In this episode of the Eye on AI podcast, we dive into the critical issue of data quality for AI systems with Sedarius Perrotta, co-founder of Shelf.
Sedarius takes us on a journey through his experience in knowledge management and how Shelf was built to solve one of AI’s most pressing challenges—unstructured data chaos. He shares how Shelf’s innovative solutions enhance retrieval-augmented generation (RAG) and ensure tools like Microsoft Copilot can perform at their best by tackling inaccuracies, duplications, and outdated information in real-time.
Throughout the episode, we explore how unstructured data acts as the "fuel" for AI systems and why its quality determines success. Sedarius explains Shelf's approach to data observability, transparency, and proactive monitoring to help organizations fix "garbage in, garbage out" issues, ensuring scalable and trusted AI initiatives.
We also discuss the accelerating adoption of generative AI, the future of data management, and why building a strategy for clean and trusted data is vital for 2025 and beyond. Learn how Shelf enables businesses to unlock the full potential of their unstructured data for AI-driven productivity and innovation.
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(00:00) Introduction and Shelf's Mission (03:01) Understanding SharePoint and Data Challenges (05:29) Tackling Data Entropy in AI Systems (08:13) Using AI to Solve Data Quality Issues (12:30) Fixing AI Hallucinations with Trusted Data (21:01) Gen AI Adoption Insights and Trends (28:44) Benefits of Curated Data for AI Training (37:38) Future of Unstructured Data Management
