Advanced RAG with Command R

Greetings Cohere Community,

In a recent video, Greg Pavlik, SVP of AI at Oracle, spoke about working with Cohere and building “practical AI that helps customers solve actual business problems.”?

But what does AI for enterprise really look like?

1. It starts with RAG (retrieval-augmented generation). According to Pavlik, “RAG, [provides] more accurate, trustworthy, and contextually grounded results for business users.” This means moving away from general-purpose models to models like Command R that use enterprise data as the source of truth. Check out Cohere CEO Aidan Gomez discussing this very subject with global tech expert Azeem Azhar in The Year of Scaling AI .?
2. It delivers performance at every step in production. Businesses need future-proof technology. For enterprise AI, that means scalable solutions that can process large volumes of data fast and at low cost. Models that deliver:?Enhanced accuracy. Businesses can’t afford the risk of model hallucinations. More accurate solutions, like Command-R include source citations to mitigate against the risk of hallucinations. Powerful retrieval. Optimized to reduce memory costs with compressed embeddings and improve relevance, our Embed and Rerank models work alongside Command-R to deliver best-in-class RAG solutions.?Optimized inference. Pat Lee, head of Strategic Enterprise Partnerships at NVIDIA, recently stated : “Optimized inference is essential for production AI, and Cohere’s models available as NVIDIA NIM microservices can help enterprises scale their AI deployments to drive transformation.”?
3. It is versatile. Choosing an AI model no longer has to dictate your entire technology stack. Enterprise AI requires models and systems that are flexible and universally available. Cohere works with all major cloud providers, as well as on-prem for regulated industries and privacy-sensitive use cases. More recently, we announced our models will also be available via Nvidia’s enterprise platform .?
4. It is easy to use and easy to onboard. For quick adoption and ongoing experimentation, you want tools made with developers in mind. From simple visual dashboards that help you fine-tune the models and track costs, to Tool Use that helps you chain LLM systems and automate function calling, consider models and platforms that make it easier for your engineering teams to deliver. Enterprise AI also means upskilling and training professionals on AI development. LLM University offers a broad AI curriculum to get started fast.?
5. It is safe. From board members to developers, privacy and security are at the forefront of everyone's priorities. Understanding the best practices for responsible AI deployment requires strong technology partners willing to collaborate and learn. We recently released Command R weights with Cohere For AI to give researchers worldwide better access and visibility, so they can study these models for the benefit of all.?
6. It addresses real business problems . AI's true value for companies lies in mastering its use: from transforming legacy systems like search , to innovating with AI-driven knowledge assistants, and accelerating data-driven decision-making on a global stage and across multiple languages. Gain a market edge with AI by focusing on creating real value, training teams, and managing data wisely.

Our customers are looking to increase efficiencies, improve decision-making and access to data, and deliver better customer experiences. We're committed to turning these goals into reality by building enterprise solutions designed for production scale. Let us know how we can help. ?

For more, check out our latest articles or read on for this month’s highlights and upcoming events!

Product?

Introducing Command R , a generative model for RAG use cases to enable production-scale AI for enterprise. It balances efficiencies with performance and leads the way in a new generation of scalable, production-grade models.

For Business

Our latest model, Command R, is coming to the recently launched NVIDIA API catalog , delivering powerful AI software for enterprise customers.?

Developers

We are making it easier to build better, faster, and more efficient solutions. Check out our new compressed embeddings and embed jobs capabilities for more efficient and accurate search and retrieval. And try out function calling with LLMs using our newly released Tool Use . Plus, coming soon is our multi-hop Tool Use. If you want to join the beta, please reach out!

Research

Cohere For AI released the weights for Command R publicly, so that the model can be used for research purposes. This is part of a wider effort to support the machine learning ecosystem alongside research compute grants and open-source research releases like Aya .?

Company

Cohere is working with Accenture to provide businesses with generative AI solutions powered by Cohere’s models to accelerate how we can help companies incorporate AI into their operations at scale, prioritizing privacy and security.?

Upcoming events with Cohere?

• April 9 [Online]: Cohere For AI will be hosting Hugging Face fellow Johannes Kolbe as he explores the application of deep learning techniques in computer vision.
• April 9 [Las Vegas]: Cohere will be at Google Cloud Next ‘24 . Hear from Dwarak Talupuru, Machine Learning Engineer, in his lightning talk that spotlights the innovative use of Google Cloud TPUs in training models.?
• April 17 [Online]: Join Cohere For AI in conversation with Saquib Sarfraz, AI and ML expert working as Lead of Deep Learning at Mercedes-Benz Tech Innovation . The talk will look at clustering structures within large-scale unlabeled data.?
• April 25 [Online]: Join Cohere For AI and the ML Theory Group as they welcome Google Deepmind’s Petar Veli?kovi?, who will present recent work on Categorical Deep Learning , a more general theory of unified architectures.

For all upcoming events, explore cohere.com/events .?