Data fusion and graphic link diagram platforms allow visualization of relations on a digital whiteboard to help the analyst better understand network hubs and reduce “noise.” This “fusion-only” solution does not enable predictive analytics to expand a network beyond direct and obvious connections. Furthermore, data fusion is limited, since the lack of AI and advanced analytics do not allow for entity extraction from unstructured data formats, such as videos, images, and reports. This low-cost solution has all the benefits of a basic data fusion platform with the addition of a visualization tool to help analysts understand network hubs and reduce noise. It is useful for small organizations that deal with simpler cases based on a few data sources. Data fusion and advanced analytics platforms combine the fusion available in other solutions with powerful machine learning algorithms. These tools are capable of showcasing similarities between entities, inferred relationships, risk assessment, and predictive analysis. There are two kinds of solutions in this category: 1 2 Vendor-dependent platforms do not enable flexibility for the end user when it comes to adding new data sources and creating machine learning models, since they depend on on-premise customization by the vendor. Due to this drawback, vendor-dependent solutions are a poor choice for time-critical use cases. Independent (open) platforms enable the user to have control over adding data and creating models, without the need for code. These solutions are thus ideal for time-sensitive use cases. Additional benefits to open platforms include the ability to limit access to sensitive data, since third- party vendors can be left out of the data scaling and modeling processes. 1 2 3 4 On the market