Chorology has released a patented AI-driven compliance engine to auto-identify, contextualize and classify sensitive data at scale.
The San Jose-headquartered compliance and security posture management firm has unveiled its Automated Compliance Engine (ACE) – equipped with AI-based knowledge encoding, a new domain language model, and AI planning automation. The startup came out of stealth mode earlier this year.
“These patented technologies coalesce, providing the first and only mandate-agnostic solution to deliver a complete view of all sensitive enterprise data – known and unknown – throughout structured and unstructured environments,” claimed Chorology.
Several compliance and security challenges continue to pose major risks to organizations, making technology that accurately identifies, contextualizes and classifies data essential, says the provider.
Efficiently responding to consumers’ data subject access requests (DSARs) is one use case that has to be addressed. Under legislation such as the General Data Protection Regulation, failure to respond to consumer DSARs in time can leave organizations open to administrative fines and financial risk.
With the ACE platform, organizations can frame enterprise data under management as knowledge objects. With this AI framing, very large repositories of sensitive data can be discovered, identified and classified at “ultra-high speed” and scale, we are told. Large numbers of DSARs can be automatically processed too, delivering time savings and helping to avoid penalties.
And by encoding knowledge objects for each data type, ACE can accurately recognize any data type, for any mandate, in any industry, without any costly machine learning training, and through using a single compliance platform.
“ACE now makes it possible to automatically discover all known and unknown sensitive data throughout the enterprise’s data universe, where compliance policies can then be automatically applied,” said Tarique Mustafa, CEO, CTO and founder of Chorology.ai. “Our mandate-adaptive technology uniquely applies knowledge representation and inference encoding disciplines into the artificial intelligence and language understanding, to very accurately discover, identify, classify and map data at scale, which has not been possible previously.”
Mustafa previously founded cyber security platform GhangorCloud, and he has held senior positions at the likes of Symantec, Nevis Networks, Andes Networks, Nextier Networks, and MCI WorldCom. Chorology’s founding team includes executives that have experience at firms including McAfee, TrendMicro, Cisco, and Array Networks.
