CASE STUDY

Scaling AI Capability Across Engineering Teams

How InterSystems upskilled 150+ software developers to build and deploy AI solutions

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98%

Of participants reported increased confidence in using AI

92%

Graduation rate across four cohorts

40%

Uplift across every core AI engineering skill assessed

OVERVIEW

Intersystems

InterSystems is a global leader in healthcare data management, supporting Organizations around the world with technology that connects and makes sense of complex information.

Its flagship platform, IRIS, enables Organizations to manage, integrate and analyze data at scale.

As AI rapidly reshapes the healthcare technology landscape, it has become a strategic priority for InterSystems. With rising customer expectations and AI increasingly embedded into its products, building the confidence and capability to apply this technology effectively was a critical next step in its evolution.

The problem

As AI capabilities advanced, InterSystems recognized their operating model was being fundamentally reshaped. Integrating AI wasn’t just a feature upgrade, it changed how their teams needed to think, build and deliver.

While AI became central to their roadmap, there was a gap between ambition and execution. Developers needed practical experience to confidently build, evaluate and integrate AI solutions within the IRIS platform.

The real challenge was embedding AI at scale, quickly and sustainably. Targeted education became the most effective way to close that gap.

The approach

Without strengthening internal AI capability, InterSystems risked falling behind faster-moving competitors and weakening their position as a healthcare data platform leader.

They partnered with Edifai to rapidly upskill their software engineers through a hands-on program designed to embed AI capability directly into product development.

The solution

To date, we’ve trained over 150 InterSystems software engineers (and counting), equipping them with the practical skills to design, build and deploy AI applications.

The program included:

Structured, cohort-based learning : A 10-week program combining expert-led sessions and hands-on workshops, guiding participants from core AI foundations through to real-world application within the business.
Skills benchmarking:  Pre-program assessments to establish baseline capability and measure improvement over time.
Hands-on practice:  Small-group collaboration to scope, build and deploy a working AI application, applying new skills in a practical context.

Key programme outcomes

Over 10 weeks, participants committed around six hours per week to develop the ability to:

Build AI end-to-end

‍Develop and integrate LLM-powered solutions using Python, Jupyter and Hugging Face within InterSystems IRIS.

Demonstrate measurable improvement

Benchmark capability before and after the programme to track skills growth.

Ship real AI applications

Develop functional RAG systems and agent-based workflows, moving beyond the theory into practical deployment.

Scale AI capability across teams

Learn through a structured cohort model that enabled consistent upskilling across regions and embedded AI into day-to-day development work.

Uplift across every core AI engineering skill assessed

The training enabled InterSystems’ engineers to move from experimentation to confident, real-world application, embedding AI into their development workflows and accelerating innovation across the IRIS platform.

What’s next?

Following the success of the initial cohorts, the programme now runs annually across multiple time zones, including APAC. Demand from engineers continues to grow, with strong interest in participating as AI capability becomes an increasingly central part of their strategy.

Our partnership is also expanding into training for product teams, and early discussions around customer-facing education initiatives, as they embrace a broader shift from internal upskilling to enabling their whole ecosystem.

Alki Iliopoulou

Innovation Strategist - Ecosystems Lead

InterSystems

“The 10-week AI for Software Developers program has been hugely impactful in changing the way we work. Delivered across multiple global cohorts, it has helped our engineering teams build practical skills and confidence in applying AI and supported our shift toward becoming an AI-first organization. We’re excited to continue expanding this work in 2026 and beyond.”

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