Suridata’s Data Centric SaaS security Management Platform
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Suridata's Data Centric SaaS security Management Platform
|Company size (employees)||10 to 49|
|Headquarters Region||North America|
In 3 bullets, summarize why this company is different from the competition and deserves recognition:
Our competitors focus on SaaS application configuration security while we are focusing on data security, the main difference is when they create a lot of noise and identify generic gaps. We by using our NLP engine to truly understand the business critical data we prioritize security gaps based on the security risks they oppose to the organization.
For example, in medium organization more than 20,000 records can be shared externally, using our competitors the security team will have 20,000 actions to take or examine, by using Suridata the gaps will be prioritized based on the impact and risk to the organization so that the security team will only have to take action on 200 results.
By using innovative technology, we reduce the workload of the security teams. As a result, our product allows them to focus on their highest risks first with minimal resources. By doing so, we are able to provide them with significant risk reduction without the need for large teams or multiple security solutions.
Since our incorporation in 2020, we have acquired 18 clients from the U.S. and Israel, including Deloitte, IronSource, Dataminr, Sapiens, Bank Leumi, Wellthy, and more.
Suridata provides a data-centric SaaS security management solution, that simplify, unify and automate data protection across applications.
With Suridata’s unique data-centric approach, security teams can focus on the highest data risks first, and automate actions to remediate those risks.
Suridata identifies security gaps and prioritizes them based on the business impact of the data, to enable taking automated actions or assigning tasks to end-users to mitigate those gaps.
Our technology is based on a proprietary Natural Language Processing (NLP) engine that analyses data in a human-like way and understands the unique data in each organization. The uniqueness of this NLP engine is the ability to autonomously learn each organization’s data without human intervention and within days. This capability reaches a high accuracy rate in understanding sensitivity, business content and risk, with almost zero effort from the customer side, compared to the traditional methods that require heavy customization.
This technology leverage 15 years of research done by Prof. Roi Reichart our Chief Science Officer.