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The benefits of utilizing locally hosted models with Elastic AI Assistant

A way for public sector organizations to leverage generative AI today to solve security challenges

Par

James Spiteri,

Dhrumil Patel

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With its ability to sift through large amounts of data to find unusual patterns, generative AI now plays a key role in helping teams protect their organizations from cyber threats. It also helps security professionals by augmenting their skills and bridging gaps in their knowledge. By handling complex data analysis and turning raw data into useful insights, generative AI allows teams to focus on planning their responses instead of just managing data.

Elastic AI Assistant, integrated into Elastic Security, quickly identifies, analyzes, and responds to potential threats, reducing the chance of false positives. It works well with various advanced AI systems known as large language models (LLMs) like OpenAI’s GPT models, Amazon’s Bedrock, and others designed to understand and generate human-like text. 

This means organizations can choose one or more AI models that best meet their cybersecurity needs. For organizations operating in highly regulated or air-gapped environments (settings where computers are isolated from unsecured networks to prevent unauthorized access), Elastic AI Assistant offers a secure and reliable option by integrating with locally hosted models.

Enhancing data privacy and security

The biggest advantage of deploying locally hosted models is that it greatly improves data privacy and security. This method is especially important for organizations operating in air-gapped environments, in regulated industries, or with sensitive information where keeping data private is critical. Locally hosted models ensure that sensitive data does not leave the organizational boundary so your data is never used for AI training, significantly reducing the risk of data breaches and ensuring compliance with stringent data protection regulations like GDPR and HIPAA.

Reduced latency in threat detection

By processing data closer to where it’s collected and stored, locally hosted models reduce the delay in detecting and responding to threats. Their ability to analyze data in near real time means security teams can quickly identify and remediate threats, which is vital in minimizing the potential impact of security incidents.

Operational benefits

Using locally hosted models not only enhances security and compliance but can also bring significant operational benefits. One of the primary advantages is the control it offers over the maintenance and updating of models. Organizations can undertake updates on their schedules, ensuring minimal disruption to their operations. Additionally, locally hosted models can cost less in the long run and reduce dependencies on continuous cloud services, which can sometimes vary.

Using locally hosted models comes with many benefits, but it’s also important to acknowledge some potential challenges. Setting up and maintaining locally hosted models requires more infrastructure and higher initial investment in hardware and trained staff. The need for specialized personnel to manage and troubleshoot systems could add to operational overhead, making it important to weigh these factors carefully.

Securing your organization in the modern threat landscape

As digital threats evolve, it becomes increasingly important to incorporate advanced tools like Elastic AI Assistant into your cybersecurity toolkit. The flexible framework of Elastic AI Assistant lets users easily adapt to rapidly changing AI developments by integrating specialized AI models tailored for specific fields or industries, enhancing their application effectiveness. 

Using locally hosted AI models not only enhances data security and compliance with strict regulations but also reduces latency in threat detection, helping your security team act swiftly and effectively. You will gain greater control over your data, optimize operational costs, and be better equipped to handle the complexities of modern threats.

The release and timing of any features or functionality described in this post remain at Elastic's sole discretion. Any features or functionality not currently available may not be delivered on time or at all.

In this blog post, we may have used or referred to third party generative AI tools, which are owned and operated by their respective owners. Elastic does not have any control over the third party tools and we have no responsibility or liability for their content, operation or use, nor for any loss or damage that may arise from your use of such tools. Please exercise caution when using AI tools with personal, sensitive or confidential information. Any data you submit may be used for AI training or other purposes. There is no guarantee that information you provide will be kept secure or confidential. You should familiarize yourself with the privacy practices and terms of use of any generative AI tools prior to use. 

Elastic, Elasticsearch, ESRE, Elasticsearch Relevance Engine and associated marks are trademarks, logos or registered trademarks of Elasticsearch N.V. in the United States and other countries. All other company and product names are trademarks, logos or registered trademarks of their respective owners.

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