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Digital twin 

We are TECTWIN, a digital-twin based AI/ML solutions provider. We bring unique perspective on trends, challenges, and untapped potential from network data. Our unique differentiator is creation of revenue enabler platforms & solutions for Communication Services Providers (CSPs), Governments & Enterprises which will enhance commercial opportunities using virtual reality, mobile data and geolocation. The solution allows capitalisation and leveraging of AI driven data insights which further enhances end user services and impact business processes.

Smart CapEx Solution

As 5G era demands efficient capital expenditures (CapEx) for staying competitive and using robust network planning practices to manage multiple use cases running simultaneously in the network, automated solutions from TECTWIN’s ‘Smart CapEx’ can improve CSPs end user experience, save capital and contribute to modern efficient operational practices. The CSPs, can build a strong foundation for achieving their strategic goals of monetising their network and bringing a better return of investment for their stakeholders. 

TECTWIN’s ‘SmartCapEx’ uses digital twin technology and connects network data such as - Performance, Configuration (PM/CM) and Geolocated data. Further data enrichment can be effected on use case specific functionality i.e Demographics, Crowdsourcing, Fixed Lines & many more. TECTWIN`s ‘Smart CapEx’ works in an open environment with an integrated workflow automation system that allows seamless integration with sales & service experts.

Geolocation Solution 

Today location can be easily obtained from a mobile device. Though tactics for assessing mobile location varies in precision, scale, how it is obtained and many other variables, these factors are taken into consideration when developing a communication service providers (CSP) monetisation strategy. Most common types of location data and targeting strategies are varied and each data source needs specific outcome it can be used for. 

When it comes to location data managed by CSPs there is not parallel for example In-building solutions (IBS) can provide more accurate results for user location unlike a WiFi. Similarly carrier IP identifies a device by a numerical identifier (assigned by the carrier) that allows it to receive information across networks making it more consistent. Registration data assigns location according to a user’s account address. Location-based content assumes proximity to a Web page containing local content. Cell tower/triangulation identifies all the devices operating within its range and is accurate at the market level where there are multiple towers in proximity to users (e.g., dense urban areas).
Depending on the goal of a campaign there can be many use cases and specific targeting strategies leveraging location data. TECTWIN offers geolocation based monetisation solutions for CSPs which can help in deciding strategies that are suited best for custom advertisement, entertainment and user services.

Our Partners

TECTWIN provides more value with its illustrious partners 
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Ericsson 

We support and contribute to Ericsson deliver RAN management and automation innovation with open rApp ecosystem 

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Fraunhofer Institute 

We work with Fraunhofer Institute for furthering wireless technologies & solutions. Our project on transforming connectivity using AI innovative approach on accelerating 5G and 6G coverage in urban and campus areas is nodal one in 2024

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VMware 

Our partnership with VMware contributes to use cases  to drive significant improvements in the Radio Access Networks (RAN) specially in the area of Smart CapEx. We recently were honoured at MWC 24  on VM ware TECHCOnnect event.

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Innovative Netztechologien

Funding program under Federal Ministry for Digital & Transport Germany

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TUV Rheinland

Our Sustainable & Energy solutions partnership

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Federal Ministry for Digital & Transport Germany

Has provided funds for XGdensify project  

Contact us

TECTWIN GmbH
Am Schweizer Garten 18
10407 Berlin
E-Mail: info@tectwin.com
Amtsgericht Charlottenburg HRB 253171

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