Pair Nova 2 Lite with Claude for cost-optimized document processing
AWS + Anthropic just showed how to cut document processing costs in half. Here's the two-model playbook.
Why it matters
AWS and Anthropic demonstrated a practical multi-model architecture for enterprise document digitization, showing how pairing lightweight models (Nova 2 Lite) with reasoning-capable models (Claude Sonnet) reduces costs while maintaining accuracy. This signals a shift toward cost-optimized model stacking for real-world workflows.
The key facts
9 to knowAmazon Nova 2 Lite handles multimodal extraction in single call
Claude Sonnet 4.6 performs spatial reasoning for name-to-face matching
Two-model pipeline deployed on Amazon Bedrock
Use case: yearbook page digitization at scale
Focus on cost optimization through model pairing
Published on AWS ML blog (credible first-party source)
Amazon Nova 2 Lite handles native multimodal extraction (photo detection, name extraction with coordinates, metadata)
Pipeline deployed on Amazon Bedrock
Cost-optimization focus via two-model orchestration
Go to the source
AWS Machine Learning Blogaws.amazon.com
Publisher excerpt: In this post, we show how pairing Amazon Nova 2 Lite with Anthropic’s Claude Sonnet 4.6 delivers an efficient solution for digitizing scanned documents at scale. We built a two-model pipeline on Amazon Bedrock for digitizing scanned yearbook pages. Amazon Nova 2 Lite handles native multimodal…