Shelf provides a knowledge platform designed to address the critical challenge of data quality in Artificial Intelligence, particularly for Generative AI (GenAI) adoption. Recognizing that bad data in documents and files is a primary limitation to GenAI success, Shelf automates and monitors content cleanup. The platform offers real-time dashboards to identify the exact sources of inaccurate answers and provides detailed analytics through its Content Quality Dashboard, identifying root causes of hallucinations and inaccuracies across 22 categories. By connecting unstructured data from any source to its semantic layer, Shelf helps organizations identify risks, filter bad data, and enrich content with context. This ensures that GenAI deployments deliver trusted answers and support responsible AI practices. Shelf aims to future-proof technology stacks by focusing on the foundational unstructured data quality required for evolving GenAI journeys, enabling businesses to confidently deploy AI solutions and avoid the risks associated with poor data quality.

Features & Benefits

• Smart Data for Trusted GenAI Answers: Cleans unstructured data from documents and files to ensure accurate and reliable GenAI outputs.
• Answer Quality Dashboard: Provides real-time transparency into GenAI answers generated by bad data and their impact.
• Content Quality Dashboard: Identifies root causes of hallucinations and inaccurate answers with 22 categories of analytics.
• Actionable Insights for Improvement: Offers specific guidance on fixing data at the source, filtering bad data, or enriching it with context.
• Future-Proofing AI Tech Stack: Focuses on the unstructured data foundation, ensuring flexibility for evolving GenAI journeys.