AWS Media and Entertainment Global

NAGRA

Marketing Personalization · Real-time Analytics · Security and Compliance

Using AWS and services such as Amazon Bedrock means both faster development of new services and features, and the ability to ramp up to meet demand. “Working with AWS gives us the certainty that we’re able to scale to millions and even tens of millions of conversations as required,” says Pearson. “And it helps us accelerate our time to market.

Its customers include content providers, pay-TV operators, and telcos, who choose NAGRA to protect their content and investments, and help them harness new technology in a fast-paced environment. “Working with over 500 customers and 400 million devices that are using our technology every day gives us a huge amount of data—and that data we use to identify with our customers how we can best maximize their revenues and reduce churn,” says NAGRA’s vice president of global solution and partner marketing Tim Pearson. “We’re currently looking at how we can infuse generative AI into our broad solution portfolio across content security, streaming solutions, and consumer loyalty.” Picking the Right Models Specifically, NAGRA has been using Amazon Bedrock—the easiest way to build and scale generative AI applications with foundation models—and Anthropic Claude 3 to develop a customer service solution.
The company found that 60 percent of client call center traffic was related to billing queries, which was perfect territory, according to Pearson, for a generative AI solution to support customers across voice and chat. “Amazon Bedrock has given us a whole range of generative AI capability to add to our customer solutions.

Reported impact

Business outcome

Vice President of Global Solution and Partner Marketing, NAGRA Organizations of all sizes across all industries are transforming their businesses and delivering on their missions every day using AWS. Contact our experts and start your own AWS journey today.

  • Revenue Growth
  • Risk Reduction
  • Scalability
  • Speed to Market

Solution

Content security and customer loyalty solutions provider NAGRA works with media and entertainment (M&E) organizations and telecoms operators around the world. Using Amazon Web Services (AWS) and generative artificial intelligence (AI), it helps clients improve processes, reduce churn, and ultimately increase revenue. The company found that 60 percent of client call center traffic was related to billing queries, which was perfect territory, according to Pearson, for a generative AI solution to support customers across voice and chat. “Amazon Bedrock has given us a whole range of generative AI capability to add to our customer solutions. Its customers include content providers, pay-TV operators, and telcos, who choose NAGRA to protect their content and investments, and help them harness new technology in a fast-paced environment. “Working with over 500 customers and 400 million devices that are using our technology every day gives us a huge

Solution architecture

2 components · 2 layers
  1. Compute
    • Amazon Bedrock Runs core compute or model execution for the security analytics workload.
  2. Uncategorized
    • Anthropic Claude Runs core compute or model execution for the security analytics workload.

Evidence from the source

Contact our experts and start your own AWS journey today.
Innovation is and will always remain core to NAGRA, and working with strategic partners such as AWS will remain a key part of our strategy going forward.” Learn more about Nagra's Insight Negotiation Agent Amazon Bedrock has given us a whole range of generative AI capability to add to our customer solutions.
Its customers include content providers, pay-TV operators, and telcos, who choose NAGRA to protect their content and investments, and help them harness new technology in a fast-paced environment. “Working with over 500 customers and 400 million devices that are using our technology every day gives us a huge amount of data—and that data we use to identify with our customers how we can best maximize their revenues and reduce churn,” says NAGRA’s vice president of global solution and partner marketing Tim Pearson. “We’re currently looking at how we can infuse generative AI into our broad solution portfolio across content security, streaming solutions, and consumer loyalty.” Picking the Right Models Specifically, NAGRA has been using Amazon Bedrock—the easiest way to build and scale generative AI applications with foundation models—and Anthropic Claude 3 to develop a customer service solution.
The fast-evolving LLMs give us access to all sorts of new and evolving technology.
Using AWS and services such as Amazon Bedrock means both faster development of new services and features, and the ability to ramp up to meet demand. “Working with AWS gives us the certainty that we’re able to scale to millions and even tens of millions of conversations as required,” says Pearson. “And it helps us accelerate our time to market.
Vice President of Global Solution and Partner Marketing, NAGRA Organizations of all sizes across all industries are transforming their businesses and delivering on their missions every day using AWS.
Transparency Evidence & methodology 70/100 reference value · 88% confidence · 2 sources

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 value70/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth10/25
    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 impact15/25
    1 metric describe measurable impact.
  • Deployment scale5/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence88%
  • Source authority20/25
    The main evidence is an official vendor-published customer story.
  • Claim traceability23/25
    11 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 transparency9/10
    2 source references 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

    NAGRA customer story

    First-party
    https://aws.amazon.com/solutions/case-studies/nagra-generative-ai/
    Source type
    Vendor-published customer story
    Published
    Jul 1, 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
  2. Kudelski Group

    Kudelski Group Careers | Welcome

    First-party
    https://careers.nagra.com/

    The page says, "With more than 1900 employees worldwide, 24 locations around the world and 3 business units, the Kudelski Group offers endless opportunities".

    Source type
    Official careers page
    Supports
    • Company size

Date evidence

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