AI R&D Enterprise Super Pack
Your team is under pressure to move from AI experimentation to production-ready systems, fast. This super pack from deepset, makers of Haystack, gives your R&D team the technical playbook to get there.
Three O'Reilly guides covering RAG architecture, enterprise LLM adoption, and NLP with Transformers cover everything you need to build AI systems that are trustworthy, scalable, and secure.
Why this matters for your team:
Most enterprise AI initiatives stall between proof-of-concept and production.
The gap isn't talent, it's architecture decisions, context engineering, and choosing the right framework before you've committed months of development time.
These guides give your team a shared reference point for the decisions that matter most: how to design retrieval pipelines that scale, how to evaluate LLM outputs systematically, and how to build language applications that meet enterprise security and compliance requirements.
What's inside:
Get three essential O'Reilly resources in one download:
1. Retrieval-Augmented Generation in Production with Haystack walks through building trustworthy, scalable RAG systems from the ground up.
2. LLM Adoption in the Enterprise provides a practical framework for moving from experimentation to meaningful GenAI products.
3. Selected chapters from Natural Language Processing with Transformers cover the foundational building blocks your team needs to build and fine-tune language applications with Hugging Face.
Featured Speakers
Disclaimer
Gartner Cool Vendors in AI Engineering, Arun Chandrasekaran, Manjunath Bhat, Arup Roy, George Brocklehurst, 6 November 2024
GARTNER is a registered trademark and service mark, and the GARTNER COOL VENDOR
badge and COOL VENDORS are trademarks and service marks, of Gartner, Inc. and/or its
affiliates in the U.S. and internationally and are used herein with permission. All rights reserved. Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.