MANZ

Solution

MANZ , an Austrian company that provides information services for legal and tax professionals, sought to revolutionize how its registered users searched its vast repository of legal documents. With over 300 million documents in its database, MANZ aimed to implement a cutting-edge solution using vector embeddings to enhance similarity searches and uncover deeper connections between documents. In collaboration with AWS Partner tecRacer Consulting , MANZ developed and successfully deployed a powerful solution, which reduced deployment times and empowered MANZ to independently develop and refine its solution. Opportunity Searching for a Better Strategy for Finding Similar Documents As a high-profile provider of legal information in Austria, MANZ needed a robust system to efficiently and intelligently search through an enormous database of legal documents.

Data flow

MANZ wanted to avoid significant performance issues that can result in prolonged query times, so tecRacer worked closely with them to optimize their infrastructure by: Correctly sizing the OpenSearch cluster: Ensuring that the cluster was appropriately sized to handle large-scale document searches efficiently. Fine-tuning queries: By improving the search query logic and structure, the performance was enhanced significantly. To automate and streamline the deployment process, tecRacer delivered a production-ready setup using Terraform.