Use cases
With Mimas.ai, we have quickly automated the detection of our most sensitive documents in order to better secure them.
Jun P., Head of engineering studies
EIXA
Context
The company manages a large volume of sensitive data (plans, customer data, financial documents) as part of complex projects. It needed a solution to identify, classify and secure these documents quickly and reliably, without their leaving the company.
Solution
- Implementation of a classification of data into 4 levels (public, general confidential, highly confidential).
- Development of a process for collecting documents and extracting their data for classification processing by Mimas.ai.
- Implementation of a classification of data into 4 levels (public, general confidential, highly confidential).
- Development of a process for collecting documents and extracting their data for classification processing by Mimas.ai.
Result
- 100% of the documents handled by the full process classified in less than 2h
- 100% of the documents handled by the full process classified in less than 2h
Mimas.ai helped us lower considerably the amount of time spent by our teams fixing the quality and the GDPR compliance of our customers' data.
Jérôme V., Consulting partner
SQLI
Context
Large companies working in the insurance domain need to accelerate their GDPR compliance efforts, and improve the quality of the data in their management systems
Solution
- Implementation of a process for automated GDPR risk management (4 levels) for feeding their data catalogs
- Data quality evaluation in the context of the fight against money laundering and the funding of terrorist activities (LCB-FT)
- Integration of these two classifiers within an automated data processing pipeline
- Implementation of a process for automated GDPR risk management (4 levels) for feeding their data catalogs
- Data quality evaluation in the context of the fight against money laundering and the funding of terrorist activities (LCB-FT)
- Integration of these two classifiers within an automated data processing pipeline
Result
- 100% of the monthly data processed
- 99% percent of precision achieved
- 100% of the monthly data processed
- 99% percent of precision achieved