A New York-based startup, Sentra, has successfully raised $50 million in Series B funding to help enterprises protect and capitalize on their data. The company, founded by an Israeli Military Intelligence colonel, aims to provide businesses with better ways to secure and manage their sensitive data, especially in the era of AI and cloud computing.
Sentra’s Ambitious Plans for Growth
Sentra, which was founded in 2021, plans to use the funds to develop more enforcement capabilities, add native remediation features, and improve the classification of sensitive data. This will help companies better manage access to their data, especially for AI tools like Microsoft Copilot. Co-founder and CEO Yoav Regev explained the company’s vision, saying:
“We want to have enough money to push it as fast as we can and to accelerate, to be boots on the ground, to be everywhere, to serve our customers, to see the opportunity and to give them the best solution.”
He continued, explaining how the funding will help Sentra grow in the next couple of years:
“We found that this number they gave us is a good number for the next two years, three years, to push everything at the right pace.”
Sentra’s Focus on Data Classification
Since its inception, Sentra has raised a total of $103 million in three rounds of funding. Standard Investments led its most recent Series A funding round in January 2023. The startup has rapidly grown to a team of 131 employees.
As businesses face increasing pressure to protect sensitive information, Regev emphasized how important it is for organizations to accurately classify data. This need is driven by both the rise in data breaches and expanding regulations. At the same time, businesses are eager to utilize AI technologies, which require deep insights into their data. Sentra’s platform is designed to give enterprises the tools they need to safeguard their data while making it accessible for AI use cases. Regev said,
“Classification is a core capability for a data security platform. We want to support every platform and every place the customers have data – from IaaS, PaaS, SaaS and on-prem. We are taking our platform to the next level, from the remediation and enforcement part – DLP, permissions. And of course AI – we keep inputting more and more AI capabilities to support AI use cases for the customers.”
Achieving High Accuracy with AI
One of Sentra’s unique offerings is its ability to classify data with over 95% accuracy. This is achieved without taking any data outside of the customer’s environment. This is done through the use of AI and Large Language Models (LLMs). These technologies help the platform classify both structured and unstructured data. Regev said,
“To do 95% highly accurate classification without taking any piece of data outside of the customer environment, this is very unique. Most other capabilities and companies cannot meet those standards.”
Sentra’s classification engine will continue evolving to support new types of data, new platforms, and emerging use cases such as AI governance.
Securing On-Premise and AI Models
While cloud platforms are standardized and easier to manage, on-premises environments are often inconsistent, requiring separate engineering efforts. Regev pointed out that Sentra is investing in two parallel development tracks — one for cloud environments and one for on-premises settings — to ensure comprehensive support. He explained,
“You can support each place of on-prem, but to do it in a very efficient and accurate way, it’s kind of a different branch. There is one branch from the cloud and one branch from the on-prem. This is kind of different technology; you have to put to double the efforts to support both.”
Managing Access and Protecting AI Tools
Sentra is also focused on managing which data enters AI models. Furthermore, Regev explained that companies must carefully control access to their data in AI platforms like Microsoft Copilot and AWS Bedrock to avoid exposing sensitive information. Sentra’s solution offers context-aware classification and enforcement that goes along with the data as it flows into AI environments. Regev said,
“We just started to see AI use cases. It’s pretty new, six months, 12 months, something like that. I couldn’t tell you a year ago those are the major AI use cases. So we want to support those three for almost every service that’s important to our customers.”
Automation and Intelligent Remediation
Looking ahead, Sentra plans to build native enforcement capabilities into its platform. This means that instead of simply identifying and classifying data risks, Sentra will also take intelligent actions to reduce those risks. These actions include masking, encrypting, and even deleting sensitive data. Regev said,
“Now, we push more and more to act by ourselves, to help you mask the data, delete the data, encrypt the data, reduce encryption. All those actions that we can do on top of your data by ourselves. This is what we push in the next couple of months based on that investment.”
Also Read: How DataMasque Helps Achieve Both Data Privacy and Utility on AWS
