Top 10: AI Platforms for Retail

AI platforms are transforming retail by enabling businesses to understand and predict customer behaviour at scale. 

They allow retailers to personalise product recommendations, optimise pricing and forecast demand more accurately, improving both sales and operational efficiency.

By automating routine tasks such as inventory management and customer support, AI platforms free teams to focus on strategy and creativity, helping brands deliver seamless, data-driven shopping experiences that increase loyalty and drive long-term growth.

Here, AI Magazine takes a look at the Top 10 AI platforms which are perfectly suited to the retail sector.

10. Hello Retail

Hello Retail focuses on AI-driven personalisation for e-commerce and online retail environments. Its platform applies machine learning to product discovery, search and recommendation engines, helping retailers tailor digital storefronts to individual shoppers. 

With tools for personalised emails, category pages and on-site merchandising, the platform allows brands to optimise the entire product discovery journey. 

Hello Retail’s emphasis on cookieless personalisation also aligns with growing privacy expectations and changing data regulations.

9. ada CX

Founded: 2016
Employees: ~500
CEO: Mike Murchison

Ada delivers AI-powered customer service automation used widely across e-commerce and retail brands. Its platform enables businesses to deploy AI agents that handle customer queries across channels including chat, messaging and web interfaces.

Retailers use Ada to resolve common service requests, manage returns or provide order updates without human intervention. 

By automating large volumes of interactions, the platform helps organisations scale support operations while maintaining fast response times and consistent brand experiences.

8. ViSenze (Rezolve Ai)

Founded: 2012
Employees: 50+
CEO: Daniel Wagner (Rezolve Ai)

ViSenze specialises in AI-driven visual search and product discovery technologies designed for e-commerce and retail environments. Its platform enables shoppers to search for products using images rather than keywords, bridging the gap between inspiration and purchase. 

Retailers deploy ViSenze to power visual search, automated product tagging and recommendation engines. 

By transforming images into structured data, the company helps brands deliver more intuitive discovery experiences and improve conversion rates across digital storefronts.

7. Blue Yonder

Founded: 1985
Employees: ~8,000
CEO: Duncan Angove
Revenue: US$1.42bn

Blue Yonder delivers AI-driven solutions that help retailers optimise inventory, pricing, demand forecasting and supply chain operations.

Predictive analytics enable companies to reduce waste, improve in-stock availability and respond quickly to changing consumer behaviour. 

By integrating AI across merchandising, replenishment and planning processes, the platform empowers retailers to enhance operational efficiency, make data-driven decisions and provide seamless shopping experiences that strengthen customer satisfaction and loyalty.

6. Oracle Cloud for Retail

Founded: 1977
Employees: ~162,000
CEOs: Clay Magouyrk and Mike Sicilia
Revenue: US$57.4bn

Oracle Cloud for Retail combines cloud infrastructure, data analytics and AI to support large retail operations. The platform provides capabilities spanning merchandising, inventory management, supply chain optimisation and customer insights. 

AI models help retailers forecast demand, automate replenishment and optimise pricing strategies. 

By integrating operational and transactional data within Oracle’s cloud environment, the platform enables retailers to respond faster to shifts in consumer behaviour and supply chain conditions.

5. Agentforce Commerce (Salesforce)

Founded: 1999
Employees: 83,000+
CEO: Marc Benioff
Revenue: US$41.5bn

Agentforce Commerce represents Salesforce’s push into agentic AI for digital commerce. Built on Salesforce’s broader data and CRM ecosystem, the platform enables autonomous AI agents to assist with merchandising, marketing and customer engagement tasks.

Retailers can deploy AI assistants to analyse shopper data, generate product recommendations or automate marketing campaigns.

By combining generative AI with unified customer data, Agentforce Commerce helps brands deliver more responsive and personalised shopping experiences across digital channels.

4. IBM watsonx

Founded: 1911
Employees: ~300,000
CEO: Arvind Krishna
Revenue: US$67.5bn

IBM watsonx is a generative AI and data platform designed to help enterprises build, train and govern AI systems at scale. 

In retail environments it supports use cases such as demand forecasting, product content generation and supply chain optimisation. 

The platform combines foundation models, data governance tools and development environments that allow retailers to integrate AI into existing operations while maintaining compliance and transparency.

3. Microsoft Dynamics 365

Founded: 1975
Employees: ~228,000
CEO: Satya Nadella
Revenue: US$281.7bn

Microsoft Dynamics 365 brings together CRM and ERP capabilities with advanced AI services from Microsoft’s broader ecosystem. 

For retailers, the platform enables unified customer profiles, predictive demand planning and AI-driven marketing insights. Integration with Azure AI and generative tools such as Copilot allows organisations to automate tasks ranging from product descriptions to inventory analysis. 

The result is a data-centric retail platform capable of connecting customer engagement, operations and analytics.

2. Google Cloud

Founded: 2008
Employees: ~200,000 (Google)
CEO: Thomas Kurian
Revenue: US$402.84bn (Alphabet)

Google Cloud has become a major platform for retailers seeking to embed machine learning and generative AI into digital commerce, marketing and supply chain operations. 

Built on Google’s deep expertise in data infrastructure and AI, the platform offers a wide range of tools including Vertex AI, large language models and advanced analytics services. Retailers use these capabilities to analyse vast datasets, forecast demand and personalise customer journeys across online and in-store channels.

Google’s retail solutions also integrate search, recommendation engines and conversational AI, allowing brands to deliver more intuitive product discovery experiences. Gen AI capabilities enable automated product content creation, smarter merchandising and real-time customer engagement through chatbots and virtual assistants. 

With its global cloud infrastructure and growing ecosystem of partners, Google Cloud AI provides retailers with the scalability and flexibility required to innovate rapidly in an increasingly digital and data-driven retail landscape.

1. AWS

Founded: 2002
Employees: ~143,000
CEO: Matt Garman
Revenue: US$128.7bn

Amazon Web Services (AWS) remains the dominant cloud platform underpinning AI innovation across the retail sector. 

With a vast portfolio of machine learning and generative AI services, AWS enables retailers to build intelligent applications that improve forecasting, personalisation and operational efficiency. Services such as Amazon SageMaker, Bedrock and specialised retail data solutions allow companies to train and deploy AI models at scale while integrating them directly into e-commerce platforms and supply chain systems.

Retailers also benefit from AWS’ deep experience in high-volume commerce environments, shaped by Amazon’s own retail operations. The platform supports advanced analytics for demand forecasting, inventory optimisation and pricing strategy, while Gen AI tools enable automated product descriptions, marketing content and conversational customer service. 

Combined with its global infrastructure and extensive partner ecosystem, AWS provides retailers with the technological foundation required to experiment with AI and scale innovations across complex, multinational operations.