Shelf

Overview

Shelf provides an AI Agentic platform designed to improve the accuracy and scalability of generative AI applications by focusing on knowledge and data governance. The platform aims to eliminate poor data quality before it impacts AI responses, enabling AI agents to reason, act, and scale with precision. Shelf was recognized as a Cool Vendor by Gartner in the Digital Workplace Applications report.

Key Features

• AI Data Model — Creates a structured intelligence layer by unifying data across systems and modeling business concepts, relationships, and logic.
• Enterprise Data Unification — Connects structured and unstructured data from various systems into a single, coherent foundation for AI.
• Knowledge Transformation — Structures knowledge into an interpretable format, allowing AI agents to reason over and act on information with precision.
• Enterprise Governance — Ensures accuracy, compliance, and continuous alignment of AI operations as business requirements evolve.
• Super Agents — Powers AI agents that deliver precise, reliable answers and scale consistently across the enterprise.
• CortexAI — Configures how AI agents reason, decide, and act, orchestrating complex workflows with reliability.
• Omnichannel Delivery — Delivers agentic experiences consistently across chat, voice, and email channels.

Who It's For

Shelf is designed for enterprises seeking to implement and scale agentic AI solutions, particularly in customer service and operational efficiency contexts. It targets organizations that face challenges with fragmented data, inconsistent AI responses, and the need for robust governance over AI-driven processes. The platform is suitable for businesses aiming to reduce average handle times, improve first call resolution, and transform customer experiences through accurate and reliable AI.

Notable Strengths

Shelf's primary strength lies in its "Knowledge + Data First AI" approach, which builds an AI Data Model of a business to ensure agents can reason and scale with precision. The platform emphasizes unifying enterprise data and modeling business logic to prevent AI failures caused by a lack of understanding of operational complexities. Customer testimonials indicate significant reductions in average handle time and improvements in first call resolution, demonstrating tangible business impact.