Industry first to use Augmented Deep Learning to unravel the value of connected vehicle data with augmented data signals to generate deep insights. Augmented data includes Social, Surface, Point of Interest (POI) and Mobility information to create enriched data market place of use cases.
Provides interface to deliver raw / processed data to consumers either as data reports or through APIs via cloud to cloud integration. Some functionality enabled are as follows:
- CXQueryBuilder : Allows stakeholders to consume data as data report by selecting different data search attributes.
- CXTryMeAPIs : Allows stakeholders to have cloud to cloud integration with ADLP.
- CXAttributes : Defines data signals that are supported in the platform.
Provides business intelligence research insights to stakeholders.
- Car Sales projection : Provides the car sales projection till 2025 based on OEM, country, make, model, etc.
- Trip Data Analysis : Allows consumers to analyse the individual trip data forms the basis for all advanced use cases. Some of the data that we analysed for the trip include trip and driver behaviour, vehicle score and trip route analysis including nearby shopping area, gas station, restaurant, bank, hospital, weather, etc.
Provides ready to use vertical specific solution and algorithms for different verticles including:
- OEM : Supports uses cases around Car Application Usage, Car Service Usage, Car Softkey Usage, Vas management, Car Price Prediction, etc.
- Fleet : Supports uses cases around Vehicle health, Driver Behaviour, Car Residual Value, Vehicle TCO, etc.
- Insurance : Supports uses cases around Driver Behaviour, Crash Analysis, FNOL, etc.
- Media : Supports uses cases around Top Stations, Application usage, Soft key usage, etc.
- Retail : Supports uses cases around Location based services, Store locations and timings, etc.
Consent Management System (CMS)
CerebrumX’s CMS empowers the data providers to exercise their right to privacy in an easy to use mechanism. High level objectives of CerebrumX CMS are:
- Mechanism to ask for consent by clearly disclosing what the consent is being given for and how the data will be used. System supports both End User Specific and Data Provider Specific consents.
- Securely storing all user consents as documentation and to support mechanics / processes for consent revoke at any point in time.
- Regularly renewing the consent as per the regulatory requirements.
Data Privacy and Anonymization
ADLP provides a plug-in to manage and maintain Data Privacy and Anonymization at the source data to ensure that any Personal Information such as names, addresses, etc is treated based on the user consent.
- Providing consumers with clear disclosures of the privacy practices including data collection, usage and sharing.
- Securely transmitting and storing all data either sensitive or otherwise.
- Implementing data retention practices and safeguards.