Part 9/12:

By tracking metrics like execution times, error rates, and success patterns, the system continuously improves, becoming more reliable and cost-effective over time.

Visualization & Explainability

Final outputs are not mere raw data; they're visualized via embedded Python code interpreters, producing charts with detailed annotations. Users receive step-by-step explanations and intermediate results—fostering trust and transparency, crucial in regulated industries like pharma.

Deployment and Scaling

The solution's deployment journey was swift:

• POC Development: Two weeks.

• Pilot Phase: Extended over a few months with initial 20 users.

• Scaling: Achieved from 20 to 700 users over six months, with 70% user satisfaction.