GUIDE · CODING · #2747
Build a citation-backed financial research assistant using Cohere and Anthropic on AWS
A CloudFormation-based demo shows how to build a financial research assistant on AWS that combines Cohere Embed, Rerank, and Parse with Amazon SageMaker AI, OpenSearch Serverless, and Amazon Bedrock (Anthropic Claude for answers). The guide explains using Embed Pro/Fast and Rerank Pro/Fast, Context Focus, and Parse to index page-level content (including tables and scanned pages) and produce citation-backed answers while trading off retrieval quality, latency, and cost.
KEY POINTS
- A CloudFormation-based demo shows how to build a financial research assistant on AWS that combines Cohere Embed, Rerank, and Parse with Amazon SageMaker AI, OpenSearch Serverless, and Amazon Bedrock (Anthropic Claude for answers).
- The guide explains using Embed Pro/Fast and Rerank Pro/Fast, Context Focus, and Parse to index page-level content (including tables and scanned pages) and produce citation-backed answers while trading off retrieval quality, latency, and cost.
- It gives a concrete, deployable pattern for combining vector search, reranking, OCR/table parsing, and LLM answers with page-level citations—useful for enterprise financial workflows that need verifiable sources and cost/latency controls.
WHY IT MATTERS
It gives a concrete, deployable pattern for combining vector search, reranking, OCR/table parsing, and LLM answers with page-level citations—useful for enterprise financial workflows that need verifiable sources and cost/latency controls.