Harnessing the Power of GenAI

With over a decade of experience in AI and more than three years specializing in GenAI, GlobalLogic is at the forefront of this transformative movement. Our goal is to enable businesses to adapt and thrive in this AI-driven era.

As a Hitachi company, we put the power of three brands to work for you – digital engineering services with GlobalLogic, experience and strategic design with Method, and digital infrastructure and data management with Hitachi – to deliver world-class products using emerging technologies.

Follow our series as our leaders discuss trends and discover how to transition from AI pilots to Enterprise-Grade AI.

Why is GenAI a revolutionary technology?

GenAI hype is everywhere. GlobalLogic experts weigh in on why it’s a truly game-changing technology.

What GenAI challenges are organizations facing?

Hear what GlobalLogic experts believe are the most significant challenges facing any organization seeking to deploy AI and GenAI at enterprise scale.

What is Enterprise-Grade AI?

Launching an AI POC can be quick and easy. Implementing Enterprise-Grade AI is far more complex. GlobalLogic leaders explain the importance of Responsible, Reliable, and Reusable AI.

How is GlobalLogic delivering Enterprise-Grade AI?

Lots of companies are talking about AI at enterprise scale. Together with Hitachi, GlobalLogic is already building an AI Platform-of-Platforms framework for Enterprise-Grade AI.

How-is-GL-delivering-enterprise-grade-AI

How is GlobalLogic using GenAI for software development?

Many organizations are putting GenAI to work in coding and testing. GlobalLogic’s CTO explains how our VelocityAI approach embeds GenAI throughout the full product development lifecycle (PDLC).

How-is-GL-using-GenAI-for-software-development

How can companies prepare data for GenAI?

GlobalLogic leaders explain why “data first” should be the mantra for any company pursuing Enterprise-Grade AI.

Why choose GlobalLogic for Content and Data Engineering?

A GlobalLogic GenAI expert explains why every company deploying a large language model (LLM) needs a structured approach to preparing and maintaining those models.