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AWS Consumer Goods United States

Chamberlain Group

CG wanted to get users connected as quickly as possible and chose Amazon Rekognition. Chamberlain Group (CG) wanted to expand the number of devices connected to its myQ app for monitoring and controlling garage doors.

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After initial testing, CG’s myQ solution using Amazon Rekognition was in production within 1 month, and the new features went live in November 2023.
CG, a global leader in intelligent access, was founded in 1954 and has products in more than 50 million homes across the United States.
Its myQ app has over 11 million users and counting, plus 8.4 million connected garage door openers.

Reported impact

Business outcome

Amazon Rekognition uses video images to determine whether the device can connect. “Anyone with a garage door opener, regardless of the brand, can scan it and connect it to our system,” says Jishnu Kinwar, vice president of advanced products at CG.

  • Customer Experience
  • Revenue Growth

Solution

Chamberlain Group (CG) wanted to expand the number of devices connected to its myQ app for monitoring and controlling garage doors. To meet this challenge, CG turned to Amazon Web Services (AWS) and added Amazon Rekognition —used to automate and lower the cost of image recognition and video analysis with machine learning—as middleware into myQ. Previously, customers had to search a list to see if their device could connect to the myQ app and then find and follow instructions to connect. CG wanted to get users connected as quickly as possible and chose Amazon Rekognition. “We already used AWS for our video and camera infrastructure,” says Benjamin Hunt, video, artificial intelligence, and middleware developer at CG.

Data flow

To meet this challenge, CG turned to Amazon Web Services (AWS) and added Amazon Rekognition —used to automate and lower the cost of image recognition and video analysis with machine learning—as middleware into myQ.

Solution architecture

1 components · 1 layer
  1. Serving
    • Amazon Rekognition Analyzes images and video to classify or identify physical devices.

Architecture clues

  • Amazon Rekognition uses video images to determine whether the device can connect.

Evidence from the source

CG wanted to get users connected as quickly as possible and chose Amazon Rekognition.
CG, a global leader in intelligent access, was founded in 1954 and has products in more than 50 million homes across the United States.
Its myQ app has over 11 million users and counting, plus 8.4 million connected garage door openers.
Previously, customers had to search a list to see if their device could connect to the myQ app and then find and follow instructions to connect.
With the myQ solution, residential customers can automatically open and close their garage door, schedule a time for their garage door to close, and record access events.
Transparency Evidence & methodology 61/100 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 value61/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth20/25
    Rewards named components, data flow, integrations, and architecture detail.
  • Outcome specificity16/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact0/25
    0 metrics describe measurable impact.
  • Deployment scale5/10
    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
    5 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

    Chamberlain Group customer story

    First-party
    https://aws.amazon.com/solutions/case-studies/chamberlain-group-case-study/
    Source type
    Vendor-published customer story
    Published
    Aug 5, 2024
    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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