.
Devlin Liles
Chief AI Officer & CCO
Scott Poulin
VP of Technology
Kevin Jourdain
Technical Director