Parrot Analytics scales smarter content intelligence with Amazon Bedrock AgentCore and Amazon Nova

Overview

Media analytics company Parrot Analytics built AI agents on Amazon Bedrock AgentCore with Amazon Nova 2 Lite to classify billions of unstructured audience demand signals, processing signals 10 times faster, cutting operational costs by 60%, and reducing manual verification by 85%.

The challenge

As media demand signal volumes grew across billions of unstructured audience data points spanning film, television, and sports content, manual classification and traditional ML approaches became costly and time-consuming; processing 10 million signals required up to 12 weeks of human verification and cost approximately $100,000 per batch, slowing analysis cycles as signal volumes grew.

The solution

Parrot Analytics implemented an agentic AI architecture on AWS using Amazon Bedrock AgentCore, an agent development platform, and Amazon Nova 2 Lite, a fast and cost-effective reasoning model, to automate metadata extraction and signal classification. AWS experts helped design and optimize the architecture; Amazon Bedrock AgentCore Runtime orchestrates agents across workflows in isolated MicroVM environments, interpreting unstructured inputs and automatically matching them to entities in the company's demand analytics system.

Reported business value

The new system processes media demand signals 10 times faster than previous methods, reduces operational costs by approximately 60 percent, and AI agents now handle approximately 85 percent of signal classification tasks, freeing engineering teams to focus on improving algorithms. Amazon Nova 2 Lite also lowered inference costs by up to five times versus Claude Haiku 4.5, and the platform now supports up to 25 transactions per second and 20 million tokens per minute.