Shelf named a Cool Vendor™ in the 2025 Gartner® Digital Workplace Applications report.
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AI Projects Won’t Deliver Results Until You Fix Your Data

This post was created by Shelf with Insider Studios. We’ve all heard the explanations for why AI projects fail: the models aren’t advanced enough, they don’t remember past interactions, they hallucinate answers — the list goes on. However, those explanations overlook AI’s...

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The GenAI Context Problem and What Enterprises are Doing to Fix it

Sponsored content in partnership with The Wall Street Journal. Despite all the hype and billions in generative AI spending, many initiatives stall and budgets get burned without results, leaving executives questioning whether the hype can ever deliver real return on investment. The reality is...

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Why 95% of Contact Center AI Projects Fail (And the Governance Blueprint That Saves Them)

Key Takeaways An MIT report reveals 95% of AI pilots fail. Contact centers are rushing AI deployments without the governance layer needed for success.  We are seeing poor data preparation and lack of feedback loops as the leading causes of AI project failure. Organizations that implement...

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The Human Brain vs. AI: Rethinking Data Governance in Customer Service

Key Takeaways Generative AI processes information fundamentally differently than humans. AI predicts patterns rather than comprehending meaning.  This distinction requires completely rethinking enterprise data governance, moving from systems designed for human interpretation to frameworks...

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While Your Competitors Chase Bigger AI Models, Here’s How Smart Leaders Are Winning the Race

Key Takeaways The real AI race isn’t about having the most advanced models, it’s about having the cleanest, contextually rich, and governed data.  While most organizations fixate on AI tools, strategic leaders are building competitive advantages through superior data governance,...

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The Customer Support Data Quality Crisis Making ROI Impossible

Key Takeaways Poor data quality is silently killing customer support AI initiatives, regardless of how much you spend on AI models or vendors Bad data poisons AI training, routing, deflection, and agent assist, making ROI impossible to achieve The solution is proper data inventory,...

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Rag as a Service: Key Benefits and Practical Applications

RAG as a service provides Retrieval-Augmented Generation (RAG) technology as a managed solution, combining information retrieval and generative AI models to deliver accurate and relevant outputs. This service offers significant benefits such as improved response accuracy and timely access to...

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Top Vector Solution for Efficient Training & Development

Vector Solutions is a platform for enhancing training and development in organizations, education, and professional settings. It integrates tools for incident management, reporting, and improving learning outcomes. With Vector Solution, you can boost efficiency and safety while effectively...

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The Transformation of Knowledge Management in the Age of AI

Intro: The Rise of AI and Automation The rapid advancement of artificial intelligence (AI) technologies, particularly in the realm of generative AI, is ushering in a transformative era across various industries. As enterprises embrace these cutting-edge technologies and automate an increasing...

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How Shelf’s Ontology-Driven Architecture Transforms Unstructured Data into Business Intelligence

Bridging the Gap: Unlocking Business Value from Unstructured Data In today’s data-driven landscape, organizations grapple with a significant challenge: harnessing the immense potential locked within their unstructured data. While raw AI capabilities have advanced rapidly, translating these...

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Optimizing Unstructured Data for Successful Generative AI Deployment: A Tech-First Approach

The Rush to Deploy Generative AI Nowadays, organizations across industries are scrambling to deploy generative AI. While some have already implemented generative AI projects into production at a small scale, many more are still in the proof-of-concept phase, testing out different use cases. A...

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RAG Optimization Tools are the Key to GenAI Accuracy

Retrieval-Augmented Generation (RAG) enhances large language models (LLMs) by integrating an external retrieval system. This allows the AI to ground responses in authoritative, real-world data, which mitigates hallucinations and extends an LLM’s knowledge base beyond its pre-training data. ...

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