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Knostic's Tailored Access Control for Large Language Models

Discover the power of AI agents. Create, customize, and control intelligent virtual assistants for your tasks.

Discover the power of AI agents. Create, customize, and control intelligent virtual assistants for your tasks.

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Updated on April 19, 2025 (3 months ago)

AI Agents Reimagined: Introducing Knostic for Secure LLM Access Control

AI agents are revolutionizing how we interact with information, but managing access to their powerful capabilities requires robust security measures. Enter Knostic, a cutting-edge tool designed to provide secure, tailored access control for large language models (LLMs). Knostic empowers enterprises to share information efficiently while preventing data oversharing by implementing need-to-know based access controls. This ensures that sensitive data is only accessible to authorized individuals, enhancing both security and operational efficiency across diverse industries. By integrating with systems like Microsoft Copilot and offering precise personalization, Knostic streamlines information retrieval and safeguards valuable assets in today's AI-driven landscape.

Pricing

Knostic offers a solution to manage access control for Large Language Models (LLMs) within enterprise environments, focusing on preventing "LLM oversharing". They provide an assessment to identify potential gaps in your current security posture and offer tailored solutions based on your organization's needs. While specific pricing details are not readily available on the website, they emphasize a personalized approach, suggesting that pricing is likely customized based on factors like the size of your organization and the complexity of your LLM implementation requirements. Here are the key points summarized: Focus: Need-to-know access control for LLMs in enterprise environments. Goal: Prevent "LLM oversharing" and ensure secure data handling. Services: Assessment to identify security gaps. Tailored solutions based on organizational needs. Pricing: Not explicitly stated, likely customized based on factors like organization size and LLM complexity.

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