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Today, complex crime is not only about traditional hierarchical mafias. The most dangerous crime consists of global criminal networks.

Those networks not only engage in criminal trafficking but also infiltrate, co-opt, and reconfigure States and institutions worldwide.

Traditional analysis tools are not enough to identify and confront this complex phenomenon.

VORISOMA is a unique set of tools powered by Artificial Intelligence to unravel criminal complexity.

After a decade of scientific research on Criminal Networks, VORISOMA transforms massive texts into analysis-ready graphs due to Machine Learning Models on Criminal Networks (MLMoCN) developed by Vortex.

In a collaborative web environment.

Our A.I. is trained with unique real data spanning 10+ years of empirical research.

Import/export oAdd elements: actor -User creates every node defining characteristics such as (i) name, (ii) actor type, (iii) default operation country, and (iv) gender. oAdd elements: relationships: User creates every interaction defining characteristics such as (i) the emitter and the receiver node, (ii) the relationship type, (iii) interaction date, (iv) empirical evidence, and (v) transnational movement of 8 types of resources. Import from CSV VORISOMA generates network graphs by importing structured data arranged in CSV files. User defines the data columns that will be used as (i) emitter and receiver actor/nodes, (ii) names of those nodes, (iii) interactions, and (iv) types of interactions. User con also merge and combine data from columns and define joiners. User can schedule automatic periodic imports from public URLs User can save a configuration of data columns as a preset to be used to import additional CSV files. Import from workspace User generates a graph by importing the content of another workspace/network. User can also download an entire workspace to a CSV file, so it can be used in other software or in other isolated workspaces inside VORISOMA. Export Formats - GML (Graph Modeling Language). - CSV in denormalized columns (compatible with CSV import). - CSV backup. Text to graph AI By using external NLP-AI models, VORISOMA AI reads a text, identifies, and extracts individuals and organizations, as well as their interactions. Additionally, there is an unfiltered importing mode that allows generating graphs by turning any semantic entity -such as places, dates, and objects-found by the NLP-Ai models in the text into nodes in a networks graph. VORISOMA assigns to each interaction generated through external NLP-AI models, the piece of text that was used as empirical evidence to create nodes and interactions. Through its external NLP-AI models, VORISOMA detects monetary transfers between actors, and generates transference records for actors referencing countries. User can adjust the decisions made by VORISOMA, to edit nodes, interactions, and empirical evidence assigned to each interaction. View/Navigate Navigate network as graph Zoom in - Zoom out. Interactive / Animated force-based visualization. User views network graph in full screen. User centers a network graph visualization. Automatic clustered visualization of disconnected nodes and node pairs. User activates and deactivates nodes labels. User searches nodes within a network graph. VORISOMA shows the number of nodes and interactions in a network graph. Navigate network as tags/cards In large networks, user changes the view to a list of tags/cards for easier navigation of nodes. Navigate neighborhood of a single node Clicking on a single node allows navigating and analyzing its immediate neighborhood, grades of separation with surrounding nodes, and expansion of routes/paths. Icons User assigns icons to specific types of nodes. Nodes operations (Lower bar) Delete User deletes nodes during graph navigation. Merge User merges two nodes into an already created node or into a new one. Break Unmerge nodes Subgraphs User selects nodes during the navigation to create a subnetwork graph. Then, the saved subnetworks can be found and navigated in the subnetworks section. Clean up Remove unused items User can remove actor types, relationship types that are not assigned to any actor/relationship (unused) Remove unrelated actors User removes all disconnected nodes. Remove all content User removes all the content in a workspace. Edit [workspace] Title User defines name of the workspace. Privacy User defines if the content of the workspace is kept isolated or shared with other workspaces. Users Administrator assigns users to the workspace under edition. Publishing options User defines if the network graph will be published in the public Criminal Aura Graph. Features Actor types User defines categories of nodes. Actors VORISOMA lists all the nodes in a workspace/network and shows alerts of disconnected nodes. Cases Dashboard with World Map, Network Graph, and Treemap in which VORISOMA shows information about judicial cases worldwide. Countries VORISOMA searches and proposes a default country for every node. VORISOMA then uses the information to show transnational criminal paths in the Criminal Aura Graph. VORISOMA shows the default country of every node/actor, whether it was manually defined by the user or by VORISOMA AI. Mentions Dashboard with World Map, Network Graph, and Treemap that shows the information about mentions of an individual in judicial cases. Relationship types Relationships Dashboard with the "Relationship table". VORISOMA shows all the interactions that conform a network, by listing the following information for each interaction: (i) Relationship type, (ii) emitter/active node, (iii) receptor/passive node, (iv) confidence level of the interaction, (v) assigned date, (vi) empirical evidence, and (vii) assigned system ID. Subgraphs Shows a tab for each generated subnetwork with its characteristics. User selects a subnetwork for analysis. Allows full navigation of each subnetwork. User sees all the exposed paths in the subnetwork, with the intervening nodes. User sees the paths as nodes that show the number of intervening nodes between two nodes selected when creating the subnetwork. Centrality: VORISOMA calculates and shows direct centrality and betweenness indicators for the subnetwork's nodes. Reports Generates statistics and pies of the network. Allows applying filters to explore statistics of various values that VORISOMA finds in the network. Navigation Add elements - actors/nodes User manually creates nodes with its characteristics and sources of information. Add elements - Content page Content management for maintaining content pages Add elements - Relationship User manually creates interactions with the nodes that were already created. Add elements - Relationship type User manually creates a type of interaction. It also can be added while creating a relationship. Add elements - Workspace User administrator creates and sets up a workspace. Add elements - Case User manually creates a case and its characteristics. Add elements - Case actor User manually specifies an actor mentioned in a judicial case. Connection matrix VORISOMA shows a matrix that can be used in software visualization. The matrix specifies with 1s and 0s if there is an interaction between two specific nodes. Count matrix VORISOMA shows a matrix that can be used in software visualization. The matrix specifies the number of interactions between two specific nodes. Accumulated confidence Matrix VORISOMA shows a matrix that can be used in software visualization. The matrix specifies the level of confidence for the evidence sustaining the interaction between two specific nodes. VORISOMA calculates the level of confidence according to the source specified by the user. Relationship Matrix VORISOMA shows a matrix that can be used in software visualization. In the matrix, VORISOMA assigns a code for showing the most prominent type of interaction between two specific nodes. Relationship Statistics VORISOMA shows the number of each interaction category. Resource movement types User creates and edits categories of resources to be shown in the Criminal Aura Graph. Resource movement VORISOMA shows and allows editing the information of those interactions in which the user registered a transnational movement of resources. Workspace graph VORISOMA shows the last version of the network graph Alerts VORISOMA highlights with red the disconnected nodes and the interactions with short evidence. Management System Logs User filters and search modifications and edits to a workspace. Users Administrator sees and edits the users assigned to a workspace. Workspaces Administrator sees and edits workspaces and users assigned. Content pages List content pages Access Control Granular User / Role based access control. Actor types Lists actor types for the active workspace Shared content List elements (actors, relationship types, and actor types) that can be shared between workspaces.

  • Three input methods:​

    • Manually: Create social agent nodes and their interactions by feeding individual data. 

    • Import massive data: Upload and configure CSV files to generate Criminal Network Graphs (CNG) with structured data.

    • Paste text: VORISOMA extracts individuals, companies, and countries from natural language text to generate databases of interactions (DoI).

  • Manage Databases of Interactions and define separate roles and access among team members.

  • Generate Criminal Network Graphs based on unique structured or unstructured sources: VORISOMA applies predefined or new categories. 

  • Navigate complex 3D networks or structures surrounding individual nodes.

  • Activate and deactivate categories of nodes and interactions during navigation to understand their role and impact on complex criminal structures.

  • Analyze critical characteristics: centrality indicators, relevant nodes, and types of interactions are automatically updated as data changes.​

  • More than 50 functions for analysis of complex criminal networks. See the full list.


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