Grid Dynamics Insights

Driving the Future of
Enterprise AI with Grid
Dynamics and Google Cloud

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Our offerings combine strong domain expertise, world-class engineering capabilities, pre-packaged assets, and a deep relationship with Google Cloud to create a unique value proposition for our customers. The result is speed, efficiency, and reduced costs in building and deploying AI at enterprise scale.” — Ilya Katsov, Vice President of Technology at Grid Dynamics.

Generative AI emerges as a transformative force for enterprises and large organizations, unlocking creativity, reducing costs, and streamlining business operations to drive better decision-making and ultimate growth. However, many enterprise AI solutions fail to reach their full potential due to the ‘AI chasm’, a gap between development and deployment, causing them to fade into obscurity.

With generative AI as a valuable growth catalyst and a proven track record of deploying pragmatic data science and AI technologies, Grid Dynamics bridges this gap, breaking new ground for enterprise clients. Our expanded partnership with Google Cloud—to be one of its generative AI implementation partners—reaffirms our AI for enterprise leadership and accelerates the development of best-in-class solutions using Google Vertex AI.

In this ebook, we discuss how we leverage our artificial intelligence and machine learning model expertise and vendor partnerships to develop practical solutions for your business by addressing the following points:

a creative building changed by artificial intelligence

How generative AI creates tangible value in today’s competitive marketplace.

modern glass building of an enterprise that implemented AI

How Grid Dynamics has built a legacy in Enterprise AI, and what the future of generative AI holds.

a modern enterprise building generated by AI

How creating generative AI success is akin to building a fine-tuned car.

glass blocks generated by generative artificial intelligence

How we deploy impactful generative AI solutions leveraging Google Vertex AI.

The key generative AI business use cases that align with your business needs and how we can help you capitalize on them.

A snapshot of Grid Dynamics’ rapidly evolving generative AI offerings

virtual street to predict behaviour of virtual personas

AI Focus Groups

Problem: Traditional focus group methodologies lack efficient participant recruitment, geographical reach, and real-time insights.

Solution: AI-based focus groups enable you to analyze user-generated content, identify brand messaging, product and customer service improvements, and predict social media campaign performance through engagements with virtual personas powered by large language models.

from view on of the building in light orange and blue colours generated by AI

AI Product attribution

Problem: Despite significant investments in catalog attribution, retailers and brands continue to struggle with proper product attribution, especially in marketplaces.

Solution: Experience our revolutionary approach utilizing large language models to analyze, harmonize, and enrich product data, unlocking its full potential to increase data fidelity and enhance customer experience.

blue and orange glass boxes generated by visual AI

Visual Generative AI for Commerce

Problem: In digital commerce, brands and retailers face challenges with costly photoshoots, 3D rendering, scalability, and limited personalization for product visuals.

Solution: Transform your digital commerce experience by incorporating your product images into generative models, enabling hyper-personalization and scalable content generation across various environments with high fidelity and advanced post-processing techniques.

Conversational knowledge assistant

Problem: Enterprises struggle with managing internal documents, leading to knowledge gaps and inefficient onboarding and training processes.

Solution: Our LLM-powered Conversational Knowledge Assistant revolutionizes enterprise knowledge management, training, and access to essential information with natural language interaction and intelligent search capabilities.

a modern glass building where companies accelerate the product design process

Generative AI product design

Problem: Product designers spend massive amounts of time ideating, modifying and prototyping new product designs, where creative inspiration is often spurned.

Solution: Empower your product design teams, enhance collaboration, and inspire creativity with cutting-edge language-to-image and image-to-image tools to accelerate the product design process with a few basic text prompts or visual cues.

Legacy code modernization

Problem: Modernizing outdated software systems to improve maintainability, scalability, and alignment with current technology standards is a time-consuming and arduous task.

Solution: Unlock the potential of your legacy codebase with AI-powered conversion, effortlessly transforming outdated systems into modern, scalable software using large language models for efficient and accurate code migration.

AI Focus Groups

Problem: Traditional focus group methodologies lack efficient participant recruitment, geographical reach, and real-time insights.

AI Product attribution

Problem: Despite significant investments in catalog attribution, retailers and brands continue to struggle with proper product attribution, especially in marketplaces.

Visual Generative AI for Commerce

Problem: In digital commerce, brands and retailers face challenges with costly photoshoots, 3D rendering, scalability, and limited personalization for product visuals.

Conversational knowledge assistant

Problem: Enterprises struggle with managing internal documents, leading to knowledge gaps and inefficient onboarding and training processes.

Generative AI product design

Problem: Product designers spend massive amounts of time ideating, modifying and prototyping new product designs, where creative inspiration is often spurned.

Legacy code modernization

Problem: Modernizing outdated software systems to improve maintainability, scalability, and alignment with current technology standards is a time-consuming and arduous task.

AI Focus Groups

Problem: Traditional focus group methodologies lack efficient participant recruitment, geographical reach, and real-time insights.

Author

Eugene Steinberg

Technical Fellow, Head of Digital Commerce

Eugene Steinberg is the founding engineer at Grid Dynamics and the head of the Digital Commerce practice. As a Technical Fellow and Consultant, Eugene has delivered some of the most extensive Grid Dynamics programs, from inception to production to maturing. Eugene has many interests, including digital commerce platforms, applications of AI/ML to commerce, information retrieval, enterprise search, natural language processing, computer vision, as well as the general science & art of building scalable distributed systems. Eugene earned a Ph.D. in Applied Math from Saratov State University.

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Grid Dynamics Insights

Driving the Future of Enterprise AI with Grid Dynamics and Google Cloud

A snapshot of Grid Dynamics’ rapidly evolving generative AI offerings

AI Product attribution

Eugene Steinberg

Technical Fellow, Head of Digital Commerce

Eugene Steinberg

Technical Fellow, Head of Digital Commerce

Subscribe to Grid Dynamics insights now

Driving the Future of
Enterprise AI with Grid
Dynamics and Google Cloud

Subscribe to Grid Dynamics
insights now