TrustLogix
Alter Blog • January 28, 2025
Alter Venture Partners is excited to be counted amongst TrustLogix’s investors as part of the company’s recently announced seed-2 financing. Even though the issue of data security has been top of mind for years with a steady drumbeat of news stories about innumerable breaches, ransomware and the theft of intellectual property, less noticed is the specific problem of data access management. This particular aspect of the overall security category has become critically important to many enterprises as they scramble to undertake data discovery, curation and management in preparation for their AI projects. Since the accuracy of LLMs and Generative AI models is heavily dependent on access to high-quality training data, enterprises that successfully unlock their valuable proprietary data for AI are better positioned to streamline manufacturing processes, improve customer service, reduce waste, and ultimately grow profit margins.
Enterprises were already focused on the issue of which employees had access to particular data sets as companies migrated to the cloud in a manner compliant with GDPR, CCPA, and other data privacy legislation. Now with the broader corporate adoption of AI, they are taking a fresh look at data security, access, and compliance on an enterprise-wide scale: across all data types, on all data platforms, in all clouds, and at all on-premises data centers. Alter firmly believes that TrustLogix’s novel solution is timely: a non-intrusive proxyless/agentless multi-cloud data security platform (DSP) that provides fine-grained protection for multiple data types in all environments. Following are details of three of the reasons supporting our investment:
Multi-Cloud & Multi-Data Platform: Many of today’s enterprises are multi-cloud: each department, function or business unit may select the service provider that best addresses its requirements. Similarly, enterprises don’t just use one data platform: in addition to Snowflake and Databricks, AWS offers RedShift, S3, Glue, and Aurora to name but a few (not to mention equivalent services at Azure and Google Cloud). Magnifying the complexity, an enterprise may also use hundreds or thousands of different applications. Each one of the components inside each one of these layers (cloud, data platform, and applications) has its own access control system which means that data policies are often manually interpreted and entered for every individual element of this ecosystem inside of a single company. TrustLogix’s unified approach to data access management places control of all policy enforcement and entitlements in one place – even if corporate data is siloed or if it is in a data lake – imposing consistency and improving visibility. Consequently, TrustLogix must operate at a scale – an enterprise-wide scale – that speaks to the design and architecture of its product.
Intelligent Data Access: Traditionally, access control has been role-based (RBAC), attribute-based (ABAC) or policy-based (PBAC). In a similarly static fashion, once permission was granted to a user for a particular data set, keeping track of usage, data ownership, updated policies, and changing employee roles was nigh impossible. Today’s access control needs to be sufficiently intelligent and dynamic to promote the democratization of data analytics and yet address the concerns of privacy, security, governance, and compliance. In regulated industries such as financial services and healthcare, failure to achieve a balance between these forces can be costly and damaging to one’s reputation. TrustLogix’s least privileged access recommendations build upon traditional RBAC and ABAC and are the result of the product’s AI-powered architecture; its Access Analyzer can automate access operations for customers. TrustLogix’s embrace of more intelligent data access means that it offers finer-grain data access controls than those at the storage layer of the underlying data platforms. Furthermore, by including data security posture management (DSPM) in its DSP, TrustLogix can detect unexpected data sharing, data exfiltration and other such unauthorized activities.
All Data Types: From their past experiences at Palerra and Oracle, TrustLogix’s founders, Ganesh Kirti and Srikanth Sallaka, not only envisioned a platform for different cloud and on-premises environments and for multiple data platforms but they also understood the need to address all data types. Enterprises have vast stores of structured data (financial transactions, sales records, time series, etc.) often in traditional or cloud-based data warehouses. Yet, according to GigaOm, the growth of unstructured data, which now comprises 80% of all enterprise data, has been outpacing that of structured data for a number of years. It is the richness of unstructured and semi-structured data that is attractive to LLMs and Generative AI models and provide the material for training. The broad applicability of TrustLogix’s solution – for the data types of today and tomorrow – has helped the company attract multiple Fortune 500 enterprise clients to date – and we are anticipating more customer wins in the near future!
For more insights on TrustLogix and its recent financing, please visit www.trustlogix.io or contact hello@trustlogix.io.
