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Multi-Source Data Fusion Platform
Multi-Source Data Fusion Platform
Traversals developed the Multi-Source Data Fusion Platform [DFP] that integrates structured and unstructured data from multiple sources, such as public records, social media, and sensors, into a single system. The [DFP] uses algorithms and machine learning to analyze and interpret the data, generating insights and actionable information. By combining various sources, DFP can provide a comprehensive view of situations, enabling users to make informed decisions.
Governments need multi-source data fusion for several reasons, including national security, intelligence gathering, and crisis response. By integrating data from multiple sources, such as satellite images, social media, and public records, governments can gain a comprehensive view of a situation and make informed decisions.
One example for multi-source data fusion in action is in the context of the conflict in Ukraine. In this case, governments have used open-source intelligence (OSINT) to monitor events, such as troop movement, or identified military equipment in use. Satellite images were used to verify information given by OSINT.
It is essential that a multi-source data fusion platform has enterprise functionality, including classification based data segmentation and access control. This functionality enables the platform to handle sensitive and classified data securely and provide access only to authorized users with appropriate clearance.
Development environments are important for enabling governments to customize and extend the platform to meet their specific needs. This functionality allows governments to develop custom applications and integrations that can further enhance the platform’s capabilities.
In summary, a multi-source data fusion platform is essential for governments to gather intelligence, monitor events, and respond to crises effectively. Enterprise functionality, such as data segmentation, access control, and development environments, is crucial to ensure that the platform can handle sensitive data securely and that is is ready for the future.
[DFP] provides data segmentation on property level allowing clients to set up complex access control.
[DFP] includes a Federated Search with GDPR-compliant access to various public records, social media and sensor data.
[DFP] provides built-in functionality for data collaboration within and outside of the organization.
[DFP] enables data scientists to integrate own data sources into the platform.
[DFP] enables data scientists to create own data products by using the Analytics and Development Environment.
[DFP] enables analysts in situation centers and strategically oriented units to react to changes in the shortest possible time via an intuitive web interface.
[DFP] integrates seamlessly with proprietary solutions. Traversals provides expertise and support as needed.
[DFP] offers automatic content-indexing, pre-processing of unstructured mass data, a broad multilingual information base and relieves analysts of routine work.
Fast, secure and always up to date. The [DFP] service is constantly being improved through customer feedback. New features are implemented in the shortest possible time thanks to the modern DevSecOps architecture and improve customer deployment.
Machine translation for 100+ languages.
AI-based event classification of text content with 200+ categories.
Possibility to collect and process Millions of data pieces per day.
GDPR-compliant integration of Google, Yahoo, Yandex, Naver, Bing, Ahmia, DuckDuckGo, Twitter, Telegram, TikTok, Reddit, VKontakte, …
Context-sensitive and robust geocoding of text content.
AI-based object recognition, scene identification, face recognition, multilingual optical character recognition.
Protected access to texts, images and videos using the built-in proxy system.
SaaS hosting in the EU cloud with web client or API (Application Programming Interface).