3584results about "Cryptography processing" patented technology

An artificial intelligence driven system of systems may include a layered architecture for providing transaction support to various types of enterprises. A governance layer implements automated governance and policy enforcement through specialized governance modules utilizing generative AI technology. An enterprise layer supports enterprise functions by integrating management and control platforms with digital infrastructure. An offering layer creates and manages system offerings via content generation, personalization, and smart product modules. A transactions layer enables automated transaction orchestration through API integration, execution, and fulfillment modules. An operations layer manages AI systems through generation, training, verification and orchestration modules. A network layer provides adaptive networking capabilities through routing, protocol selection and communication modules. A data layer processes fused data from multiple sources using machine learning and AI systems. A resource layer manages computing, storage, and other resources through specialized resource modules.

The present invention provides a large language model-based system and method for data processing in application developed by codeless platform. The invention includes identification of intent of a user to process procurement, supply chain, application integration, application restructuring or development scenarios.

A system and method for multi-scale temporal attention processing in multimodal technology deep learning systems. This system processes time-series, textual, sentiment, and structured tabular data across three hierarchically-organized temporal streams—quarterly, weekly, and intraday levels—with bidirectional cross-temporal information flow. Scale-specific attention mechanisms are optimized for respective temporal granularities, while an adaptive controller dynamically weights each temporal level based on real-time market volatility indicators. A multi-scale fusion processor integrates attention-weighted representations to generate temporally unified representations preserving both short-term market dynamics and long-term trends. This approach enables superior forecasting and risk assessment by leveraging temporal correlations across multiple time scales while automatically adapting to changing market conditions. The system facilitates interpretable AI analysis through attention visualization and enables synthetic scenario generation for model testing.

An Al -based energy edge platform is provided herein with a wide range of features, components and capabilities for management and improvement of legacy infrastructure, coordination, and orchestration with distributed systems to support important use cases for a range of enterprises. An Al -based energy edge platform may include a graph neural network including a set of nodes respectively representing at least one distributed energy resource (DER) and a set of edges respectively interconnecting the set of nodes, wherein each edge represents at least one energy - related feature among at least two nodes of the set of nodes. The platform may incorporate emerging technologies to enable ecosystem and individual energy edge node efficiencies, agility, engagement, and profitability. Embodiments may forecast, plan for, and manage the demand and utilization of energy in greater distributed environments. Embodiments may employ intelligent provisioning, data aggregation, and analytics to leverage energy market connection, communication, and transaction enablement platforms.

Systems and methods for decentralized data management across interoperable distributed platforms are disclosed. A computing system receives input data associated with a unique decentralized identifier (DID) representing an entity or event. The computing system segments the input data into encrypted data segments, each cryptographically linked to the DID, and distributes these encrypted segments across decentralized storage nodes according to a redundancy scheme. A cryptographic lineage record, including segment identifiers, timestamps, and hashes linked to the DID, is stored in a decentralized ledger. In response to authenticated access requests, the computing system reconstructs the input data by retrieving, decrypting, and cryptographically verifying the distributed data segments against the lineage record. Authorized entities access the reconstructed data through interfaces enforcing cryptographically secured access permissions defined within the decentralized ledger, providing enhanced security, provenance verification, and data resilience.

A system may include an Al convergence system of systems for a value chain network environment.

A value chain network control tower system comprises a processor and memory configured to execute a know your model system that manages the complete lifecycle of Al models in enterprise environments. The know your model system performs model intake and registration actions including model documentation collection, registration procedures, metadata collection, input / output interface standardization, legal and licensing validation checks, and security validation. The system conducts comprehensive model evaluation and risk assessment actions by analyzing foundational properties, task performance, safety and risk management, alignment and compliance characteristics, operational metrics, and tooling transparency capabilities. The know your model system executes model deployment actions through automated environment validation, predeployment approval processes, and controlled production deployment with continuous monitoring.

Systems and methods for controlling rights related to digital knowledge are disclosed. A sample system may include an input system to receive digital knowledge from a user, a tokenization system to tokenize the digital knowledge and a ledger management system to create, manage, and store things on a distributed ledger and provide provable access to the digital knowledge. A smart contract system may create a smart contract including triggering action is and respond with a defined smart contract action on an occurrence of the triggering event. The smart contract system may also process commitments to the smart contract.

A system and method for facilitating collection of Road User Charges (RUC) using a digital currency within a Distributed Ledger Technology (DLT) network are disclosed. The system generates secure digital wallets for Road Users and Facility Owners, receives trip, position, distance, and cost data from vehicles, sensors, and facility systems, and encodes settlement logic into smart contracts. These contracts automatically execute jurisdiction-specific disbursements across blockchain, directed acyclic graph (DAG), or hashgraph frameworks, ensuring scalability and auditability without reliance on centralized tolling infrastructure. An AI Activity Module processes multi-source telemetry—including vehicle sensors, GNSS / PNT data, roadside infrastructure, and third-party traffic feeds—to detect congestion, forecast conditions, optimize routing, and dynamically adjust segment-level RUC pricing in real time. The integration of AI-driven adaptive pricing with distributed ledger settlement provides a decentralized, infrastructure-agnostic framework for secure, transparent, and verifiable road use fee collection across multiple jurisdictions, distinct from conventional tolling systems.

An information technology system for a distributed manufacturing network includes an additive manufacturing management platform configured to manage process and production workflows for a set of distributed manufacturing network entities through design, modeling, printing, and supply chain stages. The information technology system includes an artificial intelligence system configured to learn on a training set of outcomes, parameters, and data collected from the set of distributed manufacturing network entities of the distributed manufacturing network to optimize digital production processes and workflows. The information technology system includes a distributed ledger system integrated with a digital thread configured to provide unified views of workflow and transaction information to entities in the distributed manufacturing network.

Systems and methods for managing resources across a global and / or cloud network. In particular, systems and methods for mitigating issues related to providing services while resources are offline (or may potentially go offline). For example, the systems and methods may mitigate issues related to providing services while resources are offline (or may potentially go offline) by monitoring network services at an aggregate level.

The present invention discloses a system and method for secure artificial intelligence-based financial technology governance and risk management, designed to provide real-time, autonomous, and verifiable compliance assurance within digital financial ecosystems. The invention integrates a secure artificial intelligence processing unit, a governance control processor, a cryptographically anchored storage unit, a federated learning coordination processor, and a quantum-resistant communication interface enclosed within a tamper-proof hardware structure. The system performs encrypted machine learning computations on financial transaction data using homomorphic encryption and trusted execution environments to preserve confidentiality during analysis. It computes a governance risk index based on probabilistic inference and anomaly detection to identify regulatory deviations, applies adaptive compliance reasoning across multi-jurisdictional frameworks, and automatically enforces governance actions through secure decision logic.

A content editor or a plugin thereto automatically generates authorship tokens that identify content authored by a human author or an artificial author. The authorship tokens are applied to the work while the work is being produced. Thus, subsequent review of the work can identify regions produced by a human author and other regions produced by an artificial intelligence.

A robot fleet management platform includes a job configuration system that determines tasks to be performed by robots of a robot fleet based on a job request and a first fleet objective. A proxy service applies fleet configuration services to the tasks to produce a data structure. An intelligence layer activates intelligence services to produce a robot task and associated contextual information that facilitates robot selection and task ordering. A job workflow system generates a workflow defining a performance order of the tasks. A workflow simulation system simulates performance of the job request based on the workflow to recursively redefine the tasks, the data structure, or the workflow until the simulation result satisfies a second fleet objective. In response to the simulation result satisfying the set of fleet objectives, a plan generator generates a job execution plan based on the set of robot tasks, the data structure, and the workflow.

A tokenization system / platform / method for minting asset-class backed tokens on a distributed ledger is described herein. A tokenization system / platform receives a token configuration indicating multiple revenue-generating assets of different types and a minting party. The platform configures smart contracts to manage revenue associated with revenue-generating assets, including a first function to mint asset-class backed tokens backed by the plurality of assets and a second function to computationally apportion and distribute revenue among blockchain addresses of token owners. After deploying the configured smart contracts on the distributed ledger, the platform initiates blockchain transactions to invoke the smart contract functions, including a first transaction that mints tokens and assigns them to purchasing users' blockchain addresses, and one or more second transactions that distribute cryptocurrency corresponding to revenue among token owners. The system / platform / method may provide for fractional ownership and management of different types of revenue-generating assets and / or portfolios of revenue-generating assets.

Systems, apparatus, and methods of managing access to private data via tokens are disclosed. The disclosed techniques provide for constructing digital tokens that represent a right-to-access private data where the tokens can be managed as individual objects. Further, such digital access tokens (DATs) can be recorded on a notarized ledger, a blockchain for example. Additionally, the rights-to-access can be embodied as a non-fungible token (NFT), which could further include support for establishing homomorphic encryption workspaces in which private data can be accessed or manipulated without exposing the private data.

Systems and methods for managing resources across a global and / or cloud network. In particular, systems and methods for mitigating issues related to providing services while resources are offline (or may potentially go offline). For example, the systems and methods may mitigate issues related to providing services while resources are offline (or may potentially go offline) by monitoring network services at an aggregate level.

This invention presents a comprehensive platform designed for the generation, management, and execution of intercompany agreements through an automated, blockchain-based system. It employs AI and NLP technologies to assist in drafting customized agreements, taking into account international laws and corporate policies. The platform converts these agreements into immutable, transparent smart contracts deployed on a blockchain network, serving as a single source of truth. It ensures real-time compliance, automatic enforcement, and efficient dispute resolution by continuously monitoring contract performance. This integration streamlines financial processes, enhances regulatory compliance, and increases operational efficiency in managing complex intercompany relationships.

The deep water port steel pipe pile foundation construction method comprises the steps that three-dimensional geological modeling and pile position positioning are conducted, specifically, a construction area is scanned through an unmanned aerial vehicle carrying a multispectral radar, geological data are obtained, a dynamic three-dimensional geological model is constructed based on a random forest algorithm, and the pile position layout and the pile sinking path of steel pipe piles are planned; multi-parameter data real-time collection and transmission: collecting perpendicularity, pile body stress and hammering vibration data in real time, uploading encrypted data to a cloud platform through a 5G / Beidou dual channel, and storing the encrypted data; the cloud platform calculates the optimal hammering energy, the vibration frequency and the hammer stopping standard by using a reinforcement learning algorithm in combination with the dynamic three-dimensional geological model and the real-time data; and pile sinking is conducted, specifically, the posture of a pile body is monitored through a laser radar and an inertial measurement unit, a PID control algorithm is adopted to drive a walking type pile driver hydraulic system, and pile sinking is conducted. According to the method, the scientificity of pile position layout and the reasonability of a pile sinking path are improved; the pile sinking efficiency is improved; the energy consumption is reduced; the pile foundation stability is guaranteed.

Systems and methods for decentralized orchestration of event records within decentralized computing environments. A processing system including decentralized execution nodes dynamically allocates microservice instances based upon real-time node performance metrics. Transaction requests including transaction data digitally associated with decentralized identifiers (DIDs) are processed by allocated microservice instances. The processing includes verifying transactions, generating cryptographically-linked immutable memorialization records associated with respective DIDs, and distributing these records to a tamper-evident distributed ledger configured to enforce immutability through consensus nodes. The processing system dynamically reallocates microservice instances among decentralized execution nodes based upon monitored utilization metrics and predefined scaling thresholds. Each memorialization record is cryptographically secured and linked permanently to the DID for data immutability, enhanced security, and dynamic scalability for event data processing in distributed infrastructures.

Techniques are described herein for system for preserving memories and experiences through a Non-Fungible Token (NFT) engine. An example system includes one or more memories storing a set of computer-readable instructions including the NFT engine and one or more processors interfacing with the one or more memories. The one or more processors are configured to execute the set of computer-readable instructions to cause the system to: receive data of a user from a time period, and execute the NFT engine to: analyze the data to classify a memory experienced by the user during the time period based on a memory threshold, generate, for display to the user, an NFT based on the memory, and mint the NFT corresponding to the memory to a blockchain, wherein a portion of the data associated with the memory is linked to the NFT.

A dynamic vision system includes a variable focus liquid lens optical assembly. The dynamic vision system includes a variable lighting assembly. The dynamic vision system includes a control system configured to adjust one or more optical parameters and data collected from the variable focus liquid lens optical assembly in real time. The dynamic vision system includes a control system configured to adjust the variable lighting assembly. The dynamic vision system includes a processing system that dynamically learns on a training set of outcomes, parameters, and data collected from the variable focus liquid lens optical assembly to train a set of machine learning models to control the variable focus liquid lens optical assembly to optimize collection of data for processing by the set of machine learning models.

A mobile device with a first transceiver, a second transceiver, one or more processors, and memory bridges communications between an offline retail machine with a short-range communication capability and a remote server by obtaining via the first transceiver a single-use request code from an information packet broadcast by the offline retail machine; transmitting via the second transceiver the single-use request code to a remote server; obtaining via the second transceiver from the remote server a grant token including the single-use request code; detecting a trigger condition for initiating provision of a product or service by the offline retail machine; and in response to detecting the trigger condition, initiating performance of the provision of the product or service by transmitting the grant token to the offline retail machine via the first transceiver.

A computer may generate a temporary digital wallet containing one or more anonymous payment tokens and transmit the temporary digital wallet to a user device of a user. When the user provides an anonymous payment token of the one or more anonymous payment tokens to a point of sale (POS) system, the computer may receive from the POS system or other systems connected thereto, a request to authorize payment for the anonymous payment token. The request to authorize payment may also include an amount to be paid by the user to the POS system. Using the anonymous payment token, the computer may retrieve a user account and determine that the user account has sufficient funds for the transaction. Based upon the determination that the user account has sufficient funds, the computer may transmit an authorization confirmation back to the POS system or any other system that the authorization request originated from.

A system uses a large language model (LLM) to implement a controlled artificial intelligence chat environment. The system may control interaction with the LLM using prompt templates that may be selected, customized, and / or modified based on information known about the user with whom the LLM will be interacting. Further, the system may evaluate output of the LLM to make changes to the LLM, the prompt templates, and so on. In some implementations, the system may use evaluation training data to adapt and fine-tune the LLM and / or another language model to evaluate output of the LLM in order to evaluate the efficacy of the chronic condition and / or disease management coaching path(s), and make improvements to the online or offline implementation of the language model in the future.

According to various embodiments, a system and method for verifying a user's identity using both document-based and biometric data is disclosed. The system may prompt a user to upload an image of a government-issued identification document and extract user information from the image using optical character recognition (OCR). The system may also extract the embedded face image from the ID and prompt the user to take a real-time selfie while performing one or more randomized actions or poses. A facial recognition engine may compare the extracted ID image to the live selfie to determine a similarity score. Based on this match, along with optional document authenticity checks, the system may confirm the user's identity in real-time for use cases such as account access, onboarding, and regulatory KYC compliance.

Systems and methods are disclosed for performing an electronic transaction using a hosted transaction page. One method comprises providing a hosted transaction page to a first data system, the hosted transaction page enabling the first data system to request an electronic transaction. Via the hosted transaction page, authentication data may be received from a user. The received authentication data may be encoded into a first format and tokenized into tokenized authentication data. The tokenized authentication data may then be transmitted to the first data system. An authorization request for performing the electronic transaction based on the tokenized authentication data may be received from the first data system, then transmitted to a second data system.

An artificial intelligence driven system of systems may include a layered architecture for providing transaction support to various types of enterprises. A governance layer implements automated governance and policy enforcement through specialized governance modules utilizing generative AI technology. An enterprise layer supports enterprise functions by integrating management and control platforms with digital infrastructure. An offering layer creates and manages system offerings via content generation, personalization, and smart product modules. A transactions layer enables automated transaction orchestration through API integration, execution, and fulfillment modules. An operations layer manages AI systems through generation, training, verification and orchestration modules. A network layer provides adaptive networking capabilities through routing, protocol selection and communication modules. A data layer processes fused data from multiple sources using machine learning and AI systems. A resource layer manages computing, storage, and other resources through specialized resource modules.

A method includes receiving a protection request for an exchange and generating a metadata object including a plurality of outputting attributes for outputting. The method further includes generating a protected NFT including a link with the metadata object. The protected NFT is encapsulated within a control structure that restricts an output of the metadata object. The method further includes signing the protected NFT using at least one of a first private key or a second public key. The method further includes transmitting the signed protected NFT to the remote device and continuously monitoring the exchange. The method further includes detecting, by the control structure, at least one outputting attribute of the plurality of outputting attributes is satisfied and, in response to detecting the at least one outputting attribute is satisfied, outputting at least a portion of the output.