Nishan Portoyan: AI-Driven Quality Optimization Strategies
summary
Describes a deployed platform called Secure GPT that filters and anonymizes data before it reaches external LLMs (ChatGPT, Copilot, Gemini, Claude) or an on‑prem model, with 21 integrations (Jira, SharePoint, GitHub) and FINMA approval for banking. Shows concrete wins: automated rework of 5,000 test cases into a standard template (months of manual work saved), synthetic data generation from production datasets for GDPR‑safe testing, and a repeatable five‑step rollout that enforces goals, data checks, tool selection and monitoring.
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chapters (10)
- 0:00Introduction
- 3:46AI-driven quality optimization
- 11:54AI evolution and security
- 16:17AI and data breach risks
- 18:31Secure AI solutions
- 25:26Five-step AI transformation
- 27:12AI in quality assurance
- 32:54AI adoption challenges
- 36:12Future of AI in QA
- 36:54Q&A
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