Systems | Development | Analytics | API | Testing

For years, QA practices were designed for predictable, rules-based software. AI has upended that reality by introducing risks that traditional methods cannot fully address.

The promise of AI breaks down when testing focuses only on idealized inputs. Real users ask incomplete questions, switch languages mid-thread, or provide contradictory details that models must still handle.

When it comes to accessibility, there are a lot of vendors and each is unique and credible in its own way.

We put two of the most talked-about models head-to-head in a real-world RAG scenario, and the results might surprise you. Hemraj Bedassee , Delivery Excellence Practitioner,