legal_document_review · services · workflow
Unlocking enhanced legal document review with Lexbe and Amazon Bedrock
Legal professionals must analyze massive sets of case documents per matter; keyword searches return unwieldy result sets and fail to surface hidden evidence connections, making manual review time-consuming, error-prone, and costly.
How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · User submits legal query
A user accesses the frontend application through a web browser to query the case document corpus.
Tools used
Amazon BedrockAmazon Bedrock Knowledge BasesAmazon OpenSearchAWS FargateAmazon CloudFrontApache TikaTitan Text v2Amazon Bedrock Sonnet 3.5Amazon ECSLexbe Pilot
Outcome
After multiple iterations of collaboration with Amazon, Lexbe Pilot reached up to 90% Recall Rate, enabling polished findings-of-fact reports with source hyperlinks and deep automated inference across large multilingual document sets.
What failed first
The initial system iteration achieved only a 5% Recall Rate, far below production requirements, and traditional eDiscovery techniques could not surface hidden relationships or produce findings-of-fact reports.
Results
Volume5%
Cost replacedsignificant cost advantage
Grounding & classification
Source type: technical build writeup
37 fields verified against source quotes, 3 dropped as unverifiable.
document aienterprise searchragsummarizationemailknowledge basebuilder submittedfailure mode describedmetric backednamed customerproduction runtime claimedtools describedvendor confirmedworkflow describedlegalaccuracy improvementcost reductiontime savedtechnical build writeuplegal document reviewlegal opsdocument to recordrag answering