It cannot compare data from multiple businesses or systems, especially for long-term analysis.

Chat-based AI focuses on extracting what's in the data but lacks the ability to deliver deeper, actionable insights about the data itself.

It struggles to execute multi-step workflows (e.g., processes with 20+ steps), limiting its ability to support comprehensive tasks.

Analyzing large documents that exceed its context window is challenging, leading to incomplete or inaccurate insights.

The system is ill-equipped to analyze extensive datasets, such as 10,000 documents, in a cohesive manner.

It doesn't improve or adapt based on feedback or usage patterns, resulting in static performance over time.

Chat-based AI often lacks the capability to connect disparate data points and generate personalized or context-specific recommendations for complex scenarios.

These systems frequently fail to seamlessly integrate with multiple platforms or data sources, restricting their ability to work in a broader ecosystem.