Agnik-Technology

9th April, 2009
Agnik wins a multi-year contract from Missile Defense Agency. Read More

9th April, 2009
Complete Innovations, a Canada-based company has entered into an agreement with Agnik. Read More

9th April, 2009
Imarda Inc, with headquarters in New Zealand, has entered into an agreement with Agnik. Read More

22nd January, 2009
Grace Pacific Corporation of Hawaii adopts MineFleet for their fleet. Feeney Wireless and Agilis Systems are managing this solution for Grace Pacific. Read More

5th January, 2009
Agilis Systems offers MineFleet-powered Web Services. Read More

5th January, 2009
Source Inc. chooses MineFleet technology for its vehicle data mining applications. Read More

15th April, 2008
Sierra Wireless (NASDAQ: SWIR - TSX: SW) and Agnik announce agreement to jointly market Agnik’s MineFleet® predictive vehicle data mining system along with the line of AirLink™ vehicle tracking solutions offered by Sierra Wireless. Read More

Agnik’s products are developed based on a strong technical foundation of algorithms and systems for data analysis and mining in mobile and distributed environments. Its proprietary technology is developed based on years of research and development by its founders and technical team members.

Data Analytics in Mobile Devices:

Mobile devices such as cell-phones, PDAs, laptops, smart cards, and wearable computers are increasingly being used for data intensive applications. In some cases these devices themselves are connected to different types of sensors that generate lots of data (often continuous data streams). Sometimes, these devices are used to remotely monitor data sources over a wireless network. The new generation of data intensive applications in mobile devices needs support for data analysis in environments with limited resources (e.g. memory, processing power, battery power, user interface). Agnik offers a comprehensive technical solution for data analysis and mining in mobile environments. Some of our core technical capabilities include the followings:1) Fast, scalable analysis of high volume data stream using light-weight computing devices.
2) Minimizing expensive communication load in data analysis over wired and wireless networks.
3) Design and implementation of data analysis techniques that reduce battery power consumption.
4) Minimizing the ``footprint'' of the system in order to be able to run it in light-weight devices.

Large Scale Distributed Data Mining:

Agnik is spearheading the next generation distributed data mining applications that are designed to run in a network of desktop computers and high-end devices such as the Internet, grids, and peer-to-peer systems. Agnik offers complete end-to-end distributed data mining technology that allows analyzing distributed data, comparing and aggregating results without having to centralize all the data to a single central place.

Pattern Preserving Crypto for Data Analysis and Mining

Can you analyze encrypted data so that certain underlying patterns can be detected but the data is hidden from the outside world? Agnik’s proprietary Pattern Preserving Crypto (PPC) technology offers exactly that. United States Department of Homeland Security is using this technology for developing the next generation of surveillance systems that monitor threats against the cyber infrastructure of the country while preserving the privacy of the monitored data.This technology can be used in surveillance systems that require continuous monitoring of sensitive data, comparing observations, and finding matches across multiple, proprietary data sources. Library transactions, employee behavior, healthcare data, financial data, law enforcement data and mobile communications are just a few of the data types being monitored today for corporate security, cyber-threat, and counter-terrorism related tasks. Agnik’s pattern preserving crypto technology will allow detecting the threats while protecting the privacy of law-abiding individuals, since raw surveillance data is often divulged during the process of monitoring.

Real-time Resource-Constrained Data Analysis in Embedded and Sensor Systems

New generation of computing platforms such as embedded devices and sensor networks are increasingly developing applications that generate lots of data in ubiquitous environments. Personalization, context aware applications, and surveillance applications for such environments require serious analysis of the real-time data streams. However, the resource-constrained environments in these devices offer many challenges for real-time analysis of the data. Agnik has developed proprietary technology for real-time data management and mining of un/semi and structured data streams. Agnik’s MineFleet product-line designed for onboard data stream mining in vehicles is bringing the benefits of this technology to the commercial fleet management industry.

For more information about the work performed in the above areas by one of the co-founders of Agnik, please follow http://www.cs.umbc.edu/~hillol