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It is imperative that copyright holders and content producers know how and where their artistic content is used online. Unauthorized file sharing is a threat to the viability of studios, TV networks and producers. The use of P2P file sharing is a worldwide problem that initially may seem difficult to combat. However, IT forensics can help bring some clarity to the situation.


At TECXIPIO, we recognize the creativity, time, effort and money that has gone into producing movies, TV shows and music. We understand the frustration of content producers and copyright holders who sometimes feel powerless to stop movie leaks and the unauthorized use of their work. Consumers should enjoy the high quality shows they love in ways that value and respect creative content and develop funding for future production.

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A a fingerprint. Through a magnifier it becomes visible, that the lines are formed by "0" and "1" digits


TECXIPIO has been monitoring P2P file sharing torrents since 2012. Our expertise in IT forensics allows us to map what was shared, when it was shared and by what clients. We generate reliable data so you will find your creative work in a digital world. Our useful data and scalable systems help studios, media organizations and content providers take back control. Our file sharing data products and solutions deliver valuable market insights to help you understand target markets, how illegal content is used and what is particularly popular. Content and distribution can then be adjusted and strengthened to satisfy demand and increase legitimate consumption.


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As an expert in IT forensics, TECXIPIO is committed to providing accurate and up-to-date information to our clients. Our file sharing data solutions are always being developed and refined to meet the needs of our growing customer base. We welcome customer feedback so we can introduce new features that represent real added value. What’s more, our products can be tailor-made to offer a customized solution to meet your individual needs.

Our mission is clear: Useful data. Scalable Systems.

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