In regulated industries, even a minor deviation from source data can have significant consequences. Imagine this scenario: a team relies on an AI model to summarize clinical research. The output appears accurate at first glance, but subtle inaccuracies—like paraphrasing that misrepresents data—are uncovered during expert review. For industries like healthcare or finance, such errors are unacceptable.
At Great Wave AI, we tackle this challenge by building specialized “agentic architectures.” Instead of a single AI model handling every task, we break the process into smaller, focused agents. One agent retrieves data, another formats it, and another validates the output. This modular approach ensures AI responses align strictly with the provided source material, instilling confidence in the technology and maintaining compliance.