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AWS Retail United States

Tapestry

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For luxury retailers, understanding customer preferences and empowering frontline staff can make the difference between a thriving brand and one that falls behind. Tapestry , the parent company of iconic brands like Coach, faced a critical challenge: how to efficiently gather, synthesize, and act upon feedback from thousands of store associates.

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1 year
10 times
10x faster development of generative AI solutions
30,000 pieces of feedback collected in 1 year

Reported impact

Business outcome

Tell Rexy and Ask Rexy have helped Tapestry bridge the gap between in-store knowledge and corporate decision-making, ultimately contributing to a more productive workforce and improved customer experience. “Using AWS, we’re generating the kinds of insights that help our teams to be even more successful,” says Chandak. With the generative AI engine in place, the retailer is poised to build upon this success.

  • Customer Experience
  • Productivity Improvement
  • Speed to Market

Solution

For luxury retailers, understanding customer preferences and empowering frontline staff can make the difference between a thriving brand and one that falls behind. Tapestry , the parent company of iconic brands like Coach, faced a critical challenge: how to efficiently gather, synthesize, and act upon feedback from thousands of store associates. Tapestry’s engineering team used close to 20 AWS services to develop a generative AI engine that can be used to build various applications for both its retail stores and corporate offices. Amazon Bedrock —a fully managed service that offers a choice of high-performing foundation models from leading AI companies—serves as the foundation, hosting the large language model that powers the engine’s generative AI capabilities. As of October 2024, the team has built two applications: Tell Rexy and Ask Rexy.

Solution architecture

3 components · 2 layers
  1. Ingest
    • Amazon Transcribe Converts audio into text for search, analysis, or summarization.
  2. Compute
    • Amazon Bedrock Hosts the foundation models and generative AI application logic.
    • Amazon Translate Translates content into additional languages for localized experiences.

Architecture clues

  • And with the chatbot feature, we’ve also empowered our stakeholders internally to gather relevant insights.
  • Ask Rexy is a chatbot that lets corporate analysts at Tapestry query and gain insights from the collected feedback data.

Evidence from the source

Amazon Bedrock —a fully managed service that offers a choice of high-performing foundation models from leading AI companies—serves as the foundation, hosting the large language model that powers the engine’s generative A
For luxury retailers, understanding customer preferences and empowering frontline staff can make the difference between a thriving brand and one that falls behind.
Tapestry , the parent company of iconic brands like Coach, faced a critical challenge: how to efficiently gather, synthesize, and act upon feedback from thousands of store associates.
Tapestry is a global house of brands, including Kate Spade New York and Coach.
Tapestry’s engineering team used close to 20 AWS services to develop a generative AI engine that can be used to build various applications for both its retail stores and corporate offices.
The company employs over 18,000 people, many of whom are frontline retail associates who work directly with customers.
Transparency Evidence & methodology 90/100 reference value · 85% confidence · 1 source

Review how this reference was scored and trace each normalized claim back to its documented source.

01

Scoring methodology

How scores are calculated

Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.

Customer reference value90/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth15/25
    Rewards named components, data flow, integrations, and architecture detail.
  • Outcome specificity20/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact25/25
    2 metrics describe measurable impact.
  • Deployment scale10/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence85%
  • Source authority20/25
    The main evidence is an official vendor-published customer story.
  • Claim traceability21/25
    10 of 12 key fields link to a named source.
  • Direct evidence20/20
    6 direct source quotes retained.
  • Date provenance8/10
    The publication date comes from publisher-controlled metadata.
  • Source transparency8/10
    1 source reference document publisher, URL, authority, retrieval, and supported fields.
  • Implementation specificity8/10
    Rewards source-backed components, data flow, quantified impact, and a specific outcome.
02

Traceability

Sources & provenance

Field coverage shows which facts each source supports. Dates are shown only when documented by the source.

  1. AWS

    Tapestry customer story

    First-party
    https://aws.amazon.com/solutions/case-studies/tapestry-generative-ai-case-study/
    Source type
    Vendor-published customer story
    Published
    Jan 8, 2025
    Supports
    • Customer
    • Business problem
    • Solution
    • Products
    • Solution components
    • Data flow
    • Integrations
    • technical area
    • use case category
    • Business outcome
    • outcome category
    • Metrics
    • Architecture
    • evidence quotes
    • Publication date

Date evidence

Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.

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