MinerEye does something that no other company is doing right now: fills the black holes in data governance, namely unstructured data. Unstructured data is data that is hard to discover, map, index and classify — think file attachments, PDFs, PowerPoints, Word documents. Think about the data entities within these documents: social security numbers, citizenship, medical histories, intellectual property, and of course sensitive business or product information. Think about how many times emails have been forwarded or sent to reply-all in a collaborative environment without a thought about who is receiving that sensitive information inside an attached document. MinerEye automates the discovery, categorizing, and risk scoring of sensitive and personal data within an organization’s unstructured repository, from within those attached files.
When organizations need to comply with stringent regulations from various directions like privacy, financial, or security concerns, having a tool to find the information within unstructured data can be like finding a needle in a haystack. Continuous use of MinerEye technology automates the tracking and management of sensitive data, particularly critical when searching among huge volumes of data. Through artificial intelligence and machine learning, MinerEye reduces the manual labor typically involved in finding and taking action on unstructured data.
In the federal market, there is no shortage of sensitive, unstructured data in large-scale environments. Here’s how MinerEye can help the federal government.
Data protection & secure collaboration
Siloed information can prevent the right people from accessing the data they need. MinerEye can assist agencies in secure sharing of information with increased accuracy, and less manual work, increasing capabilities across agencies that can benefit from securely sharing information.
Data discovery and governance
MinerEye can autonomously identify all instances of sensitive data and pull information related to it, such as who has handled it and if it’s been modified. In large-scale environments typical for federal agencies, MinerEye can automate manual investigations and help agencies proactively protect themselves against data breaches.
Large data sets, particularly in cloud environments are exposed to security flaws like a lack of file classifications, improper or incorrect classification. MinerEye reduces the attack surface in large data sets by identifying ROT (redundant, obsolete, trivial) data — to reduce the number of files to only what is required, thereby ensuring a secure and optimized cloud infrastructure. MinerEye also offers multi-dimensional file classification with multiple virtual labels that simulate all the required policies in handling data. This synchronization enables the classification to reflect who is using the data, for what purpose, and the data’s content.
MinerEye has already seen success abroad, and has received a highly competitive SME Instrument Grant from the European Commission. As government modernization efforts gain momentum, it’s not hard to see how a solution like MinerEye’s is necessary to protect data when using the cloud or an on-premise network. In case of a post-breach investigation, this same technology identifies what data was compromised.
Throughout Dcode Accelerate, MinerEye honed their go-to-market strategy, discovered how their commercial use cases translated to the federal market, and learned how to navigate the federal procurement process. Now, MinerEye is fully vetted for the federal market and ready to help agencies secure sensitive and personal data in unstructured repositories.
Interested in learning more about Dcode Accelerate for tech companies looking to scale in the federal market? Visit dcode.co/tech here →