Without a reliable data access layer that integrates context-aware data streams into AI workflows, even advanced models will produce inconsistent results.
LLMs operate on static training data, making them unreliable for enterprise use cases requiring current information. Organizations deploying AI agents for financial due diligence, procurement, and competitive intelligence need a real-time web intelligence layer with controlled retrieval, structured extraction, and governance to enable production deployments without compliance risk.
by Uri Knorovich
opinion
Aug 13, 20267 mins
A growing sentiment in tech is that large AI model providers will eventually replace traditional software vendors.
The argument makes some sense. If a model can write code, answer questions, and automate workflows, then over time it should be able to take on the functionality of thousands of existing applications. Why maintain a fragmented stack of software tools and solutions when a single intelligent system can do it all?
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