Strategy and Solutions

Upon a thorough analysis of the Data Security platform's business needs, Zymr experts devised a comprehensive data engineering macro architecture. To ensure optimal integration with Google Cloud, we conducted a series of research spikes, meticulously qualifying the most effective AI-native techniques. Zymr's expertise extended to the complete lifecycle management of MLOps, providing a seamless framework for our client. The solution was successfully deployed on Google Cloud, featuring advanced AI capabilities such as time series event analysis and data classification, bolstering data security measures. Notably, our proficient MLOps team architected a robust data ingestion pipeline, efficiently storing raw, feature-engineered, and golden datasets within Google BigQuery Data Lakehouse. This holistic approach has revolutionized our client's data security platform, enhancing its data management, classification, and overall efficiency.

The Client

Cequence is a prominent NASDAQ-listed multinational cybersecurity firm based in California. They specialize in the development of cutting-edge zero-trust network and data security solutions. Their innovative products and solutions are at the forefront of safeguarding digital assets, establishing trust in an inherently untrusted digital world, and providing comprehensive data security measures to protect against evolving cyber threats.

Key Outcomes

The solution enabled the deployment of an advanced AI-driven Data Security platform on Google Cloud, elevating data classification and analytics capabilities.

Our MLOps expertise streamlined data management and ingestion, storing raw and feature-engineered datasets in Google BigQuery Data Lakehouse, enhancing the efficiency and scalability of the client's platform.

Business Challenges

The client encountered multifaceted challenges when embarking on the development of a novel data security Software as a Service (SaaS) platform integrated with AI-native threat intelligence. To bolster their data infrastructure, they sought assistance in creating a robust data lake, essential for the efficient processing and analysis of vast volumes of information. Additionally, the client aimed to harness the power of domain-specific Large Language Models (LLMs) to offer their clients generative AI insights, but required expert guidance in designing and implementing these LLMs to enhance the overall capabilities of their platform.

Business Impacts / Key Results Achieved

Leveraging Google Cloud Services, we meticulously designed a hyper-scale data lake architecture that has revolutionized our data management capabilities. This transformation allowed us to seamlessly handle real-time, time-series, and event data ingestion, effortlessly managing over 20 terabytes of data per day. Furthermore, the well-architected MLOps framework they established ensured the highest standards of quality, security, observability, and resilience in our data operations. Most importantly, Zymr's solution has empowered us to rapidly incorporate new ecosystem data sources into our DSP data lake, fostering agility and adaptability in our ever-evolving data landscape. Their expertise has truly elevated our data management and analytics capabilities, driving us toward greater efficiency and innovation.