Document Processing · Enterprise Knowledge Search · Marketing Personalization · Real-time Analytics · System Migration
To develop AI models for its solution, the company fine-tuned open-source large language models such as Llama2 7b from Hugging Face with its own datasets and used Amazon SageMaker , a fully managed service that brings together a broad set of tools to provide high-performance, low-cost machine learning. “Using Amazon SageMaker, we can manage, develop, test, and deploy our AI models efficiently,” says Arnaud de La Bédo
Reported impact
Generative artificial intelligence (AI) capabilities are evolving daily, requiring companies to rapidly adapt to recent advances. Daxte used this new technology to create LegalMap —one of the first French generative AI solutions for legal documents.
Generative artificial intelligence (AI) capabilities are evolving daily, requiring companies to rapidly adapt to recent advances. Daxte used this new technology to create LegalMap —one of the first French generative AI solutions for legal documents. To develop AI models for its solution, the company fine-tuned open-source large language models such as Llama2 7b from Hugging Face with its own datasets and used Amazon SageMaker , a fully managed service that brings together a broad set of tools to provide high-performance, low-cost machine learning. “Using Amazon SageMaker, we can manage, develop, test, and deploy our AI models efficiently,” says Arnaud de La Bédoyère, founder of Daxte. In 2023, Daxte worked with Data Reply France , an AWS Partner , to optimize training costs by migrating from GPU resources to AWS Trainium , a high-performance machine learning training accelerator, and AWS Inferentia , which provides accelerators designed to
Daxte Using Amazon Textract for Accurate Document Scanning Daxte was founded in 2022 and created a generative AI solution, LegalMap, that helps search for information in French legal documents.
Daxte used this new technology to create LegalMap —one of the first French generative AI solutions for legal documents.
Generative artificial intelligence (AI) capabilities are evolving daily, requiring companies to rapidly adapt to recent advances.
LegalMap, built on Amazon Web Services (AWS), combines high accuracy, inference performance, scalability, and reliability in a single solution.
The solution finely filters searches and systematically sources answers from millions of documents.
To develop AI models for its solution, the company fine-tuned open-source large language models such as Llama2 7b from Hugging Face with its own datasets and used Amazon SageMaker , a fully managed service that brings together a broad set of tools to provide high-performance, low-cost machine learning. “Using Amazon SageMaker, we can manage, develop, test, and deploy our AI models efficiently,” says Arnaud de La Bédo
Review how this reference was scored and trace each normalized claim back to its documented source.
Scoring methodology
Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.
Traceability
Field coverage shows which facts each source supports. Dates are shown only when documented by the source.
The profile lists the registered office in Senlis, France and does not expose a numeric employee count.
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