Media, entertainment and sports companies shouldn't have to choose between the rapid innovation of AI and the security of their most sensitive data. As studios, streamers and investors increasingly rely on AI to evaluate high-stakes content, rights and distribution choices, their workflows often involve unreleased IP and proprietary strategies. Speed is essential - but so are privacy and governance.

Parrot Analytics solves this by pairing global intelligence with enterprise-grade safeguards. To deliver both lightning-fast insights and absolute data control, we have built our next-generation AI capabilities on AWS. In March 2026, Parrot Analytics named Amazon Web Services as its primary cloud provider for generative AI, seamlessly integrating Amazon Bedrock AgentCore and Amazon Nova across all products.

Faster intelligence when decisions cannot wait

In a published AWS case study following our AWS partnership announcement, Parrot Analytics’ audience demand signal classification workflow achieved three material improvements:

• 25 TPS sustained agentic throughput
• 20M tokens per minute
• 10x faster media signal processing

For Parrot Analytics customers, the value is not speed for its own sake: it is more current intelligence, shorter analysis cycles and an architecture able to keep pace with growing volumes of both structured and unstructured signals across film, television and sports. And what else? AI processing without contributing to shared model training.

AI processing without contributing to shared model training

A common concern is whether prompts, documents and outputs sent to a foundation model become training data. For Amazon Bedrock, AWS ensures that neither AWS nor third-party model providers use Bedrock inputs or outputs to train Amazon Nova, Amazon Titan or third-party models. AWS also states that user inputs and model outputs are not shared with model providers; read more here in the Amazon Bedrock FAQ.

In practical terms, information is processed to perform the requested task - known as inference - and Parrot Analytics’ use of Amazon Bedrock does not turn that information into material for training a shared foundation model or improving the base model for other customers.

This distinction is especially important where workflows involve commercially sensitive materials such as unreleased scripts, production plans, rights valuations, investment models, deal structures or proprietary strategy.

Through Amazon Bedrock, organizations maintain precise, account-level governance over inference data, including all prompts and model completions. Parrot Analytics utilizes Zero Data Retention (ZDR) configurations within its AWS environment and a multi-tenant infrastructure to separate customers' data in completely isolated environments.

This gives our customers the assurance that commercially sensitive inputs and outputs are never stored by AWS or disclosed to any third-party foundation model providers.

Under the AWS shared responsibility model, Parrot Analytics remains responsible for securely designing, configuring, operating and governing its applications.

Separation between model providers and customer data

AWS ensures that third-party models in Amazon Bedrock operate in AWS-managed Model Deployment Accounts. Model providers do not have access to those accounts, Amazon Bedrock logs, customer prompts or model completions. This creates an important separation between using a model and exposing customer data to the company that developed it.

For the agentic workflow described in the Parrot Analytics AWS case study, Amazon Bedrock AgentCore Runtime runs agents in isolated MicroVM environments, supporting secure execution at scale while the platform processes large volumes of signals.

See the Amazon Bedrock data protection documentation for the technical architecture behind this separation.

Certified AWS security and privacy controls

Amazon Bedrock and Amazon Bedrock AgentCore are included in the scope of AWS ISO/IEC certifications that cover information security, cloud-specific controls and privacy management:

• ISO/IEC 27001:2022 - an information security management system built around risk identification, treatment and continual improvement.
• ISO/IEC 27017:2015 - additional security controls and guidance for the provision and use of cloud services.
• ISO/IEC 27018:2019 - controls and guidance for protecting personally identifiable information in public-cloud environments.
• ISO/IEC 27701:2019 - a privacy information management framework extending the information security management system.

These certifications apply to AWS’s control environment and provide independent assurance regarding the information security, cloud security and privacy management systems supporting AWS services.

Review the current AWS ISO certifications and services in scope and the AWS shared responsibility model for more information.

What this means for our customers

By combining Parrot Analytics’ proprietary audience demand intelligence and industry expertise with enterprise AI services on AWS, we help clients move faster while maintaining control over the information that matters most.

Where directly applicable, the Parrot Analytics product terms of service clearly state that customer content will not be used to train, fine-tune, calibrate, validate or otherwise improve a general-purpose AI, large language model or generative AI system.

This results in:

• Control of sensitive intellectual property. Bedrock inputs and outputs are not used by AWS or model providers to train shared foundation models.
• A more transparent AI supply chain. AWS documents separation between model providers, deployment accounts, logs, prompts and completions.
• Enterprise-grade foundations. The underlying AWS services operate within an independently audited and certified security and privacy control environment.
• Human accountability. Parrot Analytics keeps expert judgement central, using AI to support rather than replace high-stakes decision-making.
• Faster, fresher intelligence. Shorter processing cycles help decision-makers work with insights closer to the market moment.

Read the AWS case study or speak with Parrot Analytics about applying enterprise AI to your content, rights and investment decisions.