Abstract: An overlay system is provided that includes a plurality of storage elements and processing circuitry coupled thereto. The plurality of storage elements store a plurality of executable graph-based models such that first and second storage elements store first and second executable graph-based models, respectively. Each executable graph-based model includes a plurality of nodes. The processing circuitry receives a stimulus to share a first node of the first executable graph-based model with a second node of the second executable graph-based model. The processing circuitry instantiates a tenant overlay node that is associated with the second node and includes a set of constraints to be adhered to by the second node while sharing the first node. The processing circuitry creates a sharing channel as a medium between the first and second storage elements. The sharing channel and the tenant overlay node enable sharing of the first node with the second node.

Abstract: The disclosure relates to method and system for hyper-localization of an application. The method includes obtaining a first page associated with the application. The first page includes at least one element. The method includes receiving user input corresponding to the at least one element associated with the first page for a first predefined locale of a plurality of locales. Each of the plurality of locales includes at least one of a geography and a language. The method includes associating the first page with a hyper-localization database. The hyper-localization database includes information corresponding to the at least one element of a plurality of pages for the plurality of locales. The method includes extracting data associated with the at least one element based on the user input from the hyper-localization database; and generating a second page for the first predefined locale based on the extracted data and a schema of the first page.

Abstract: This disclosure relates to a method and system for sanitization of sensitive data. The method includes analyzing sensitive data present within a page of an application based on a deterministic algorithm. Further, the method includes classifying the sensitive data into a high risk sensitive data and a low risk sensitive data based on a ML classification algorithm. For the one or more sensitive data classified as the high risk sensitive data, the method further includes performing a destructive sanitization on each of the high risk sensitive data. For the one or more sensitive data classified as the high risk sensitive data, the method further includes performing a non-destructive sanitization on each of the high risk sensitive data.

Abstract: The disclosure relates to method and system for generating contextual thumbnail previews. The method includes extracting data associated with a project including at least one component. The data includes one or more breakpoints, and one or more locales defined for the at least one component of the project. The method further includes generating a contextual map based on the data received; generating one or more interim thumbnails based on the contextual map; mapping the one or more interim thumbnails with pre-stored thumbnails within a database through a Machine Learning (ML) model; generating a consolidated contextual map based on the contextual map and the mapping; and generating one or more final thumbnails corresponding to the contextual thumbnail previews based on the consolidated contextual map.

Abstract: An overlay system including a storage element and processing circuitry is provided. The storage element stores an executable graph-based model that includes various active nodes and various micro-overlay nodes. Further, each active node includes multiple node elements, where each micro-overlay node is associated with at least one node element, and extends the functionality of the corresponding node element. The processing circuitry receives a contextualized stimulus. Further, the processing circuitry identifies an active node, node elements of the active node associated with the processing of the contextualized stimulus, and one or more micro-overlay nodes associated with each identified node element. The processing circuitry executes an operation associated with the contextualized stimulus based on the identified node elements and one or more micro-overlay nodes associated with each identified node element.

Abstract: A system comprises an executable graph-based model. The executable graph-based model comprises a first overlay node. The first overlay node comprises processing logic that is operable to interact with one or more associated nodes of the executable graph-based model. Further, the executable graph-based model comprises a first node that has the first overlay node associated therewith. The system further comprises a processing unit configured to receive a first stimulus associated with the first overlay node and, in response to the first stimulus being received, cause execution of said processing logic of the first overlay node. Execution of said processing logic of the first overlay node is based on the first node.

Abstract: This disclosure relates to method and system for legacy network transformation. The method includes receiving data corresponding to a legacy WAN from one or more data sources. Further, the method includes analyzing the data to identify one or more transformation requirements for the legacy WAN, based on one of a statistical technique, or a machine learning technique. Further, the method includes determining one or more configuration parameters corresponding to the legacy WAN based on a set of pre-defined business policy rules and the one or more transformation requirements. Further, the method includes generating a high-level design for SD-WAN based on the one or more transformation requirements and the one or more configuration parameters. Further, the method includes generating a low-level design including configuration guidelines templates for the SD-WAN based on the high-level design. Each configuration guidelines template may facilitate the transformation of legacy WAN to the SD-WAN.

Abstract: The disclosure relates to a method and system for dynamically mitigating threats of generative Artificial Intelligence (AI) models. Conventional systems often suffer from inefficiencies due to sequentially applying threat detection checks leading to unnecessary preprocessing and increased computational demands. Additionally, such systems typically focus only on input data, neglecting potential threats in outputs. The disclosed system and method addresses these drawbacks by employing a hierarchical structure of macro and nano classifiers. The system utilizes macro classifiers for broad initial threat categorization followed by specialized nano classifiers for detailed analysis of specific threat subtypes, thereby optimizing processing time and computational resources. The system operates in real time, applying predefined moderation rules to both input and output data to ensure comprehensive threat mitigation.

Abstract: An overlay system is provided that includes a storage element and processing circuitry coupled thereto. The storage element stores an executable graph-based model including a plurality of nodes, a plurality of rule overlay nodes, and a plurality of data analysis overlay nodes. The processing circuitry receives a stimulus indicative of a data analysis operation and identifies a first node, a rule overlay node associated with the first node, and a data analysis overlay node associated with the first node. The processing circuitry executes a set of rules associated with the rule overlay node on a composition of the first node to generate a set of outputs. The data analysis overlay node uses the set of outputs to determine whether a data analysis score associated with the first node exceeds a data analysis score threshold.

Abstract: The disclosure relates to system and method for continuously tracking humans in an area. The method includes receiving video data of the area from overhead cameras. Each of overhead cameras includes Field of View (FoV), FoV includes overlapping region and non-overlapping region, and overlapping region corresponds to region of intersection between at least two FoVs. The method further includes detecting presence humans in first FoV through object detection and classification models; for each human of humans, assigning unique global identity (ID) corresponding to human in first FoV, and reassigning unique global ID to human when human moves from first FoV to second FoV through overlapping region between first FoV and second FoV using weighted combination of resource assignment algorithm, intersection-over-union (IOU) based track detection, and velocity and direction estimation of subsequent frame of video data; and continuously tracking, in real-time, each of humans in the area through unique global ID.

Abstract: A method discloses obtaining a node template comprising a predetermined node structure and rules governing generation of node instances based on the node template. Data elements are received. A run-time node is generated in response to the reception of the data elements. The run-time node comprises the node template and a node instance. The node instance comprises the data elements mapped to the node template based on the rules of the node template. A run-time overlay comprising an overlay template and an overlay instance comprising processing logic implementing at least one generic rule of the overlay template are obtained. The executable run-time node is generated. It comprises a composition of the run-time node and the run-time overlay such that the processing logic of the run-time overlay is operable to interact with the run time node during execution of the executable run-time node.

Abstract: A method for transforming data organized in tabular structure is disclosed. In some embodiments, the method includes assigning a score to each of a plurality of cells within a table based on an associated set of orthogonal features characterizing a set of data. The set of orthogonal features comprises visual features, syntactic features, and language-based features. The method further includes identifying for each of the plurality of cells, a cell type based on the assigned score. The method further includes determining a table type based on the cell type and the set of orthogonal features determined for each of the plurality of cells. The table type comprises one of a row-oriented table, a column-oriented table, or a composite table.

Abstract: A method and/or system for Artificial Intelligence assisted service catalogue generation for network service provisioning is disclosed. The method comprising receiving input data which comprises either or combination of one or more specification documents or one or more configuration changes in network functions and/or network components. The entities and attributes of the entities are extracted from the input data which are then reconciled with graph database representing network function model to determine modifications in the input data. The graph database is updated based on the modifications identified in the input data, and recommendations comprising model elements are generated using AI engines which are displayed at the service modeler interface for generation of the service catalogue for network service provisioning.

Abstract: A method and/or system for automated estimation of 3D orientation of a physical asset using deep learning models and computer vision algorithms, according to one or more embodiments. The system may be configured to receive images of the physical asset and camera orientation data as input, use deep learning neural network models to isolate the physical assets across the images, track each physical asset instance throughout the images and derive a 3D point cloud model of each asset by projecting binary masks of the asset contours from different view-points. The 3D point cloud model is further processed and supplemented with camera orientation data to estimate the 3D orientation of one or more assets present in the images.

Abstract: This disclosure relates to a method and a system for managing anonymized data across computing devices in a blockchain network. The method includes generating the blockchain network including a blockchain ledger based on a dataset associated with each of a plurality of end users. The method of generating the blockchain network includes constructing the blockchain ledger corresponding to the dataset associated with each of the plurality of end users; generating a unique ledger key corresponding to the dataset associated with each of the plurality of end users; and storing the dataset associated with each of the plurality of end users in the blockchain ledger based on the unique ledger key. The method further includes communicating a joining request to a second computing device for joining the blockchain network. The method further includes granting access to the second computing device to the dataset associated with the plurality of end users.

Abstract: An overlay system including a storage element and processing circuitry is provided. The storage element stores an executable graph-based model. The processing circuitry receives a contextualized stimulus. Further, the processing circuitry identifies nodes associated with processing of the contextualized stimulus and determines an association between each identified node and a node layer present in the executable graph-based model. The processing circuitry loads the identified nodes, simultaneously, into the executable graph-based model based on the determined association such that one or more identified nodes are loaded into at least one node layer. The identified nodes loaded into the executable graph-based model form a projection. The processing circuitry further executes an operation associated with the contextualized stimulus based on the projection.

Abstract: A method for access management in graph-based model is provided. The graph-based model comprises a plurality of nodes and an overlay structure comprising processing logic. The overlay structure is associated with one or more nodes of the plurality of nodes. Processing circuitry determines a first node group of the graph-based model. The first node group comprises at least one node. The processing circuitry associates a first contract with the first node group such that the first contract is configured to act as a proxy for one or more nodes within the first node group in relation to requests from outside the first node group. The processing circuitry receives a stimulus and a context associated therewith. The stimulus is associated with the first contract. The processing circuitry maps the stimulus to the first contract to determine an access response. The processing circuitry processes the stimulus based on the access response.

Abstract: A method and system for cross-verification of alarms in real-time comprising identifying primary variables and secondary variables causing the event, labelling the primary variables and the secondary variables by primary engine and secondary engine based on Artificial Intelligence based predictive model building, predicting the labels by one or more inference engine based on previous history and data patterns, triggering secondary engine for cross-verification of alarms whenever there is a prediction from the primary engine, identifying the correlation between the labels from the primary engine and the secondary engine by validation engine, identifying alarm type based on correlation, recommending predictive maintenance and displaying on dashboard the cross-verification status of the alarms. The method reduces misclassification of alarm types based on predictive or preventive maintenance, reduces the maintenance costs of assets, and helps in prioritizing the critical alarms based on the alert type.

Abstract: A method and system can implement error and event log correlation in an apparatus and include extracting one or more log information associated with a storage location and creating a flexible structure of the one or more log information. The one or more log information is translated to a database store based on a user input. A match level is determined between an event and error data through the one or more log information extracted. When the match level exceeds a predetermined value, a relationship between the event and error data is created through an algorithm and a shareable entry is created for the relationship in a format usable by another apparatus.

Abstract: Onboarding a Virtual Network Function (VNF) package utilized by multiple network services is disclosed. The VNF package is received from a vendor for network services requested by a customer. The VNF package and its contents may be uploaded on an orchestrating manager, and a NFVI admin decides workflows for the VNF package, for validating and certifying the VNF package. The VNF package is validated using multiple checks and then parameters are identified for monitoring and certifying the VNF package. The VNF package is then ready for onboarding and instantiating the network services requested by the customer.