The RSA Conference 2025 is set to kick off on April 28. Known as the “Oscars of Cybersecurity”, RSAC Innovation Sandbox has become a benchmark for innovation in the cybersecurity industry.
Let’s focus on the new hotspots in cybersecurity and understand the new trends in security development.
Today, let’s get to know the company MIND.
Introduction of MIND
MIND is a cybersecurity startup based in Seattle and Tel Aviv, dedicated to redefining data loss prevention (DLP) and insider risk management (IRM) through automation and artificial intelligence technologies. Its mission is to help organizations protect their most sensitive data, reduce risks and maintain brand reputation in a digital and AI-driven world. MIND’s vision is to reconstruct data security and data loss prevention through simplification, AI and automation.
Core Team Members
Eran Baraka is the co-founder and CEO of MIND, with a background in enterprise technology and business strategy. He has served as an executive in many startups and also held important positions in large technology companies, involving artificial intelligence, cloud computing, data security and other fields.
Itai Schwartz is also the co-founder of MIND. He has a technical background and is good at large-scale system architecture design and artificial intelligence system engineering. He has participated in the development of multiple AI and distributed computing platforms, has in-depth research on the construction and optimization of machine learning platforms, and is a key promoter of MIND’s product technology route.
Core Products and Technologies
MIND’s platform integrates data discovery and classification, data detection and response (DDR), and data leakage prevention and mitigation functions to provide a full range of data security solutions.
1. Data Discovery and Classification
MIND’s data discovery and classification solutions are designed to help companies fully identify and understand their sensitive data, especially in the current diverse IT environment. Through deep integration with SaaS applications, local file sharing, terminal devices and email systems, MIND can continuously discover all data, users and activities in the enterprise and provide a complete inventory of data assets. This approach helps reveal sensitive data blind spots at rest, in transit and in use, exceeding beyond the capabilities of traditional DLP solutions.
MIND’s deployment process is fast and convenient. As a cloud-native platform, it can be integrated with multiple IT systems of an enterprise in minutes. After integration, the system will record resources, users, authorizations, file activities and metadata to provide a clear view of risks.
One of its core technologies is a multi-layered AI classification engine that can identify file types beyond traditional sensitive data types (such as credit card numbers and social security numbers), including agreements, profiles, scripts, board meeting minutes, medical records, bank statements, contracts, tax forms and payroll reports. In addition, the engine can also classify specific sensitive records in these files, such as PCI, PII, PHI, cloud keys and credentials. MIND’s classification engine supports a variety of file types, including images and compressed files. Each resource containing sensitive data is given a customizable label and access control based on user type. To speed up classification, MIND uses precise and LSH techniques to skip classified data.
Through these features, MIND not only helps companies understand what is in their resources, but also adds specific organizational context and understands the business meaning behind the data, thereby achieving comprehensive visualization and accurate classification of sensitive data.
2. Data Detection and Response (DDR)
DDR aims to monitor the use of sensitive data in real time through automated means, identify potential risk activities, and prioritize them according to the severity of risks, thereby effectively reducing false positives.
The system can automatically or manually execute response measures, speeding up the security team’s investigation. Traditional data security tools often lack accurate classification of sensitive data, resulting in failure to detect truly important data breaches and generating a large number of false positives. MIND discovers and classifies sensitive data through a comprehensive directory of resources, users, authorizations, file activities and metadata, combined with the organization’s specific business context and data meaning.
MIND AI determines the severity and priority of risks based on the comprehensive context of sensitive data at rest, in transit and in use, develops a unique language to describe the risks of users interacting with data, and generates a set of rules to detect problems. When problems are detected, MIND AI data security analysts can automatically remediate them according to the organization’s policies, using their unique capabilities to collaborate with users and data owners through communication tools such as Slack, Microsoft Teams and Google Chat to help respond to problems. Security teams can automate these skills, or examine problems and approve recommended remedies.
3. Data Breach Prevention and Mitigation
MIND provides an AI-based automation solution in DLP, designed to prevent sensitive data from being leaked during transmission or use in real time.
Unlike traditional DLP tools that rely on static compliance policies, MIND uses autonomous, context-aware and risk-based assessment methods to act as an AI data security analyst for the enterprise, automating DLP and internal IRM procedures. Traditional DLP tools often lack accuracy and contextual understanding, resulting in frequent false positives, hindering normal business activities, reducing terminal performance, and affecting user experience. MIND intercepts user activities in real time and assesses potential risky behaviors by deploying local lightweight proxies and browser extensions on Windows, Mac and Linux terminals. Once a problem is detected, MIND’s AI data security analyst can automatically or manually prevent the data breach based on the organization’s policies.
For activities with lower risks, MIND provides a “speed reduction” function to guide users to understand organizational policies and initially block activities but allow users to continue operations. The security team will still be notified of these issues and can take remedial measures as needed. In addition, MIND provides security teams with a range of progressive remediation options, from completely blocking activities to providing guidance, monitoring or allowing operations, supporting automated processing or manual review and execution of recommended remedial measures. Through these features, MIND achieves real-time protection against sensitive data leaks, improves the effectiveness of DLP, reduces false positives, and optimizes user experience.
Market Recognition and Customer Cases
MIND has gained the trust of many well-known companies including Guild, OpenWeb, Noname Security, Gravity Payments, etc. For example, Guild chose MIND to protect its critical company and customer data, successfully deploying DLP programs that can operate efficiently even for small teams.
Industry Impact and Future Outlook
MIND’s innovative solutions stood out in the 2025 RSAC Innovation Sandbox Competition and became one of the top ten, receiving $5 million in investment support. This achievement not only proves the advancement of its technology, but also demonstrates its great potential in the field of data security. As enterprises’ demand for data security continues to grow, MIND is expected to continue to lead the industry in the future.
