At Traegis Tech LLP we provide affordable and efficient systematic planning and tracking in a safe, cost-effective and reliable fashion for our users and clients.

Traegis addresses the gap existing in social media in the area of planning and tracking movement in a collaborative manner, through our powerful services engine which includes a next-generation Dynamic Data Management services around the planning, tracking and analysis of movement using smart devices and apps

We launched our first app (Traeser) aimed at the biking community in early 2018 and it has garnered a huge following without active promotion

We commercially engage businesses and partners to use the capabilities of the Traegis engine (as proven in the Traeser implementation) and leverage the data lake for analytics for better insights

As part of the architecture, Traegis keeps the data and services separate to create an opportunity for multiple apps to utilize services provided by our platform and data lake while addressing security and privacy concerns.

Traegis Tech LLP was formed in 2017 by like-minded and experienced biking enthusiasts when a need was felt to create a platform/app focusing on safety aspects of riding. TTL created the Traeser app focusing on planning and sharing rides, tracking riders and emergency notifications if a rider has problems.

The Traegis engine provides a highly extensible set of services on a Data Lake which provides efficient storage capabilities for data (structured and unstructured) and content.

While the services engine and the data lake are capabale of supporting a wide variety of functionality, some of the key areas of interest are

Planning Services

Planning provides for route definition, halts, schedules etc. automated itinerary generation and collaborative planning

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Tracking Services

Low cost cloud based location logging and sharing services, with alerts and notifications and dynamic updates

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Analytics Services

Behavioural analytics based on user movement with pull based offers on goods and services, protected at the data lake level through consolidation and obfuscation

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© 2019 - TraegisTech LLP

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