PilotEvidence: Medium55/100

Carrier uses Amazon Bedrock to help customers achieve sustainability goals

Carrier Global Corporation is using generative AI to scale its Abound Net Zero Management product for a global audience. Customers upload utility bills in local languages, which are extracted and processed to generate actionable energy-saving and emissions insights. The solution is in pilot and is intended to help customers manage energy consumption and reduce carbon footprints.

Published
May 2026

Reported outcomes

Strategic outcomes

New product / capabilityTurned utility bills into sustainability insightsMarket & geographic expansionScaled product for global audienceCustomer experience & trustHelped customers manage energy consumptionSustainability & ESGSupported carbon footprint reduction
Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks
Customer
Carrier Global Corporation
Provider
AWS
Maturity
Pilot

The solution is in pilot and is intended to help customers manage energy consumption and reduce carbon footprints

Customer identity supportedSource describes one deploymentMaturity supported

Primary read

Use case focus

Showing 3 of 3

  • 1Document processing
  • 2Sustainability analytics
  • 3Energy optimization
  • Carrier wanted to scale Abound Net Zero Management globally while handling diverse utility data across regions and languages.
  • The company needed to turn scanned utility bills into structured data that could be analyzed for sustainability insights.
  • Carrier uses Amazon Textract to extract text and data from uploaded utility bills.
  • It then passes the extracted text into a large language model on Amazon Bedrock to identify and populate relevant data points.
  • The solution combines the extracted data with historical trends and predictive analytics to generate customer insights.
  • The article says the solution is still in pilot phase.
  • Once commercially available, it is intended to support customers in reducing carbon footprints and optimizing energy usage.
Sources & evidence1
Evidence: Medium55/100Evidence strength
  • Customer explicitly identified
  • Deployment status explicitly supported
  • Primary source available
  • Technical implementation details available
Type: Customer StoryPublished: May 13, 2026Publisher: AWSEvidence: PrimaryConfidence: High

AI-generated summary. Verify important details with the linked sources before relying on this case.

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