In an announcement made on February 19, 2025, Securiti, renowned for its data security, privacy, governance, and compliance solutions, revealed its partnership with Databricks. This collaboration integrates Databricks’ Mosaic AI and Delta tables with Securiti’s Gencore AI solution. The initiative specifically targets the enterprise market, intending to simplify and expedite the development of secure, enterprise-grade generative AI (GenAI) systems and AI agents by leveraging proprietary enterprise data.
Addressing Key Challenges in GenAI Deployment
Ensuring Secure Connection and Governance
The integration addresses a significant hurdle in deploying GenAI systems—securely connecting to data systems while ensuring the robustness of controls and governance throughout the AI pipeline. Given that most enterprise data is unstructured, proper governance and control of these assets become crucial. Utilizing Databricks’ Delta tables and Mosaic AI, coupled with Securiti’s Gencore AI, the partnership aims to bridge this gap effectively.
Gencore AI facilitates the adoption of GenAI in enterprises by streamlining the construction of AI pipelines from numerous data systems. With the new integration, organizations can securely tap into their structured and unstructured data through the Databricks Data Intelligence Platform. The ease with which unstructured data can be managed and transformed into actionable insights, while maintaining stringent security protocols, is a major breakthrough. This ability not only accelerates AI initiatives but also ensures data compliance and governance are upheld.
The Role of Data Command Graph
The Securiti Data Command Graph plays an integral role in secure data piping and synchronization, allowing organizations to safely transfer unstructured data to Delta tables from various SaaS applications and data systems across IaaS and private clouds. The process involves selecting relevant files, sanitizing sensitive data, and ensuring compliance with privacy and security standards before data import. This mechanism ensures that data integrity and security are maintained throughout the transition, giving enterprises confidence in their data handling processes.
Maintaining the sanctity of data during transfer is critical in enterprise operations. Any breach or mishandling can lead to significant repercussions, not just in terms of compliance, but also in potential financial and reputational damage. The combination of Securiti’s capabilities with Databricks’ robust data management system addresses these concerns, providing a seamless, secure data flow that aligns with enterprise standards.
Comprehensive Data Controls for Enterprise AI
Gencore AI Security Measures
Gencore AI provides extensive data controls including data sanitization, LLM firewalling, entitlement controls, and deep visibility with provenance tracking. These controls are in alignment with the OWASP Top 10 guidelines for safe AI systems. This suite of security measures ensures that GenAI applications operate within secure parameters, preventing any unauthorized access or data breaches, which is fundamental for enterprise applications where data sensitivity and user privacy are paramount.
Enterprises can now proceed with their AI initiatives knowing their data is protected and regulatory compliance is assured. Data sanitization helps in removing or obfuscating sensitive information, LLM firewalling helps in controlling what data can be accessed by AI models, thus preventing unauthorized data flow. Entitlement controls ensure that only authorized personnel have access to the data, and provenance tracking provides an audit trail, which is crucial for maintaining transparency and accountability.
Enhancing AI with Compliance
Building personalized AI applications becomes significantly more streamlined with access to rich unstructured data that comes with built-in security measures and compliance-tracing. Enterprises can create applications that are not only tailored to user needs but also maintain enterprise-grade security and governance while leveraging contextual user data. This is an essential advantage in an era where data-driven insights can significantly influence business outcomes and customer satisfaction.
The combination of security and compliance protocols with the agility to develop personalized AI applications ensures that enterprises can innovate confidently. This balance allows for the creation of highly intelligent systems capable of delivering insights and solutions that align with user expectations and regulatory requirements, making it easier for enterprises to adopt advanced AI technologies without the associated risks.
Strategic Impact and Future Prospects
Perspective from Databricks
Ariel Amster, Director of Strategic Technology Partners at Databricks, emphasizes that this integration allows enterprises to securely utilize their structured and unstructured data, expediting AI initiatives while maintaining stringent data security and compliance. This perspective highlights the strategic impact of the partnership, where the combined strengths of both companies create a robust platform for AI development and deployment. It indicates the importance of secure and compliant data management in accelerating AI-driven transformations across various industries.
Such advancements are crucial for enterprises looking to stay competitive in a rapidly evolving technological landscape. By ensuring data integrity and compliance, organizations can leverage AI to its fullest potential, driving innovation and efficiency. The ability to balance security with speed without compromising on either aspect is a game-changer for enterprise AI initiatives.
Insights from Securiti
On February 19, 2025, Securiti, acclaimed for its solutions in data security, privacy, governance, and compliance, announced a partnership with Databricks. This strategic alliance aims to integrate Databricks’ Mosaic AI and Delta tables with Securiti’s Gencore AI solution. The collaborative initiative is directed at the enterprise market, with the goal of simplifying and speeding up the development of secure, enterprise-grade generative AI (GenAI) systems and AI agents. By leveraging proprietary enterprise data, the partnership seeks to create robust and efficient AI solutions that meet the demanding requirements of large businesses. This merger of technologies promises to foster innovation and enhance the security and performance of AI applications in various industries. The integration allows enterprises to harness the full potential of their data while ensuring compliance and governance, thereby driving both productivity and security in AI-driven processes.
