LLMs sometimes generate “hallucinations”—outputs that may sound plausible but are factually incorrect or misleading. If employees rely on these hallucinated responses for decision-making, it can lead to costly mistakes, operational inefficiencies, or even legal liabilities. For example, an LLM might fabricate a statistic or misinterpret a legal requirement, leading to incorrect conclusions.

Detecting hallucinations is difficult because the LLM outputs often appear coherent and accurate. Without safeguards in place, organizations might unknowingly incorporate incorrect information into their workflows, damaging their credibility and decision-making processes.

CalypsoAI mitigates hallucinations by providing pass/fail template instructions to its models, ensuring that outputs meet specific accuracy thresholds. By incorporating robust validation methods into the LLM workflow, CalypsoAI helps organizations avoid the risks associated with hallucinations and ensures that only reliable, verified information is used in decision-making processes.