297 results about "Compliance check" patented technology

The invention discloses a contract risk assessment and compliance check method, system and device based on a large language model and a medium, belongs to the cross technical field of artificial intelligence and natural language processing, and aims to solve the technical problem of how to automatically, quickly and accurately identify potential risks and compliance in a contract. According to the technical scheme, the method comprises the steps of data preprocessing, wherein non-plain text format files of various sources are subjected to data preprocessing and converted into plain text format files; constructing a knowledge performing semantic understanding and relation extraction on industrial standards, internal regulations of enterprises and a plain text format file obtained after preprocessing by utilizing a big language, and constructing a structured and queriable knowledge base; training a large language model: optimizing parameters of the large language model in combination with pre-training and supervised training; and risk assessment and compliance check: based on the trained large language model and the compliance rule base, performing identification and analysis of potential risk points and compliance check on the input contract text.

The invention discloses a document information input method and system based on big data processing, and belongs to the technical field of document information processing. According to the method, deep risk feature screening is performed on document data by combining big data mining and a knowledge graph, potential sensitive elements can be accurately identified, risk categories and influence ranges are analyzed based on association rules, automatic early warning and real-time risk notification are realized, a dynamic rule knowledge base is adopted, multi-dimensional compliance verification is supported, and the risk assessment efficiency is improved. Service constraint conditions can be updated in real time, the flexibility and adaptability of rules are ensured, the accuracy and timeliness of compliance check are improved, pattern matching and multi-level check are performed on compliance data objects through an intelligent check process and a recheck rule set trained by big data, the preciseness and reliability of data check are ensured, and the data check efficiency is improved. Through comprehensive quantitative calculation of the business complexity, the risk coefficient and the timeliness priority, the task scheduling weight parameter is generated, the receipt auditing path is optimized, and the auditing efficiency is improved.

A system for improving employee engagement and automating the integration of business processes. The system includes: a user interaction module configured to receive multimodal inputs, including natural language text and voice requests from employees via enterprise portals, mobile applications, voice-activated devices, and collaboration platforms, and to generate real-time responses via conversational output channels; a context processor that is operationally coupled with the user interaction module, wherein the context processor stores the interaction history, employee preferences, organizational role metadata, and task results in both short-term and long-term memory and dynamically derives context for controlling responses and initiating workflows; A natural language and intent processor that is communicatively linked to the context processor. The intent engine consists of large language models trained on company-specific lexicons to perform intent detection, entity extraction, ambiguity resolution, and sentiment or urgency classification from employee queries; a workflow orchestration layer in communication with the intent engine and the context processor, wherein the workflow orchestration layer includes a rule-based and AI-powered process execution engine configured to automatically initiate, route, and complete cross-functional business tasks, including approvals, escalations, and compliance checks, with workflows defined using modular templates that include conditional logic and time-based triggers; Webhooks and authentication protocols provide secure interoperability between the workflow orchestration layer and external enterprise platforms; a feedback and learning module that is operationally coupled with the workflow orchestration layer and the natural language understanding engine, wherein the feedback and learning module is configured to analyze task completion rates, response accuracy, latency metrics, and user feedback signals, and to retrain underlying language and workflow models for adaptive improvement in real time; and an administration console with role-based access controls, compliance dashboards, audit trails and interfaces for workflow configuration, whereby the administration console enables authorized personnel to monitor system operations, adjust interaction rules and enforce data protection restrictions across departments.

The invention discloses a medical health question and answer method and device based on an intelligent agent and a medium, and relates to the technical field of artificial intelligence medical question and answer, and the method comprises the steps: receiving an intention analysis report through a master control intelligent agent, accessing a dynamic dialogue context pool, and generating an intelligent agent cooperation instruction according to the state of the intention analysis report and the state of the dynamic dialogue context pool; performing credibility evaluation on the preliminary medical answer report by using a credibility calibration agent, generating a confidence score and an evidence conflict level, and performing multi-dimensional weighted fusion and risk mode recognition by using a dynamic risk evaluation strategy to generate a diversified disposal instruction; and when the diversified treatment instruction is issuing permission, performing safety compliance check on the preliminary medical answer report to generate compliance medical answers. According to the invention, multi-dimensional control of credibility and security of medical answers is realized, and finally the beneficial effects of providing personalized medical questions and answers and ensuring that information is real, reliable, compliant and safe are achieved.

The present disclosure presents systems, methods, and non-transitory computer-readable media for transforming civil, architectural, or engineering drawings into Building Information Modeling (BIM) or Computer-Aided Design (CAD) models. One such method comprises training an artificial intelligence algorithm on a collection of 2D civil and architectural blueprint designs to enable the artificial intelligence algorithm to efficiently extract elements from the blueprint designs and map them into 3D data model objects; creating a 3D data model using the trained artificial intelligence algorithm, from an input collection of 2D blueprint designs; creating a project database by adding metadata from the input collection of 2D blueprint designs; generating a database of code rules and regulations; performing, using the project database, and the database of code rules and regulations, a compliance check to determine if the 3D data model complies with the database of code rules and regulations; and presenting results of the compliance check.

The invention relates to the technical field of artificial intelligence, can be applied to business scenes of financial science and technology, medical health and the like, and discloses a multi-modal content compliance auditing method, device, equipment and medium, and the method comprises the steps: receiving a multi-modal content set, and generating to-be-audited content; converting the multi-source content into unified semantic representation through an analysis unit; calling the judgment model based on the auditing strategy library and the configured auditing engine to perform semantic comparison, and generating an auditing processing result; outputting an abnormal level result according to the processing result; a rectification suggestion is generated and pushed based on the abnormal level result, and feedback data is received at the same time; recording feedback data and auditing tracking records, and generating a compliance data view and an auditing conclusion; and updating the auditing strategy library and the configured auditing engine according to the feedback data. According to the method, cross-modal check is realized through unified semantic representation, the check flexibility is improved in combination with a strategy library and a configuration engine, rectification and feedback are driven by using an abnormal level result, and the accuracy and efficiency of compliance check are improved.

According to the method, multi-modal data such as voice, images, texts, GIS and Internet of Things sensing are fused, and deep neural network prediction, reinforcement learning scheduling optimization and rule engine compliance check are combined; the intelligent vehicle and material dispatching method and system are applied to multiple scenes such as emergency material storage depots, fire-fighting emergency command, urban disaster response, traffic accidents and medical first aid. The system is interconnected and intercommunicated with an intelligent emergency material storage cloud platform, a city brain, Beidou navigation, intelligent fire fighting and other external platforms, and supports one-key issuing, path optimization, traffic signal linkage and whole-course return closed loop. Compared with the prior art, the method has the advantages that unification of multi-modal situation awareness, data-driven optimal scheduling and expert knowledge constraints is realized, the response time is remarkably shortened, the resource utilization rate is improved, and compliance safety is ensured.

Orchestration solutions for agentic automation for artificial intelligence (AI) agents, robotic process automation (RPA) robots, agentic orchestration processes (AOPs), and humans-in-the-loop with self-healing and capabilities to increase autonomy. Agentic orchestration, via a conductor application, enables the automation, modeling, and monitoring of complex business processes from start to finish. A user or an initiating software process requests that a given AOP be run. The AOP defines a business process (e.g., in Business Process Model and Notation (BPMN)), and may utilize one or more RPA robots, one or more AI agents, and / or one or more humans to assist with accomplishing this process, such as resolving invoice discrepancies, onboarding an employee, performing compliance checks, synchronizing order data among multiple backend systems, etc.

The embodiments disclose a cryptographically governed system for contextual memory management in artificial intelligence including a Contextual Orchestration and Scoped Memory Protocol (COSMP) and a Decentralized Memory Wallet (DMW), which enforce secure, auditable, and policy-driven access to AI memory. Traditional token-based memory tracking is replaced by memory capsules secure data units with embedded access policies and tamper-evident logs 5400 organized via a distributed ledger. Access control is managed through decentralized identifiers (DIDs) and private cryptographic keys, ensuring that all memory interactions are signed, verifiable transactions. This architecture establishes a universal trust layer for AI, enabling post-hoc compliance checks and privacy-preserving audits. Applicable across domains such as national security, healthcare, and autonomous systems, the invention enforces rigorous behavioral constraints and access governance within AI memory and decision-making processes.

The invention discloses a bank system research and development project management system, and the system comprises an intelligent management platform which generates a compliance check list and a difference report through the real-time butt joint of a supervision database; the risk prediction module is used for predicting risk levels such as research and development cycle delay and resource hyperbranched, triggering early warning and suggesting a deployment scheme; the block chain evidence storage and tracing module is used for storing the hash value and the operation record of the key node document in a chaining manner, and solidifying a timestamp and a person in charge; the task collaboration module is used for analyzing a demand document by using NLP, automatically disassembling the demand document into an executable task tree, analyzing manpower and equipment conflicts through a resource occupation graph, and intelligently generating a deployment scheme; and the security control module is used for implementing hierarchical authority based on role and data sensitivity, and sensitive operation needs dual verification of biometric authentication and dynamic token to prevent unauthorized access. The system is high in risk resistance, high in overall research and development efficiency and fast in data management and auditing, and can meet the requirements in the research and development process of a bank system.

The invention discloses a software process arrangement system and method based on a large model, and particularly relates to the technical field of software process arrangement. The intelligent process design module is used for realizing intelligent and low-threshold process design and optimization through natural language understanding and a visualization technology; the Agent collaborative execution module is used for dynamically distributing tasks, monitoring states and coordinating a plurality of Agents to efficiently complete process execution; and the knowledge learning enhancement module is used for constructing a domain knowledge system and providing intelligent support for process decision and optimization. According to the method, the demand described by a natural language of a user is converted into a structured process definition through the intelligent process design module, rapid design is carried out by utilizing a process pattern library and a visual editing tool, and meanwhile, compliance check and optimization suggestion are carried out, so that compliance and high efficiency of process design are ensured, and the process design efficiency is improved. And the Agent collaborative execution module dynamically allocates tasks to appropriate Agents according to process requirements, monitors the execution state in real time, and performs coordinated processing in case of abnormality to ensure efficient execution of the process.

The invention discloses a static database self-adaptive fuzzification desensitization implementation method for highly sensitive data in the power industry. The method comprises the following steps: a data preprocessing module, a sensitivity analysis module, a fuzzification algorithm module, a self-adaptive mechanism module and an effect evaluation and verification module. Compared with the prior art, the method has the advantages that 1, self-adaptive dynamic adjustment is performed: a desensitization strategy is automatically optimized according to data characteristics and use scenes, and privacy protection indexes (such as k-anonymity values) are improved by 30%-50%; 2, multi-dimensional balance: the information loss rate is reduced by 10%-20%, the query accuracy is improved by 5%-10%, and safety and service requirements are considered; 3, system expansibility: a plug-in architecture supports dynamic loading of new algorithms and rules, and a configuration management module realizes strategy real-time adjustment; and 4, compliance guarantee: through a law and regulation rule base and a compliance check algorithm, the compliance is ensured to meet the standard.

The embodiment of the invention provides a report customization method and device based on medical data. A report customization method based on medical data belongs to the technical field of data processing, and obtains standardized data after redundant data, missing data and inaccurate data are removed through data cleaning and standardization processing, so as to improve the data source quality of a generated report. The method comprises the following steps: standardizing data of a user demand report, generating structured data by performing multi-dimensional analysis and feature extraction on the standardized data to highlight the correlation between the data so as to facilitate the generation of a high-quality report, and finally, mapping the structured data to a user demand report template and combining compliance check and risk assessment rules embedded in the user demand report template so as to improve the user demand report quality. And the function that the report meets the customized demand of a customer is further improved.

A platform for architectural drawing generation and approval which allows for easy generation of 3D architectural images from text descriptions, question and answer templates, and / or sample images for user or designer review and approval, and conversion of those 3D architectural images to 2D architectural drawings for permitting and construction. In an embodiment, the system and method involve generating structured requirements via a question and answer structured template, generating 3D images from a combination of the structured requirements and sample images provided by a user, and generating 2D architectural drawings from the 3D architectural images. In an embodiment, the 2D architectural drawings can be submitted for automated code compliance checking via one or more architectural modeling engines.

The invention belongs to the technical field of computer-aided project management, and discloses an electric power engineering design project management system and method, and the system comprises a data integration and processing module, a multilayer dynamic knowledge graph data storage library, a graph-based automatic compliance check engine, and a graph neural network-based predictive risk engine. And an active design change impact analysis module. According to the method, a unified and intelligent project data core is constructed, heterogeneous data sources such as design files and law and regulation texts are integrated in a multi-layer dynamic knowledge graph, automatic compliance review is realized by utilizing graph query, data-driven risk prediction is realized by utilizing a graph neural network GNN, and the risk prediction efficiency is improved. And the linkage influence of design change can be simulated and quantitatively evaluated. According to the method, the problems of data islanding, passive compliance examination, subjective risk management, difficulty in change analysis and the like in the prior art are solved, and the management efficiency, accuracy and initiative of the electric power engineering design project can be remarkably improved.

A system (100) for automating financial consolidation and reporting in a cloud-based ERP environment, comprising: a data aggregation and integration module configured to collect and integrate financial data from multiple sources, including ERP, accounting software, and third-party applications; an AI-driven cross-company reconciliation module configured to use machine learning algorithms to identify and eliminate cross-company transactions, detect duplicate entries, missing records, and transaction discrepancies; a currency conversion and standardization module configured to enable real-time currency conversions and ensure compliance with international accounting standards such as IFRS and GAAP; a compliance and audit module configured to monitor compliance with financial regulations and tax laws, automate audit trails, and generate compliance reports; a financial analysis and anomaly detection module configured to analyze financial patterns, detect anomalies, and prevent fraudulent activities using artificial intelligence; a report creation and customization module configured to automate the creation of financial reports, balance sheets, and cash flow reports with customizable templates; a scalability and cloud deployment module configured to deploy the system (100) in a cloud-based ERP environment and enable real-time access to financial reports and dashboards; an automation and workflow optimization module configured to minimize manual intervention by automating data reconciliation, reporting, and compliance checks; a security and access control module configured to implement role-based access control, encryption, and authentication mechanisms to ensure data security; and an integration and API management module configured to enable seamless connectivity with external financial applications and enterprises via APIs.

The invention relates to the technical field of computer information security, in particular to a method and a system for compliance check based on a windows operating system, comprising the following steps: a preparation stage: identifying applicable laws and regulations and industry / internal security standards, selecting check tools, and formulating project plans; in the data acquisition stage, an operating system version, a patch, a user permission, network configuration and log information are acquired through WMI or PowerShell; the beneficial effects are that through the automatic compliance inspection process, the manual inspection time is greatly reduced, and the working efficiency is improved; and monitoring a plurality of dimensions, such as configuration, application, permission, patches and the like, of the Windows operating system to ensure that various configurations of the operating system meet security standards.

Disclosed is a procurement optimization approach that integrates real-time reinforcement learning and blockchain-based compliance checks for dynamic, transparent decision-making. Initial procurement specifications and weightings are automatically generated using AI analysis of historical procurement data, followed by supplier evaluations using multiple criteria decision analysis with buyer-defined weightings, while a reinforcement learning module continuously refines these weightings based on observed procurement outcomes or feedback. Each updated weighting is automatically verified against predefined procurement rules encoded on a distributed ledger, ensuring that no unauthorized criteria change bypass regulatory thresholds. If found compliant, the system immutably stores the refined weighting and resulting supplier evaluation as a ledger transaction, creating an unalterable audit trail. Optional modules handle anomaly detection, predictive risk analytics, duplication detection across departments, automated tender generation, quantum-resistant cryptography, and ERP integration. This modular design addresses persistent procurement challenges: static weighting, delayed or incomplete compliance checks, and limited traceability. By unifying adaptive AI logic with an immutable ledger, the disclosed system offers robust, real-time improvements in cost efficiency and governance.

The invention relates to the technical field of intelligent detection, and particularly discloses a method for intelligently matching software compliance of motor vehicle inspection and detection equipment, which comprises the following steps of: firstly, constructing a software compliance inspection database based on a standard file; carrying out semantic analysis on each compliance test item in the database and the software information of the motor vehicle inspection and detection equipment by adopting a natural language processing technology based on deep learning, and respectively extracting semantic feature representations of the equipment software information and each compliance test item; and furthermore, the equipment software information is inquired and matched with each compliance test item, so that compliance detection of the motor vehicle inspection and detection equipment software is intelligently realized. Therefore, the efficiency and the accuracy of compliance inspection can be greatly improved, the subjectivity and the error of manual auditing are reduced, the updating and the change of a software version are better adapted, and the software of the motor vehicle inspection and detection equipment is ensured to accord with the latest specified standard.

The invention provides a building industry finance and tax compliance digital evidence chain integrated platform which is deployed based on a cloud computing architecture and comprises a distributed server cluster, a network communication module and a database storage system. By constructing the integrated digital platform, fundamental efficiency improvement and risk management and control reinforcement of finance and taxation management in the building industry are realized, the platform enables a data acquisition process to be highly automatic, manual repeated entry work is greatly eliminated, financial personnel are liberated from tedious account checking, and the financial personnel are greatly improved. The compliance check module based on a rule engine and artificial intelligence can perform real-time and comprehensive automatic analysis on all transaction data, significantly improves the identification accuracy and timeliness of potential compliance risks, realizes instant alarm, converts passive risk response into active risk response, and improves the risk handling efficiency. Compared with a traditional manual mode, the data processing speed is improved in order of magnitude, the monthly checkout and report generation time is greatly shortened, the enterprise decision cycle is remarkably accelerated, and the overall operation efficiency is improved.

Embodiments of the present disclosure relate to methods and apparatuses for compliance check in a communication system. According to some embodiments of the disclosure, a UE may: receive, from a BS, an RRC reconfiguration message for mobility; and transmit, to the BS, an RRC complete message in response to receiving the RRC reconfiguration message for mobility. The RRC reconfiguration message for mobility may be associated with an enhanced CPA or an enhanced CPC.

The invention relates to the technical field of computer science, and discloses a cryptographic logic vulnerability detection method and system based on a large language model. The method comprises the following steps: firstly, constructing a diversified cryptographic vector knowledge base, and organizing and managing through text vectorization; based on cryptographic algorithm standards such as FIPS, performing logic compliance check on the target code; in combination with a small number of examples and thinking chain prompts, guiding a large language model to identify potential logic vulnerabilities; summarizing a compliance check and reasoning process result, and retrieving related knowledge in a knowledge base based on cosine similarity to enhance model judgment; and finally, integrating knowledge enhancement and logic analysis results, and outputting a structured vulnerability detection report. According to the method, a universal cryptographic vulnerability detection framework which does not need to run codes and is suitable for multiple programming languages is constructed, automatic recognition and detection of complex logic defects in cryptographic codes are achieved, and the accuracy and reasoning ability of a large language model in a cryptographic vulnerability detection task are improved.

The invention provides a dynamic collaborative management method and system for intelligent configuration of DevOps in the power industry, and belongs to the technical field of operation and maintenance management of a power information system.The method comprises the steps that a natural language instruction of a user is analyzed, a target application, a target environment identifier and a target version are recognized, and a deployment request is generated; in response to the deployment request, calling the security baseline configuration library to execute static code compliance check to generate an application version package; deploying the application version package to a target environment, and synchronizing deployment data to a knowledge graph; after deployment is completed, a dynamic configuration change request is generated, a security baseline configuration library is called to execute dynamic configuration compliance verification, and dynamic configuration is updated to a target environment; and the running state of the target application is monitored in real time, dynamic configuration is automatically adjusted when the target environment changes, and fault positioning and repairing are executed based on the knowledge graph when the running state is abnormal. According to the invention, full-life-cycle management from a user instruction to application deployment, configuration management, operation monitoring and fault processing is realized.

The invention provides a dynamic auditing and risk control supervision method based on multiple Agents, aims to solve the problems of insufficient heterogeneous data processing capability, inaccurate risk identification and low auditing efficiency in the prior art, and constructs a heterogeneous data analysis Agent, a retrieval enhancement generation Agent, an intelligent risk identification Agent and an automatic auditing process Agent based on a multi-Agent system framework. Comprehensive analysis and processing of various data sources are achieved, and the retrieval efficiency and coverage rate of risk elements are improved through vectorization retrieval and dynamic SQL query. The risk identification capability is dynamically optimized through a pre-training model in combination with historical risk case analysis, and high-reliability compliance review is realized in combination with a regulation content library. The method can support various automatic auditing processes, including text review, financial analysis and error correction review, and generation of a standardized auditing result report, obviously improves auditing efficiency and precision, reduces compliance risks, and is widely applicable to the fields of financial auditing, enterprise risk control, compliance check and the like.

The invention relates to the technical field of artificial intelligence, and discloses a data processing method and device based on a mirror data layer, computer equipment and a storage medium, and the method comprises the steps: obtaining to-be-submitted data, generating submission batch information for the to-be-submitted data based on a data exit layer, and carrying out the partition management of the to-be-submitted data, and submitting the to-be-submitted data to a specified mechanism, when it is detected that the to-be-submitted data is submitted successfully, obtaining storage receipt information returned by the specified mechanism after receiving the to-be-submitted data; and when determining that the to-be-submitted data is successfully stored based on the storage receipt information, writing the to-be-submitted data into the mirror image data layer, and performing partition management on the to-be-submitted data according to the submission batch information to complete data submission of the to-be-submitted data. In the financial insurance field, especially in the life insurance business, the mirror image data layer provides a reliable data basis for data auditing and compliance inspection, the accuracy in the data management process is ensured, manual intervention is reduced, and an insurance company is helped to meet supervision requirements.

The invention discloses an object-centered business process violation inspection method and system based on Tokine replay, and belongs to the field of process mining, and the method comprises the following steps: constructing an object graph from an object-centered business process event log, and extracting process execution; deleting cross-layer redundant dependencies in process execution, dividing the process execution according to echeles, and obtaining a binding sequence; performing Tokine replay in the multi-object Petri net model according to the binding sequence to obtain a replay result and a deviation result; and quantifying the compliance according to the fitting degree, and displaying a part with serious deviation in the process by using a local diagnosis method to obtain an object as a center business process violation inspection result. The system comprises an object graph and process execution acquisition module, a binding sequence acquisition module, a replay result and deviation result acquisition module and an object center business process violation check result acquisition module. For the object-centered business process, the method provided by the invention improves the accuracy of the compliance check of the object-centered business process.

The invention discloses a forest illegal felling identification system based on computer vision, and the system comprises the following modules: a multi-source collection module which is used for collecting data and generating a unified space-time identification data set and an index; the correction registration module is used for correcting data, performing cross-sensor registration and unified resampling, and outputting an aligned image and a geo-fence index; the double-flow change module is used for pairing different time phase sub-graphs according to spatial-temporal indexes, constructing an improved double-flow network to generate a continuous change thermodynamic diagram and extracting candidate change blocks; the vector segmentation module is used for carrying out segmentation, refinement and vectorization under geo-fence constraints to obtain a fine-grained target set; the compliance checking module is used for combining the graph database and the rule engine to carry out space-time compliance checking; and the alarm judgment module is used for edge rapid reasoning and alarming, cloud rechecking and multi-source verification to form a judgment result set. The system gives consideration to accuracy and timeliness, and is suitable for continuous supervision and law enforcement evidence collection of forest regions under complex weather and topographic conditions.

The invention relates to the technical field of system compliance management, and discloses a system compliance early warning method and system, electronic equipment and a storage medium, and the method comprises the steps: collecting system file data, and carrying out the standardization processing and structural analysis; data preparation is carried out based on the system metadatabase and the supervision fine tuning corpus set, an initial model is constructed and trained, a trained system large model is formed, and version management is carried out; determining early warning types, establishing a system revision early warning model for different early warning types, and triggering early warning reminding according to an output result of the early warning model; performing difference comparative analysis on the same-theme systems based on the system large model, and generating a compliance inspection report; receiving a natural language question, generating an answer and providing system traceability information; a system outline is generated according to system revision requirements, a chapter summary and clause content are generated based on the system outline, and real-time compliance check and clause recommendation are supported. According to the invention, the intelligent demand of enterprise system full-life-cycle management can be met.

The invention relates to the technical field of auxiliary bid evaluation, and discloses an intelligent auxiliary bid evaluation method and system based on machine learning and a cloud platform, and the method comprises the steps: automatically analyzing project information and a bid invitation file through a natural language processing module, constructing a structured evaluation task definition, such as a compliance list and a comparison matrix header, and carrying out the automatic analysis of the project information and the bid invitation file; and converting the unstructured bid evaluation requirement into a machine executable task. Meanwhile, the bidding file is parsed in parallel and structured into a unified data format; and based on a preset review rule, performing efficient extraction and compliance verification on mass bidding data to form a multi-dimensional data cube. And then, cleaning, alignment and difference analysis are carried out on the data cubes, a visual compliance report and a KPI comparison matrix are automatically generated, and bid evaluation experts are assisted to make decisions. Therefore, by introducing the machine learning and cloud platform technology, automation, intelligence and standardization of the bid evaluation process are realized, the bid evaluation quality and efficiency are remarkably improved, and powerful technical support is provided for bidding and tendering.

The embodiment of the invention discloses a file cross-network transmission method and device and a computer readable medium. A specific embodiment of the method comprises the steps of determining file structure information of a to-be-transmitted file in response to the fact that the to-be-transmitted file passes compliance check; determining whether a target file template exists or not according to the file structure information; performing file content separation on the to-be-transmitted file to obtain a target file; generating a chained invisible watermark according to a template identifier corresponding to the target file template, meta-file information corresponding to the to-be-transmitted file and the target file; embedding the chain type invisible watermark into the file to be transmitted to obtain a watermark embedded file; according to the meta-file information, a ferry server matched with the to-be-transmitted file is distributed through a distribution server; and according to the ferry mode, the file embedded with the watermark is transmitted to an external storage space in a cross-network manner through the ferry server. According to the embodiment, efficient and safe cross-network data transmission is realized.