Narayana Swamy

Databahn.ai is at the forefront of addressing the complex challenges in the cybersecurity "big data" arena with its innovative Data Fabric platform. By revolutionizing the way data is handled, federating, and decoupling data ingestion from conventional platforms like SIEM and Security Lakes, Databahn.ai offers a more efficient and cost-effective solution for data management. This strategic approach not only simplifies processes but also results in substantial cost savings by eliminating high subscription and license fees traditionally associated with these platforms. The platform's unique methodology ensures that only pertinent data is funneled to downstream platforms, thereby enhancing data quality, governance, and speeding up analysis within Security Operations Centers (SOC). The Security Data Fabric framework developed by Databahn.ai encompasses several key components designed to streamline data collection, orchestration, observability, and governance across both cloud and on-premise sources, with unparalleled levels of resiliency. This framework supports intelligent data pipelines that efficiently direct crucial data to security tools, reducing costs and improving performance. Furthermore, Databahn.ai’s platform emphasizes proactive security controls, offering insights to comprehensively understand an organization’s security stance. It encourages the integration of custom AI models and the establishment of proprietary Security Data Lakes, providing organizations with full control and deep insights into their data posture without compromising sensitive information. The tangible benefits realized by Databahn.ai’s clients are testimony to the platform’s efficacy. Customers report a 40% reduction in SIEM costs within the first month of deployment, the replacement of outdated log collectors with Databahn.ai's resilient edge collectors, and data ownership through bespoke data lakes. This not only signifies a reduction in tool sprawl and infrastructure