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NIX helped the healthcare company streamline cybersecurity task management with an AI-powered solution.
Cybersecurity, Internet Services and Computer Software, Healthcare
Data Science, Web Development, Cybersecurity
Google Cloud, Vertex AI, LangChain
Our client specializes in developing, manufacturing, and distributing healthcare systems, both devices and software, for people with diabetes. Due to the sensitive nature of patient data and the stringent cybersecurity requirements imposed by regulatory bodies, the company prioritizes data protection and maintains rigorous security protocols like HIPAA, FDA, GDPR, etc.
To safeguard information transfer, each product release undergoes multiple cybersecurity checks, from bend testing to code review. Security architects analyze the results—including the vulnerabilities found—collect them into a report for regulatory authorities, and work on risk mitigation strategies.
Since these tasks were manual and inefficient—leading to unnecessary costs and resource allocation—the company decided to streamline and automate the entire process for greater cost-effectiveness and productivity. They asked the NIX team to develop a specialized AI-powered portal capable of generating reports and making smart predictions, ultimately streamlining document flow and assessing product release risks. The client chose us for our proven cybersecurity background and vast experience in healthcare development.
Develop an LLM-based system to autonomously generate cybersecurity reports for medical devices using an internal documentation database and generative AI technologies.
Ensure this system intelligently analyzes identified threats and vulnerabilities and proposes comprehensive mitigation strategies.
Our team developed an LLM-based system with a function-driven architecture that automates repetitive documentation tasks and streamlines cybersecurity administrative workflows. Deployed in the Google Cloud Platform (GCP), it utilizes various GCP services, such as Cloud Run and Google Workflows, and fully leverages generative AI capabilities. All data within this solution is encrypted both at rest and in transit, ensuring robust security.
To unite and set up all interconnected operations, we integrated the platform with the necessary enterprise-level systems, including threat modeling tools and the Oracle database as the final storage for reports. This two-way data synchronization ensures the correct extraction and processing of information for generating reports.
To optimize information aggregation from the cybersecurity reporting repository, our team used a combination of advanced technologies, including prompt engineering techniques, the retrieval-augmented generation (RAG) approach, and Vertex AI model capabilities. This enabled precise data extraction, efficient analysis, and accurate report generation.
Prompt Engineering: Domain-specific prompts allowed the AI to understand complex cybersecurity language and regulatory needs, ensuring well-structured reports and actionable mitigation strategies with minimal corrections.
RAG Approach: By combining Google Search grounding with Vertex AI Search, the system accessed both external and internal data sources, delivering reliable, verifiable, and contextually relevant outputs.
Vertex AI Models: These models facilitated rapid data processing, accurate information retrieval, and smooth integration with the company’s systems, ensuring synchronized and reliable workflows.
To increase the accuracy of the system’s predictions and the quality of the generated reports, we are constantly improving our AI model. Feeding it curated data from Oracle’s database and internal storages and using automated iterative prompt optimization, we instruct the AI to generate predictions on known data and compare results with expected outcomes. This process can be repeated any number of times to further enhance the accuracy of AI outputs.
With this LLM-based system enriched with generative AI technologies, the client significantly enhanced the company’s workflows and achieved all of their goals:
This gave cybersecurity professionals more time to dedicate their expertise to strategic and critical endeavors, boosting the company’s performance and improving its products.
We continue to work on the project to make the system even more sophisticated and its predictions even more accurate.
1,000+
AI-powered Reports
70%
Less Time Spent per Report
90%
Accuracy of Mitigation Strategies
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