With the right context, Large Language Models (LLMs) can be a powerful tool to accelerate enterprise digital transformations. Knowledge graphs provide that enterprise context, giving organizations the ability to understand and trust LLMs to take advantage of their powerful applications. The Semantic LLM Accelerator offering with Enterprise Knowledge (EK) will help you capitalize on the capabilities of an LLM powered by a knowledge graph, demonstrating the potential of a Semantic LLM through a practical and efficient roadmap and prototype.
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Why Power AI With Knowledge Graphs?
Knowledge graphs are the bedrock of enterprise AI, enabling the next generation of Search, Recommendation, Chatbots, Graph Machine Learning, Natural Language Question Answering, and more. Through this accelerator, you will be able to:
- Talk to your private data using natural language questions: Power interactive chatbots for your internal users and customers, resolving inquiries and providing information across industries, from customer support to marketing.
- Accelerate content and data production on demand: Efficiently generate reports, articles, and documents with natural language inputs, saving time and enhancing productivity.
- Enhance and augment monitoring and resolution of issues: Assist users in diagnosing and resolving technical issues by embedding product information alongside operations standards.
- Create job aids and provide learning on demand: Empower employees with dynamically generated, on-demand learning resources and job aids, making training more efficient and effective for your workforce.
In 10-12 weeks, the Semantic LLM Accelerator will deliver understanding, alignment, and a first implementable version (FIV) Semantic LLM prototype. By engaging with experts in graph data modeling, LLM best practices and standards, and Enterprise AI, we will help your organization:
- Prioritize and pilot key use cases to quickly validate the application of an LLM;
- Demonstrate how your organization will benefit from the application of an LLM augmented by a graph;
- Define and pilot your first implementable version (FIV) of a Semantic LLM;
- Upskill your team in graph and LLM best practices and standards; and
- Align on an implementation roadmap to scale Enterprise AI (e-AI) usage across your organization.