MetaLearner uses Meta's Llama 3.1 to make ERP systems like SAP and Oracle easier to work with.

Ipsos used Gemini 1.5 Pro and Flash to create an internal tool that allows market researchers to pull real-world data from Google Search for analysis.

Dun & Bradstreet created an AI search with Google’s Gemini to help customers with complex queries like "Find me all the companies in this area with a high ESG rating." They’ve also built an AI-powered email-generation tool that helps sellers create tailored, personalized communications to prospects and customers for its research services.

BigDataCorp, a data analytics and consulting firm from Brazil, uses Mistral AI models hosted on AWS Bedrock to enable client businesses to dive deeper into their data using natural language.

SAIF CHECK, a company based in Riyadh, Saudi Arabia, uses Meta's Llama 3 to develop a model evaluation system that assesses AI models for compliance with legal, regulatory, privacy, and data security standards. Utilizing a Retrieval Augmented Generation (RAG) framework, the system scans and integrates global regulatory environments into a comprehensive knowledge base, enabling conversational and context-aware evaluations for both technical and non-technical users. This enhances trust in AI models, streamlines the auditing and certification process, and ensures businesses in the Middle East and North Africa can deploy AI solutions confidently and compliantly.

Marketing and product teams at Amplitude use Perplexity to draft market landscape insights.

Databricks uses Perplexity Enterprise Pro to accelerate R&D, enabling its engineering, marketing, and sales teams to execute faster and more efficiently. The company estimates saving 5,000 working hours monthly.

Viable uses GPT-4 to analyze qualitative data from platforms like Zendesk and Intercom at scale, providing businesses with actionable insights to improve customer support, reduce churn, and optimize product roadmaps. The AI model fine-tunes analysis for unstructured data, offering context-rich insights that surpass traditional summarization tools.

MongoDB extends Mistral's performance and efficiency from the model layer to the data layer by securely unifying application data, metadata, and vector embeddings in a single platform. Developers can create rich, real-time AI applications across various use cases, from conversational AI to complex reasoning, gaining a competitive edge by building with Mistral AI and MongoDB.

ML Commons has integrated Meta's Llama 2 70B parameter model into version 4.0 of its MLPerf Inference benchmark. The published results demonstrate the performance potential of various platforms for running one of the most demanding and capable large language models, highlighting the efficiency and scalability of Meta’s Llama 2 in high-performance computing environments.

Superinsight, a data analytics company, integrated Mistral AI on AWS Bedrock to enhance its data analytics capabilities. This provides clients with powerful tools to unlock the full potential of their data, delivering cutting-edge AI capabilities.