A Sneak Peak into the Report

Sell, service, and support technical products and equipment? You might have a knowledge friction problem.

Field technicians, customer support agents, channel partners, and sales managers all need quick access to information to do their jobs effectively, ranging from maintenance tips to warranty policies. Yet, too often, hunting for this information is a struggle — in fact, 70% of knowledge workers spend an hour or more searching for a single answer.

Where generative AI can help

Generative AI solutions can uncover answers hidden inside technically rich content and deliver them where and when they're needed. But not just any GenAI tool will do. Businesses selling, servicing, and supporting engineered products often have a ton of complex, multimodal content that's continuously being refreshed and is scattered across a myriad of sources. In other words, your content isn't just hard to find, but also challenging for machines to understand. A GenAI solution capable of reading your content — including schematics and tables — just like a human can democratize access to trusted knowledge, streamline workflows, and improve decision-making.

Retrieval-augmented generation is the right way to implement GenAI to solve knowledge friction.

You can't afford to deliver incorrect or outdated information to your employees, partners, and customers. More and more businesses with revenue on the line are turning to retrieval-augmented generation (RAG) AI technology. With RAG, your trusted content (and only your trusted content) serves as the basis of generative outputs. That means the answers people receive are trustworthy, fact-based, and traceable to their sources.

4 key considerations for implementing RAG with technically rich content

How can you make sure you're implementing RAG right? Businesses with technically engineered products need to consider four critical factors when deploying RAG to solve knowledge friction:

  1. Accuracy: Can the RAG solution really understand your content?
  2. Security: Is your content safe from prying eyes and cyberthreats?
  3. Scalability: Can the RAG application manage high volumes of complex data and grow along with your needs?
  4. Speed: How quickly can you get up and running?

Learn what it takes to get RAG right

Implementing RAG in an enterprise setting, especially when your content is technical in nature, is easier said than done. Find out how to quickly unlock the value of GenAI for your employees, partners, and customers while ensuring high accuracy and security.