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Knowledge Graphs
By offering a comprehensive view of information and its relationships, Knowledge Graphs enable more effective decision-making, communication, and collaboration across various domains by enhancing data organization, integration, and retrieval. They support advanced analytics, personalization, and AI applications while improving data governance and interoperability.

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Features

AI Techniques Powering Enterprise Productivity: From Automation to Augmented Intelligence

AI stands beyond experimental status—it is a founding power for corporate productivity delivery. From automating repetitive workflows to enhancing complex decision making, AI transforms how work gets done.

The Rise of GenAI and LLMs

In 1950, Alan Turing suggested a test to determine if computers could mimic human intelligence well enough that an impartial observer could no longer tell the difference. We are still talking about the Turing Test almost 75 years after its inception.

The AI-Driven Transformation of Enterprise Data Architecture

The past year has been an exhilarating one with AI and more specifically, generative AI (GenAI), quickly emerging as a transformative force, reshaping how businesses will operate, innovate, and interact with customers. As AI continues to gain prominence, its impact on enterprise data architecture is becoming increasingly apparent.

Adding Meaning to Data: Knowledge Graphs, Vector Databases, and Ontologies

This article discusses the importance of context in enterprise data for generative AI (GenAI), and, in fact, for any AI initiative.

Enterprise AI Case Studies

Zuvu AI and Vana Collaborate on Decentralized AI in the Bittensor Ecosystem

Zuvu AI and Vana are announcing a strategic partnership to advance decentralized AI by integrating user-owned data, permissionless compute, and economic incentives.

SSI Strategy and Metalmind Collaborate on Life Sciences Enterprise AI Solutions

Through this partnership, SSI Strategy will leverage Metalmind's advanced capabilities in natural language processing (NLP) and large language models (LLMs) to enhance its service delivery.

Enterprise AI Whitepapers

Five Critical Design Considerations for AI Infrastructure

AI-Ready Data for GenAI Success

Semantic Layers for the AI Era: Real-Time Access, Smarter Decisions

Accelerating generative AI deployment