Retail and eCommerce GenAI Modernization Assessment on AWS
Compass UOL · Customer Service
Certification per AWS Marketplace.
Evidence tier Source Confirmed · 4 captures on record
What the publisher says
As described on AWS Marketplace.
Retail and eCommerce organizations are rapidly adopting generative AI to improve customer experience, optimize product discovery, automate content creation, and increase conversion rates. However, these initiatives often evolve in silos across marketing, digital commerce, and operations teams, resulting in inconsistent experiences, duplicated tooling, and limited scalability.
Without a unified architecture, retailers struggle to operationalize GenAI across key use cases such as product description generation, personalized recommendations, search optimization, and customer engagement, leading to missed revenue opportunities and increased operational costs.
Show the rest of the publisher’s description (30 more lines)
Compass UOL helps retailers assess and modernize their GenAI landscape on AWS by identifying fragmentation across commerce platforms, customer data, and AI workloads. This assessment defines a scalable, AWS-native architecture that connects data, personalization engines, and GenAI services such as Amazon Bedrock.
The result is a structured roadmap to scale GenAI across digital commerce channels, improve conversion rates, reduce manual content operations, and enable real-time personalized shopping experiences while increasing AWS consumption in a controlled and efficient way.
Buyer Problem / Business Trigger
Fragmented GenAI initiatives across marketing, eCommerce, and customer experience platforms
High manual effort in product catalog creation, content generation, and campaign execution
Low conversion rates due to weak personalization and product discovery experiences
Difficulty scaling GenAI across omnichannel commerce environments
Delivery Model
Discovery of current GenAI use cases and digital commerce workflows
Assessment of data, customer platforms, and AI architecture
Definition of AWS-native GenAI reference architecture
Roadmap for scaling personalization and automation
Assessment / Engagement Scope
Evaluation of eCommerce workflows (catalog management, search, recommendations, campaigns)
Mapping of GenAI use cases (product content generation, personalization, chat commerce)
Assessment of customer data platforms and analytics pipelines
Review of scalability, latency, and cost of AI workloads
Design of AWS-native architecture (Bedrock, data lake, personalization services)
Identification of inefficiencies, fragmentation, and missed automation opportunities
Expected Output / Deliverables
GenAI modernization assessment report
AWS reference architecture for retail GenAI workloads
Prioritized use case roadmap aligned to revenue and conversion impact
Recommendations for cost optimization and operational efficiency
Implementation roadmap for scaling GenAI across commerce channels
Customer Decision Questions
This offer helps the customer answer:
How do we scale GenAI across eCommerce and customer experience without fragmentation?
Which AWS architecture enables real-time personalization and search optimization?
Where can GenAI improve conversion rates and reduce operational effort?
Highlights
Highlighted by the publisher on AWS Marketplace.
Scales GenAI across customer experience, Reduces tool fragmentation and cost, Improves CX consistency, Defines production AWS architecture
Agent build and provenance
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The layer-by-layer build, the evidence behind each claim, the risk basis and the cross-marketplace links are open to any account. Some rows are disclosed, some the source leaves Unknown; a free account shows you which.
Sources
Linked repositories
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