Mistral
4 use cases using this technology
Zalando enhancies customer engagement and operational efficiency with Mistral
Zalando
Zalando, a European e-commerce platform, integrated Mistral models hosted on AWS Bedrock into its platform to add natural language processing and machine learning capabilities. The integration supports personalized recommendations, improved customer service and streamlined operations for the retailer's shopping experience.
Transforming the CX experience: How Cisco plans to cut renewal proposal time by 20%
Cisco
Cisco's Customer Experience organization partnered with Mistral to build the AI Renewals Agent, the first solution from a strategic partnership between the two companies. Account managers previously had to manually analyze more than 50 signals across structured and unstructured customer data to draft renewal proposals. The agent uses text-to-SQL across multiple platforms, keeping customer data on premise and scaling across Cisco's own GPU cluster, with Mistral's Applied AI team collaborating on fine-tuning. Cisco estimates the agent can cut time spent creating renewal proposals and preparing for customer engagements by up to 20%.
Austrian Academy of Sciences unlocks Ancient Greek with Mistral
Austrian Academy of Sciences
The Austrian Academy of Sciences (OeAW), together with its Austrian Archaeological Institute, partnered with Mistral and services partner Reply to build Apollo, described as the first advanced large language model for Ancient Greek. Apollo is trained on a specialized corpus of 600 million words of historical Greek text plus tens of thousands of published inscriptions and papyri, helping researchers reconstruct damaged texts and identify thematic connections across collections. The OeAW reports Apollo turns work that once took years into hours, addressing over one million unread Greek papyri worldwide, with future phases planned for semantic search and handwritten inscription decipherment.
Multitudes Builds Code Review Quality Feature in 2 Months Using 3 LLMs on Amazon Bedrock
Multitudes
Multitudes, a New Zealand-based engineering analytics startup, used Amazon Bedrock to build a code review quality feature, testing over 10 large language models across roughly 1,000 code reviews before choosing Amazon Nova Pro for bot detection, Anthropic Claude for feedback specificity and prompt-injection detection, and Mistral for sentiment analysis, orchestrated with Amazon Elastic Container Service. The feature increased monthly active users by 44 percent within two months of launch and reduced severe misclassification rates from 20 percent to under 1 percent.