AI EXPERTISE # Artificial Intelligence Services Enterprises don't have an AI idea problem. They have an AI execution problem. Strategy without engineering gets you a roadmap, and engineering without adoption gets you a demo. We own all of it because half-measures are why most AI initiatives fail. TRUSTED BY LEADING COMPANIES ### 250+ AI Projects successfully delivered ### $4.4B In ROI generated for AI clients ### 400+ Improvers in our AI practice ### 21 Offices Across 7 countries and 3 continents WHAT WE DO ## From First Strategy to Full Production, We Own the Entire Artificial Intelligence Lifecycle Every stage of the Artificial Intelligence lifecycle is a practice Improving has built so your engagement doesn't stall when the work moves from one phase to the next. [**AI Strategy & Planning →** \\ \\ We connect your AI ambition to your actual data, engineering, and organizational reality. Executive strategies, team readiness assessments, use case prioritization, and a roadmap your teams can actually execute.](https://www.improving.com/expertise/ai/strategy-roadmap-assessment/) [**AI Training & Enablement →** \\ \\ We run AI workshops, enablement programs, and adoption sprints led by the same practitioners who deliver AI engagements for enterprise clients. Your teams build real skills into the work they're already doing. Not classroom awareness. Actual capability.](https://www.improving.com/services/training/ai/) ### Agent Creation & Deployment → From scoped proof of concept to enterprise-grade deployment. We build agentic systems that connect to your live data and act autonomously. GenAI, NLP, custom LLMs, and the production engineering that keeps them performing. ### Machine Learning & Data → Custom ML models, intelligent automation, and MLOps infrastructure built on your proprietary data. Not LLM wrappers. Not proof of concepts that never ship. Production machine learning, with the case studies to back it up. THE INTELLIGENCE OPERATING SYSTEM ## The Trust Evolution: 8 Stages of Artificial Intelligence Adoption Most organizations don't fail at AI because of the technology. They fail because they skip the trust-building stages that make AI safe to scale. Our maturity model defines the progression every enterprise goes through, not just in tools, but in governance, team readiness, and the way work gets done. ##### WAVE 1 ### Tools **Stages 1-2** From zero AI usage to off-the-shelf AI assistance. Humans approve every action, building the foundational trust required to advance. ##### WAVE 2 ### Process **Stages 3-4** AI moves beyond individual tasks to full workflows and governance infrastructure becomes essential. This is where most organizations stall. ##### WAVE 3 ### Agentic Operations **Stages 5-8** Agents run autonomously, coordinate in parallel, and span multiple products. This is where organizations stop managing AI and start operating with it. ## The Real Challenge isn't the Technology, It's Building the Trust to Let it Work Each stage builds the muscle memory and governance infrastructure required to advance. Skipping stages doesn't accelerate adoption. It undermines it. HOW YOUR TEAM EVOLVES NOT SURE WHERE TO BEGIN? ## Start With An AI Readiness Assessment We'll map your organization against our 8-stage IOS maturity model and show you exactly where you are and what comes next. No commitment required. [Get Your AI Readiness Score →](https://www.improving.com/resources/ai-readiness-assessment/) READY TO MOVE? ## Explore Our AI Deep Learning Program 12 weeks. A senior trainer and an Embedded Engineer working directly alongside your team, building real capability into the work you're already doing. [Explore the Program →](https://www.improving.com/services/training/ai/ai-deep-learning-program/) OUR PARTNER ECOSYSTEM ## Who We Build With & What We Build On We don't just have relationships with the world's leading technology platforms. We build real things with them, for clients like you. Here's how our ecosystem works together across a full AI engagement. [View All Partners →](https://www.improving.com/partners/) STRATEGY & ARCHITECTUREDATA FOUNDATIONBUILD & DEPLOY AIOBSERVE & MAINTAIN ### Setting the Foundation for AI Success _Before a single model is trained_ Every successful AI engagement starts with alignment: on goals, constraints, team structure, and what "done" actually looks like. Our strategy-phase partners help us get that right before anything is built. QUESTIONS WE'RE HELPING YOU ANSWER - Which cloud platform is right for your AI workloads and team? - What does a realistic 90-day AI roadmap look like for your organization? - How do you structure your team to deliver AI continuously? COMMONLY USED AT THIS STAGE [**Microsoft**](https://maps.app.goo.gl/D7cT1LAsKALW5A1s5) #### AWS #### Google Cloud TYPICAL DELIVERABLES #### AI Readiness Assessment #### Cloud Strategy #### Team Model Design #### 90-Day Roadmap **Microsoft Azure Solutions Architect Expert — validated expertise in enterprise cloud architecture and AI-ready infrastructure design** ### Getting Your Data House in Order _The work most teams skip. And regret_ AI runs on data. Before building anything, we help clients establish a reliable, governed, and scalable data platform so what we build on top of it actually works. This is where AI initiatives either get the foundation they need or stall. QUESTIONS WE'RE HELPING YOU ANSWER - Where does your data live, and is it trustworthy enough for AI? - How do you enable real-time data availability without losing governance? - What does a modern data foundation actually require at your scale? COMMONLY USED AT THIS STAGE #### Snowflake [**Databricks**](https://www.improving.com/partners/databricks/) #### Confluent TYPICAL DELIVERABLES #### Data Architecture #### Lakehouse Design #### Governance Model #### Streaming Pipelines **Databricks Certified Data Engineer Associate — certified expertise in lakehouse architecture, data pipelines, and ML-ready data platforms** ### Building and Deploying AI That Works _Where strategy becomes production_ This is where we build AI models, agents, integrations, and the infrastructure that ties it together. Our build-phase partner ecosystem covers cloud deployment, foundation models, and agentic systems that operate autonomously in production environments. QUESTIONS WE'RE HELPING YOU ANSWER - Which foundation model is right for your use case — and should you build or buy? - How do you deploy AI models reliably in a cloud-native environment? - What does an Agentic AI system that connects to your live data actually look like? COMMONLY USED AT THIS STAGE [**Microsoft**](https://maps.app.goo.gl/D7cT1LAsKALW5A1s5) #### AWS #### Google Cloud #### Anthropic #### Cognition TYPICAL DELIVERABLES #### Custom AI/ML Models #### Agentic MVP #### MLOps Pipelines #### AI/ML Deployment **Microsoft Azure AI Engineer Associate — certified expertise in building and deploying AI solutions on Azure including OpenAI, Cognitive Services, and ML pipelines** ### Keeping AI Systems Performing After Launch _Production is where promises are tested_ Getting to production is one thing. Staying there reliably, with full visibility into model performance, data drift, and infrastructure health, is another. Our observability-phase partners give us the monitoring and optimization tooling to keep AI systems performing under real enterprise load and improving over time rather than decaying. QUESTIONS WE'RE HELPING YOU ANSWER - How do you maintain AI model performance as data drifts over time? - How do you get full observability into AI systems without drowning in noise? - Where is cloud spend going and what can you responsibly reduce? COMMONLY USED AT THIS STAGE #### AWS #### Google Cloud #### Elastic [**Databricks**](https://www.improving.com/partners/databricks/) TYPICAL DELIVERABLES #### Observability Stack #### Model Monitoring #### Security Posture #### IaC Pipelines **Google Cloud Professional Data Engineer — certified expertise in designing data processing systems and building performant data pipelines for ongoing platform optimization** ### Building With Anthropic Claude powers some of the most capable agentic systems we build for enterprise clients. We bring Anthropic's safety-focused models into production environments where reliability isn't optional. CLIENT RESULTS ## Artificial Intelligence That Reaches Production. And Delivers. ### 3x Increase in qualified leads ### 90 Day delivery ### 42% Faster operating speed ### Agentic AI for Sales Enablement — From Manual Process to Production in 90 Days Lakeshore Learning's sales team spent hours manually sourcing educational funding opportunities across government websites and spreadsheets. Improving built an Agentic AI system that crawls live data sources, identifies relevant opportunities autonomously, and hands off to sales with full context — deployed in 90 days. FOR THE SKEPTICS ## Our Practitioners Teach What They Build - Watch Them Do It Every session is led by an Improving practitioner, the same people delivering AI 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 - YouTube Tap to unmute [Building Trust at Scale for Growth and AI: What to Do First, Next, and Later in Data Governance](https://www.youtube.com/watch?v=0YHEdEDfji0) [Improving](https://www.youtube.com/channel/UCp3IAAMb13i1bkNx-39OWig) Improving1.47K subscribers MARCH 12, 2026 ##### 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 - Improving Talks Series - YouTube Tap to unmute [Governance that actually works - Improving Talks Series](https://www.youtube.com/watch?v=iO4z-ICDEYs) [Improving](https://www.youtube.com/channel/UCp3IAAMb13i1bkNx-39OWig) Improving1.47K subscribers FEBRUARY 27, 2026 ##### 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 - Improving Talks Series - YouTube Tap to unmute [Define the Need, Solve the Problem: An AI-First Playbook for Developers - Improving Talks Series](https://www.youtube.com/watch?v=40xw1qOhWA4) [Improving](https://www.youtube.com/channel/UCp3IAAMb13i1bkNx-39OWig) Improving1.47K subscribers JANUARY 30, 2026 ##### Define the Need, Solve the Problem: An AI-First Playbook for Developers ###### Claudio Lassala _Technical Director_ 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 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. AI PRACTICE LEADS ##### Devlin Liles _Chief AI Officer & CCO_ ##### Scott Poulin _VP of Technology_ ##### 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