Web data infrastructure and knowledge layers for reliable real-time AI agents
Build a data layer that gives LLMs and AI agents fresh, reliable, structured web context at inference time instead of relying only on frozen training data. The infrastructure scrapes and processes public web data, then supplies it to a knowledge layer that grounds agent answers in current information.
From IBM Technology — Why Does AI Need Access to the Web? at 05:19
Problem: Pre-trained models do not know about changes after training, such as new products, prices, laws, news, inventory, or business closures. Without reliable live context, agents can hallucinate, propagate incorrect decisions across multiple agents, and act on outdated or fabricated information.
For: Companies building AI agents and AI tools that need current web information, including electronics purchasing systems, shopping price-comparison agents, marketing agents, and finance agents.
Examples
- An AI agent advising an electronics company on purchasing decisions could hallucinate a new phone and recommend buying components, creating a potentially costly mistake.