Generative AI
For Retail &
E-Commerce
SambaNova Suite Avances Personalized
Experiences That Delight Customers
Leverage AI to Improve the Customer Journey
The pandemic accelerated the growth of online shopping, leaving retailers scrambling to improve their online experiences and shore up their digital transformation efforts. At the same time, customer expectations have never been higher, with 91% of consumers more likely to shop with brands who recognize, remember, and provide relevant offers and recommendations.1Source: Accenture, Making it Personal, Personalization Pulse Check
E-commerce giants are widening their lead in digital acceleration, leaving the rest of the market to make a choice—innovate or become irrelevant. To differentiate and stay competitive, retailers must lean into rapidly advancing AI technologies to better understand their customers and provide them a more personalized and satisfying buyer’s journey.
Strengthen Customer Relationships With Your Brand
Developing and deploying state-of-the-art recommendation and language services can be complex, expensive, and beyond the reach of many retail organizations—until now. SambaNova Suite augments the AI expertise of retailers of all sizes by providing a comprehensive platform, services, and models that enable you to develop and deploy state-of-the-art AI solutions without the time and expense of building complex AI architectures and hiring teams of machine learning experts.



Natural language-driven services—such as search, sentiment analysis, listing generation, content monitoring, voice interactions, and chat—are crucial to enhancing the customer journey. Deep understanding at scale requires building, training, and tuning these complex models efficiently and cost-effectively.
A complete omnichannel customer approach brings valuable new insights but also creates a surge in new data to analyze. Conventional technologies struggle to consume this data and require organizations to decide which signals to use or ignore, compromising the accuracy of recommendations. Alternatively, building recommendation systems with complete omnichannel data and your unique offer catalog will improve shopper satisfaction and increase revenue.
Use Cases
Customer Experience

Natural language-driven services—such as search, sentiment analysis, listing generation, content monitoring, voice interactions, and chat—are crucial to enhancing the customer journey. Deep understanding at scale requires building, training, and tuning these complex models efficiently and cost-effectively.
High-Impact Personalization

A complete omnichannel customer approach brings valuable new insights but also creates a surge in new data to analyze. Conventional technologies struggle to consume this data and require organizations to decide which signals to use or ignore, compromising the accuracy of recommendations. Alternatively, building recommendation systems with complete omnichannel data and your unique offer catalog will improve shopper satisfaction and increase revenue.

As powerful as the latest AI innovations are, moving them to production consumes vast technology resources, requires an army of experts to scale and time to production is lengthy. To support a high volume of interactive users and provide them with exceptional experiences, retailers need access to highly scalable, low-latency production inference systems that deliver against SLAs at a fraction of the cost of conventional solutions.
Accelerated AI Solutions for Retail & E-Commerce
SambaNova provides next-generation recommendation and natural language platform solutions that help retailers enhance customer experiences, strengthen loyalty, and grow revenue.
SAMBANOVA SUITE
FOR RECOMMENDATION
Improve the accuracy of your predictions to deliver more personalized, meaningful information and content to your end-users.
SAMBANOVA SUITE
FOR LANGUAGE
Achieve breakthrough efficiency in NLP while you free up your machine learning talent to focus on higher-value initiatives.
Learn how SambaNova can help your company leverage AI to deliver personalized, meaningful customer experiences.