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Infinite Lambda Expands into the US, Appoints Jim Ternyila as Regional General Manager

Nas Radev
29 May 2025
Read: 2 min

Today, we are happy to announce Infinite Lambda’s expansion into the United States and the appointment of Jim Ternyila as General Manager for the region. The move marks a major milestone in the company’s international growth and comes at a pivotal moment, as enterprises look to turn AI ambition into scalable, real-world impact.

Despite record investment, most organisations remain early in their data and AI transformation journeys. Three-quarters of companies are limited to just a few AI use cases, and 90% of enterprise data, particularly unstructured data, goes unused.

Infinite Lambda helps its clients close this gap by modernising data infrastructure, designing fit-for-purpose AI strategies, and equipping internal teams with the knowledge and skills they need to use data and AI to solve business challenges, drive growth, and deliver measurable value and impact, securely, responsibly, and at scale.

“The challenge most companies face with their AI aspirations is the lack of proper foundations,” said Jim Ternyila, General Manager, US. “Most organizations are still operating on legacy platforms that weren’t built for AI. Their data is fragmented, governance is weak, and teams don’t have the tools or training to make it work. That’s the gap we close, and I will be working to bring that capability to the US market.”

To lead Infinite Lambda’s US operations, we have appointed Jim Ternyila as General Manager, US. Ternyila brings more than 15 years of experience driving digital transformation and AI strategy in healthcare and life sciences. He joins from Johnson & Johnson, where he has led cross-functional initiatives to enhance commercial performance, increase provider engagement, and improve patient outcomes through data-driven marketing and digital innovation.

Previously, at AstraZeneca, Ternyila led a global digital transformation programme that accelerated drug development timelines and generated more than $150 million in annual operational savings, blending R&D efficiency with measurable business impact.

“What drew me to Infinite Lambda and what sets us apart is our ability to help clients move from infrastructure to impact,” said Ternyila. “We don’t just modernize platforms; we help clients apply AI to the challenges and opportunities that matter most and ensure their teams are empowered to lead the transformation.”

At the core of Infinite Lambda’s approach is Flowline, our proprietary migration and modernisation platform. Designed to compress delivery timelines from months to weeks, Flowline automates the most time-consuming aspects of data migration from legacy platforms to modern infrastructure, while embedding best practices in governance, quality, and architecture.

Infinite Lambda also helps clients move beyond experimentation to meaningful AI adoption. The company works closely with business and data leaders to identify high-priority opportunities to leverage the power of AI to automate processes, eliminate inefficiencies, and augment how teams work to deliver business value. They then help design and implement AI solutions grounded in real-world workflows, from models that surface real-time insights to agentic solutions that support decision-making.

At Infinite Lambda, we are also unique in our approach to client enablement and capacity building. Our fully customised training programmes, technical accelerators and immersive bootcamps embed upskilling directly into delivery to ensure internal teams are equipped with the skills, knowledge and confidence they need to operate, adapt, and extend the AI-ready infrastructure that has been built.

With over 250 successful projects delivered across EMEA and APAC, and strong partnerships with Snowflake, dbt Labs, and Fivetran, Infinite Lambda brings a proven track record of engineering excellence, strategic clarity, and business impact. We serve clients across financial services, healthcare, insurance, retail, and technology, helping them move from legacy limitations to scalable, secure, and enterprise-level AI.

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