Intelligent employment settlement and compliance service system for flexible employment scene

Abstract

The invention relates to the technical field of intelligent services, and discloses an intelligent employment settlement and compliance service system for a flexible employment scene, which comprises a distribution module, a management module, a calculation module, a declaration module and a central platform module, and is characterized in that the distribution module distributes an independent access domain name for each user through containerization; and an independent account space is suggested, and a standard or non-standard contract template is stored in the management module. Through the multi-tenant architecture based on the independent domain name and the exclusive account system, the platform can provide logic isolation, independent configuration and safe isolation business space for a plurality of merchants, each tenant is completely independent in the aspects of data storage, business rules, fund accounts, contract templates and the like, the high-risk problems of data cross renting, authority exceeding and the like are effectively prevented, and the service safety of the tenants is improved. Federated deployment of a flexible employment platform is facilitated, a plurality of heterogeneous merchants can be served in one platform, and good business expandability and business replication capability are achieved.

Description

Technical Field

[0001] This invention relates to the field of intelligent service technology, specifically to an intelligent employment settlement and compliance service system for flexible employment scenarios. Background Technology

[0002] With the development of the digital economy, flexible employment models have been widely adopted in various industries such as logistics, e-commerce, manufacturing, retail, and catering. Enterprises employ part-time, short-term, and project-based workers to address needs arising from temporary situations, large fluctuations in workforce, and sensitivity to labor costs. Meanwhile, flexible employment platforms are gradually becoming a crucial bridge between employers and employees, handling functions such as job posting, identity verification, contract signing, task recording, payroll settlement, and tax processing.

[0003] Existing flexible employment systems suffer from technical bottlenecks, including complex payroll calculations, opaque payment processes, fragmented working hours, diverse pricing models, high rates of manual intervention leading to errors or delays, a lack of automated tax filing processes, significant regional policy differences making manual filing time-consuming and labor-intensive, compliance risks for businesses, a lack of standardized identity verification and contract signing, reliance on weak authentication methods, non-standardized contract processes lacking legal validity, and a lack of isolation mechanisms in multi-tenant management. When the same platform serves multiple merchants, data sharing, resource misuse, and security risks are high, resulting in poor operational flexibility. Therefore, there is an urgent need for a technical solution that features automated settlement, tax compliance, trustworthy employment, and tenant federation to address the current pain points of flexible employment platforms. Summary of the Invention

[0004] This invention provides an intelligent employment settlement and compliance service system for flexible employment scenarios. It has the beneficial effects of automating various complex payroll calculations and ensuring compliance and security. It solves the problems mentioned in the background technology, such as complex payroll calculation, opaque payment process, lack of automation in tax declaration process, lack of unified standards for identity verification and contract signing, and lack of isolation mechanism for multi-tenant management.

[0005] This invention provides the following technical solution: an intelligent employment settlement and compliance service system for flexible employment scenarios, comprising:

[0006] The allocation module assigns an independent access domain name to each user through containerization and suggests independent account space;

[0007] The management module stores standard or non-standard contract templates. Based on the user's needs, it automatically matches and retrieves the matching standard or non-standard contract template using an NLP model, thereby obtaining the signed and confirmed standard or non-standard contract and uploading it to the independent account space for storage.

[0008] The calculation module determines the salary based on the signed and confirmed standard or non-standard contract, and establishes an independent settlement channel for settling the salary.

[0009] The declaration module has built-in tax rules and dynamically identifies tax responsibilities and automatically declares them based on the local tax rules.

[0010] The central platform module is used to collect operational data from each user for report analysis.

[0011] As an optional solution to the intelligent employment settlement and compliance service system for flexible employment scenarios described in this invention, it further includes:

[0012] The security module uses real-name authentication, facial recognition, and bank card four-factor authentication to adaptively select a combination of verification methods based on the risk level, thereby strengthening the uniqueness and credibility of the user's identity.

[0013] The central platform module analyzes and determines the risk level based on the collected user operation data, and isolates permissions by using user identity and access control policies to ensure that operations and data cannot be accessed interchangeably.

[0014] As an optional solution of the intelligent employment settlement and compliance service system for flexible employment scenarios described in this invention, the management module analyzes the user's requirements, adaptively modifies the non-standard contract by combining context analysis, and annotates and parses the rights and obligations of both parties on the non-standard contract by combining historical information in the database.

[0015] The historical information in the database includes example descriptions that match the rights and obligations in the annotations;

[0016] The risk-sharing level is precisely optimized by combining the modified non-standard contract with matching example descriptions through the central platform module, and then confirmed by the user.

[0017] As an optional solution of the intelligent employment settlement and compliance service system for flexible employment scenarios described in this invention, the management module determines the task, task income, identity attributes, tax payment location and wage payment information data based on the confirmed standard or non-standard contract.

[0018] The management module estimates risk and profit based on the identified tasks and instance descriptions, and determines the average market profit by searching for similar identified tasks at the current time point, generating an analysis report for users to query.

[0019] As an optional solution to the intelligent employment settlement and compliance service system for flexible employment scenarios described in this invention, the declaration module dynamically identifies tax liability based on the determined task, task income, identity attributes, tax location and wage payment information data;

[0020] When income exceeds the tax threshold, the withholding policy is activated through the declaration module according to the region, and the individual income tax calculation, withholding declaration and tax form generation are completed automatically.

[0021] As an optional solution of the intelligent employment settlement and compliance service system for flexible employment scenarios described in this invention, the declaration module connects to the electronic tax bureau, tax SaaS system and third-party tax service platform through API interface to realize the automatic submission of tax declaration data;

[0022] After the declaration is completed, the declaration module automatically receives and synchronizes tax voucher documents and tax records to the user's independent account space;

[0023] The declaration module uses an adapter pattern to encapsulate the interface protocols of different tax platforms, supporting parallel declarations across multiple platforms.

[0024] The declaration module automatically matches the optimal declaration path based on the location of employment and synchronizes the tax payment certificate and electronic payment receipt with one click.

[0025] As an optional solution of the intelligent employment settlement and compliance service system for flexible employment scenarios described in this invention, the management module initiates a two-way signing process through the electronic signature platform after the contract template is determined. During the signing process, the mobile phone numbers of all parties are verified for real-name authentication. The signing timestamp, operation IP address and device information are recorded during the signing process, and the above information is stored as a signing log.

[0026] The management module uploads the hash value, signing time, and signer identifier of the signed contract to the blockchain for evidence storage, obtains the blockchain evidence storage result, and generates tamper-proof electronic evidence.

[0027] The blockchain-based evidence storage results are associated with the contract documents and stored in the user's independent account space, supporting post-event verification and judicial retrieval.

[0028] As an optional solution of the intelligent employment settlement and compliance service system for flexible employment scenarios described in this invention, the security module performs identity verification in the task execution, contract signing and salary payment stages, and cross-compares the facial images, ID card information and bank card information collected in each stage;

[0029] When the comparison results are inconsistent, a risk warning is generated and subsequent operations are suspended.

[0030] The present invention has the following beneficial effects:

[0031] 1. This intelligent employment settlement and compliance service system for flexible employment scenarios, through a multi-tenant architecture based on independent domain names and dedicated account systems, can provide multiple merchants with logically isolated, independently configured, and securely isolated business spaces. Each tenant is completely independent in terms of data storage, business rules, fund accounts, and contract templates, effectively preventing high-risk issues such as data cross-leasing and unauthorized access. It is conducive to the federated deployment of flexible employment platforms, serving multiple heterogeneous merchants within a single platform, and has good business scalability and commercial replication capabilities.

[0032] 2. This intelligent employment settlement and compliance service system for flexible employment scenarios uses a natural language processing model for semantic analysis and a rule engine to match job type, work method, region, and compensation model to recommend the most suitable template. It supports automatic calculation of remuneration for various complex pricing methods such as hourly wage, piece-rate payment, and performance subsidies, which greatly reduces the cost of manual calculation and verification. It supports integration with multiple payment channels, and the payroll process is fast, secure, and the accounts are clearly divided. Users can view work hours records and income details in real time, which improves the platform's transparency and trustworthiness.

[0033] 3. This intelligent employment settlement and compliance service system for flexible employment scenarios automatically identifies whether the conditions for withholding and paying individual income tax are triggered. Combining task attributes, regional policies, and user roles, it intelligently calculates the tax amount and generates declaration materials. It can connect to the tax system to realize functions such as invoice issuance, individual income tax declaration, and voucher archiving. It effectively avoids legal risks caused by enterprises or platforms due to payment and reporting on behalf of others, reduces the financial and tax processing costs of the operation team, and enhances the ability to resist audits. Attached Figure Description

[0034] Figure 1 This is a schematic diagram of the overall structure of the present invention. Detailed Implementation

[0035] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0036] Example 1

[0037] Please see Figure 1 One type of intelligent employment settlement and compliance service system for flexible employment scenarios includes:

[0038] The allocation module assigns a unique access domain name to each user through containerization and suggests independent account space;

[0039] The management module stores standard or non-standard contract templates. Based on the user's needs, it automatically matches and retrieves the appropriate standard or non-standard contract template using an NLP model, thereby obtaining a signed and confirmed standard or non-standard contract and uploading it to a separate account space for storage.

[0040] The calculation module determines the salary based on the signed and confirmed standard or non-standard contract, and establishes an independent settlement channel for salary settlement.

[0041] The declaration module has built-in tax rules and dynamically identifies tax responsibilities and automatically declares them based on the applicable local tax rules.

[0042] The central platform module is used to collect operational data from various users for report analysis.

[0043] Specifically, regarding the allocation of independent access domain names, after a user successfully registers, the system automatically generates a unique subdomain in the format: [user-id].platform.com. Domain routing is implemented through DNS resolution and Nginx reverse proxy. It supports enterprise users binding their own domain names (such as hr.company.com) to enhance brand credibility.

[0044] The independent account space is built using containerization technology (Docker + Kubernetes) to create an independent running instance for each user. Each instance contains a dedicated application service container, database sharding (MySQL schema isolation), and object storage buckets (such as OSS). Access is strictly restricted within the account space; cross-user access requires authentication through an API gateway. Through a multi-tenant architecture based on independent domains and a dedicated account system, the platform can provide multiple merchants with logically isolated, configuration-independent, and security-isolated business spaces. Each tenant is completely independent in terms of data storage, business rules, financial accounts, and contract templates, effectively preventing high-risk issues such as "data cross-tenancy" and "authority violations." This facilitates "federated deployment" of the flexible workforce platform, serving multiple heterogeneous merchants within a single platform, and possessing excellent business scalability and replicability.

[0045] The contract template library includes pre-built templates for various standard contracts, such as "Labor Service Agreement," "Project Outsourcing Contract," and "Short-Term Employment Agreement." Users can also upload non-standard contracts (PDF / Word), which the system automatically archives and extracts key fields. An intelligent matching mechanism takes user input of employment needs, such as "UI designer, remote, Beijing, payable per project," and uses a Natural Language Processing (NLP) model (based on BERT fine-tuning) for semantic analysis. Combined with a rule engine (Drools), it matches job type, work method, region, and payment model to recommend the most suitable template. If a non-standard contract is uploaded, the NLP model automatically extracts fields such as "salary amount," "service period," and "payment cycle" for subsequent calculations. The system supports automatic calculation of remuneration for various complex pricing methods, including hourly wages, piece-rate pay, and performance-based subsidies, significantly reducing manual calculation and verification costs. It supports integration with multiple payment channels (banks, housing provident funds, third-party wallets), ensuring fast, secure, and transparent payroll. Users can view work hours and income details in real time, improving platform transparency and trust.

[0046] In the electronic signing process, after the contract is generated, a two-way signing is initiated by integrating a third-party electronic signature platform, such as eSign. The signing process uses mobile phone number authentication, facial recognition, timestamps, and IP records for identity verification. After the signing is completed, the contract document is encrypted and stored in the user's independent account space, and a hash value is generated and stored on the blockchain, such as AntChain.

[0047] The dynamic identification of tax liability uses the tax rules engine to determine the nature of income (labor remuneration, business income) and whether it reaches the tax threshold, such as whether a single transaction is more than 800 yuan and whether the tax collection policy applies.

[0048] This outputs the types of taxes payable, tax rates, and withholding agents;

[0049] Input data includes task type, task income, identity attribute (natural person / self-employed), tax payment location, and cumulative income;

[0050] Among them, when income exceeds the tax threshold, the local withholding policy will be automatically activated.

[0051] Automatically calculates individual income tax and reserves tax funds. Monthly summary and generation of the "Individual Income Tax Withholding Declaration Form" are available for one-click filing via the e-Tax Bureau API. Supports integration with tax SaaS systems or third-party interfaces for multi-platform synchronization.

[0052] Tax form generation and delivery:

[0053] Automatically generates tax documents such as "Tax Payment Certificate" and "Withholding Details";

[0054] Pushed to the accounts of employers and freelancers, supporting download and blockchain storage;

[0055] In summary, by automatically identifying whether the conditions for individual income tax withholding and payment have been triggered, and combining task attributes, regional policies, and user roles, the system can intelligently calculate tax amounts and generate declaration materials. It can connect to the tax system to realize functions such as invoice issuance, individual income tax declaration, and voucher archiving. This effectively avoids legal risks for enterprises or platforms caused by "payment and reporting on behalf of others," reduces the financial and tax processing costs of the operations team, and enhances the ability to resist tax audits.

[0056] The data collection scope includes the number of employees, total settlement amount, geographical distribution, job type, total tax amount, and number of active users. The data is extracted from each container instance periodically through a security agent and then entered into the data warehouse after being anonymized.

[0057] The report analysis function generates multi-dimensional visualization reports:

[0058] The platform overview includes monthly transaction volume, tax contribution, and user growth trends;

[0059] Regional analysis reveals the employment trends and policy implementation in various regions;

[0060] The enterprise profile includes its labor cost structure and project expenditure distribution;

[0061] It supports web-based viewing, PDF export, and API access.

[0062] Among them, the data security mechanism strictly follows the "minimum necessary" principle, only collects authorized data, adopts field-level anonymization (such as ID card masking and IP hashing), and supports GDPR and Personal Information Protection Act compliance audits.

[0063] Example 2

[0064] This embodiment is an improvement upon embodiment 1. For details, please refer to [link / reference]. Figure 1 It also includes a security module, which uses real-name authentication, facial recognition and bank card four-factor authentication to automatically select a combination of authentication methods based on the risk level, thereby strengthening the uniqueness and credibility of the user's identity.

[0065] The central platform module analyzes and determines the risk level based on the collected user operation data, and isolates permissions by using user identity and access control policies to ensure that operations and data cannot be accessed interchangeably.

[0066] The security module performs identity verification at each stage of task execution, contract signing, and payroll disbursement, and cross-compares the facial images, ID card information, and bank card information collected at each stage;

[0067] When the comparison results are inconsistent, a risk warning is generated and subsequent operations are suspended.

[0068] Real-name authentication is performed by connecting to the Ministry of Public Security's Internet Trusted Identity Authentication Platform (CTID) to verify the consistency between the name and the ID number.

[0069] The face recognition liveness detection calls Alibaba Cloud IDVerify or Tencent Shield SDK, and supports blinking / mouth opening actions to prevent photo and video forgery;

[0070] The four-factor authentication of bank cards involves verifying the name, ID number, bank card number, and registered mobile phone number, and calling the UnionPay or third-party payment institution API to confirm the ownership of the receiving account.

[0071] It should be noted that all verification interfaces use HTTPS and national cryptographic SM2 / SM3 encryption to ensure secure transmission.

[0072] Furthermore, the collected user operation data includes login behavior, such as abnormal times and logins from different locations; device fingerprints, such as new devices and emulators; operation frequency, such as frequent contract modifications and multiple failed attempts; payroll patterns, such as large amounts, high frequency, and changes in bank cards; and fluctuations in contract signing frequency and amount. The risk level is:

[0073] ;

[0074] The scoring uses either a rule engine (Drools) or a lightweight machine learning model (XGBoost) and is updated daily or calculated in real time.

[0075] Based on the risk level, the system automatically matches the following identity verification combinations:

[0076] Example of risk level recommendation verification combination trigger scenario;

[0077] Low-risk real-name authentication + mobile verification code to view contract drafts;

[0078] Medium-risk real-name authentication + facial recognition for contract signing and task submission;

[0079] High-risk cases involve issuing salaries exceeding 50,000 yuan after real-name authentication, facial recognition, and bank card verification; and requiring a change of the receiving card.

[0080] The central platform module is not only used for report analysis, but also serves as the central hub for overall security governance. It generates risk levels based on collected operational data and drives access control policies to ensure that all operations and data within the system are strictly isolated.

[0081] In the user identification system, each user is generated with a unique identifier (UserID) during registration, in the format U-{timestamp}-{random}.

[0082] The identity identifier is bound to the following information: role type (enterprise administrator, freelancer, platform operator), affiliated organization (enterprise account), and container instance ID (KubernetesPodName).

[0083] The access control policy adopts the attribute-based access control (ABAC) model, which combines identity identification and risk level dynamic authorization.

[0084] If the risk level is >70, the total daily salary payment is limited to ≤50,000 yuan, bank card changes require manual review, and exporting other people's contracts or settlement records is prohibited.

[0085] By containerizing and allocating independent database shards and storage buckets to each user, resource-level isolation is achieved. All API requests must carry an identity token (JWT) containing the user_id and role. The server-side middleware automatically verifies whether the requested resource belongs to the user_id. Cross-account access requires platform approval and is logged in audit logs. When displaying aggregated data in the central platform reports, sensitive fields (such as ID cards and bank cards) are masked or hashed, supporting GDPR's "right to be forgotten" and deletion requests under the Personal Information Protection Act. When abnormal behavior is detected, such as multiple logins with the same identity in different locations or inconsistent facial recognition, the system automatically triggers a risk warning, suspends high-risk operations, and notifies the platform's risk control team and relevant enterprise administrators. User appeals and manual review channels are supported.

[0086] Here is an example of the module collaboration process:

[0087] Taking a freelancer receiving a large sum of money for the first time as an example, the user submits the task results, and the system requires facial recognition verification (medium risk).

[0088] The system judged the application for a salary of 80,000 yuan as a high-risk operation (large amount + new bank card).

[0089] Triggering dual verification of four elements + facial recognition;

[0090] The central platform compared historical data and found that the user had changed bank cards twice in the past week, raising the risk score to 75.

[0091] The system limits the maximum amount that can be disbursed this time to 50,000 yuan. The remaining 30,000 yuan requires manual review. After the review is approved, the funds will be transferred and the operation log will be stored on the blockchain.

[0092] In summary, this example breaks through the static authentication model, implementing an intelligent security strategy where the higher the risk, the stricter the verification. It adopts a closed-loop governance approach for identity, permissions, and data, forming a complete security chain from identity verification to access control and data isolation. Furthermore, it combines containerization and the ABAC model to ensure that data between enterprises is absolutely inaccessible. It is important to note that this meets the requirements for identity authentication and data isolation stipulated in the Cybersecurity Law, the Data Security Law, and the Personal Information Protection Law.

[0093] Example 3

[0094] This embodiment is an improvement upon embodiment 2. For details, please refer to [link / reference]. Figure 1 The management module analyzes the user's requirements, adapts non-standard contracts by combining contextual analysis, and annotates and explains the rights and obligations of both parties on the non-standard contracts by combining historical information in the database.

[0095] The historical information in the database includes example descriptions that match the rights and obligations in the annotations;

[0096] The risk-sharing level is precisely optimized by combining the modified non-standard contracts with matching case descriptions through the central platform module, and users can confirm it.

[0097] After the contract template is finalized, the management module initiates a two-way signing process through the electronic signature platform. During the signing process, the mobile phone numbers of all parties are verified for real-name authentication. The signing timestamp, operation IP address and device information are recorded during the signing process and stored as a signing log.

[0098] The management module uploads the hash value, signing time, and signer identifier of the signed contract to the blockchain for evidence storage, obtains the blockchain evidence storage result, and generates tamper-proof electronic evidence.

[0099] The blockchain-based evidence storage results are linked to the contract documents and stored in the user's independent account space, supporting post-event verification and judicial retrieval.

[0100] Users input their employment needs on the front-end interface, and a vector database, such as Milvus, stores the semantic vectors of historical contracts and precedents. The system then uses similarity retrieval to match the most relevant instances.

[0101] The format includes natural language descriptions (such as "I need a designer to create a logo, budget of 10,000 yuan, to be completed within 3 weeks, and the copyright belongs to me").

[0102] Structured forms (job title, budget, timeframe, intellectual property requirements, etc.).

[0103] By invoking a context analysis engine for semantic parsing and using NLP models such as BERT or ChatGLM, key intents are extracted, such as:

[0104] Services offered: "LOGO design";

[0105] Delivery standard: "Original and commercially viable";

[0106] Ownership: "Copyright belongs to Party A";

[0107] Payment method: "One-time payment upon acceptance";

[0108] Identify potential legal risks: "Copyright ownership" may involve Article 17 of the Copyright Law, and the lack of advance payment may increase the risk of the second party's performance.

[0109] If a user uploads a non-standard contract, such as a self-drafted PDF agreement, the following modification logic will be executed:

[0110] Clause completion: Automatically supplements missing legally required clauses, such as liability for breach of contract and dispute resolution, with standard wording.

[0111] Standardize the wording, replacing vague language, such as "deliver as soon as possible," with specific timeframes, such as "within 21 days after the contract takes effect";

[0112] Insert risk warnings by placing warning icons and explanations next to high-risk clauses, such as "If no deposit is agreed upon, Party B may lack performance guarantees."

[0113] Rights and obligations are aligned to ensure that the rights of Party A and the obligations of Party B, and vice versa, and to avoid unilateral clauses.

[0114] The system has a built-in database of legal knowledge and cases, storing typical clauses from historically signed contracts and court precedents, such as "a design contract was ordered to pay compensation due to unclear copyright ownership," and guidelines for handling flexible employment disputes issued by arbitration institutions. It generates intelligent annotation layers on non-standard contracts, for example...

[0115] When "Copyright belongs to Party A" is detected, add the annotation: "According to the Copyright Law, the copyright of a commissioned work can be agreed upon in the contract to belong to the commissioning party. It is recommended to explicitly state 'Party B waives the right of attribution' to avoid subsequent disputes."

[0116] When "no penalty for late payment" is detected, adding a note that fails to specify liability for breach of contract may lead to difficulties in protecting one's rights. For example, in a case (Case No. [Number] in Beijing Civil Court), the court did not support the claim for interest because no agreement was made regarding liability for late payment.

[0117] It should be noted that the annotations contain embedded links to examples, which users can click to view summaries of matching cases, mediation results, or compliance recommendations. Examples are sorted by similarity and matched based on contract type, amount, and region.

[0118] The central platform module receives the modified non-standard contract and its annotations, and extracts the following risk characteristics, including risk-sharing characteristics:

[0119] The index of imbalance of rights and obligations (such as the number of unilateral exemption clauses), the clarity of intellectual property ownership, the dispute resolution method (litigation / arbitration / platform mediation), the payment guarantee mechanism (whether there are advance payments or deposits), and the completeness of liability for breach of contract.

[0120] Construct a risk scoring model, inputting the structural features of the contract and historical user behavior data (such as past dispute rates and performance rates), and output the adjusted risk level (0–100 points).

[0121] It should be noted that the model can use logistic regression, XGBoost, or a lightweight neural network.

[0122] The optimized risk level and its basis will be pushed to the user interface and the message "Current contract risk level: High risk (82 / 100)" will be displayed.

[0123] The document lists key risk points, including the lack of prepayment clauses (increasing the risk of default by the contractor), the absence of agreed acceptance standards (potentially leading to disputes), and incomplete copyright ownership statements. It also provides optimization suggestions. Users can choose to accept the suggestions and have the contract automatically modified, or manually adjust it and reassess it. If a high risk is confirmed, the contract can be signed, requiring secondary confirmation and logging.

[0124] This embodiment operates as follows:

[0125] The business owner uploaded a self-drafted design contract, while the user uploaded "LOGO Design Agreement.docx". The content was brief and did not specify acceptance standards or liability for breach of contract. The management module used NLP to analyze the requirements and identified key points such as "copyright ownership" and "one-time payment". By automatically completing the clauses and inserting a note "It is recommended to clarify the acceptance process. For reference, case: (a) Shanghai Civil Final Judgment No. X caused a dispute due to unclear acceptance standards", the central platform extracted the contract features and combined them with the company's historical performance data (there was one previous dispute). The risk level was raised from 60 to 78, and the interface prompted "It is recommended to add prepayment and acceptance clauses". After the user adopted the suggestion, the contract was updated. Finally, the contract was signed by both parties, the risk level was reduced to 52, and the normal settlement process began.

[0126] In summary, this embodiment achieves a high degree of contract intelligence, not only matching templates but also understanding context, modifying clauses, and annotating legal risks. It possesses "lawyer-like" auxiliary capabilities, reusable legal knowledge, and transforms case experience into actionable suggestions through historical databases and case illustrations. It achieves dynamic closed-loop optimization of risks and realizes for the first time an automated risk governance closed loop from contract content to risk scoring to optimization suggestions to user confirmation, improving compliance and user experience. It reduces the risk of legal disputes and enhances users' decision-making capabilities through visual prompts.

[0127] Example 4

[0128] This example is an improvement based on Example 3. Specifically, please refer to Figure 1 , the management module determines tasks, task income, identity attributes, tax payment locations, and salary payment information data based on the confirmed standard contract or non-standard contract;

[0129] The management module estimates risks and profits based on the determined tasks and example descriptions, and determines the average market profit by retrieving tasks of the same type at the current time node, generating an analysis report for the user to query.

[0130] After the contract signing is confirmed, the management module automatically extracts and structurally processes the contract key fields to form a data basis for subsequent analysis. Among them,

[0131] Task information includes task type (such as UI design, copywriting), task cycle, delivery standards, and is extracted by NLP semantic parsing and rule matching;

[0132] Task income includes total amount, payment method (one-time / installment), settlement cycle, and is extracted by regular expression matching and amount recognition model;

[0133] Identity attributes include freelancer identity (natural person / self-employed / sole proprietorship enterprise), whether to handle temporary tax registration, and are extracted by reading user files;

[0134] Tax payment locations include the place where employment occurs (province, city), whether it belongs to a tax preferential park, and are obtained by parsing contract terms and user filling;

[0135] Salary payment information includes whether there is a social security payment record from other units, whether there is an obligation for individual income tax final settlement, and is obtained by user declaration or third-party interface;

[0136] Call the risk assessment engine, combine contract terms with historical example descriptions in the database, and calculate the task execution risk index (0–100). Among them, examples of risk factors and weights:

[0137]

[0138] Retrieve similar historical contracts and dispute cases in the vector database;

[0139] Example: Match "(2024) Hu 01 Min Zhong 2345 Hao: Since the acceptance standard was not agreed upon, the court determined that Party A's refusal to pay was unfounded";

[0140] Use this case as supporting evidence for the "Performance Dispute Risk" sub-item to improve the risk score. Generate a "Task Risk Scorecard" which includes the total score, scores for each dimension, related examples, and improvement suggestions.

[0141] Furthermore, based on the task's revenue and cost structure, net income and profit margin are calculated.

[0142] Based on identity attributes and tax payment location, the system calls the declaration module's rule base to calculate the individual income tax or business income tax payable, and extracts it according to the contractually agreed percentage (e.g., 5%). To enhance its decision-making reference value, dynamic market benchmark data is introduced to achieve a horizontal comparison between "individual income" and "industry level." The search criteria for market data retrieval for similar tasks include:

[0143] Task type (e.g., "UI design");

[0144] Task duration (e.g., "2–4 weeks");

[0145] Region (e.g., "first-tier cities");

[0146] Current time point (e.g., "Q3 2025");

[0147] Data sources include the platform's historical task database, external data interfaces, and industry reports;

[0148] By collecting the above data, the average market profit is determined. The analysis results are then integrated into a task business analysis report through the management module and pushed to the user's account space, supporting online querying and export.

[0149] Furthermore, the declaration module connects to the e-Tax Bureau, the tax SaaS system, and third-party tax service platforms via API interfaces to enable automatic submission of tax declaration data;

[0150] After the declaration is completed, the declaration module automatically receives and synchronizes tax vouchers and tax records to the user's independent account space;

[0151] The declaration module uses the adapter pattern to encapsulate the interface protocols of different tax platforms, supporting parallel declarations across multiple platforms.

[0152] The declaration module automatically matches the optimal declaration path based on the location of employment and synchronizes the tax payment certificate and electronic payment receipt with one click.

[0153] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0154] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the technical principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A smart workforce billing and compliance service system for flexible workforce scenarios, characterized in that, include: The allocation module assigns an independent access domain name to each user through containerization and suggests independent account space; The management module stores standard or non-standard contract templates. Based on the user's needs, it automatically matches and retrieves the matching standard or non-standard contract template using an NLP model, thereby obtaining the signed and confirmed standard or non-standard contract and uploading it to the independent account space for storage. The calculation module determines the salary based on the signed and confirmed standard or non-standard contract, and establishes an independent settlement channel for settling the salary. The declaration module has built-in tax rules and dynamically identifies tax responsibilities and automatically declares them based on the local tax rules. The central platform module is used to collect operational data from each user for report analysis.

2. The system for smart workforce billing and compliance services for flexible workforce scenarios as claimed in claim 1 wherein, Also includes: The security module uses real-name authentication, facial recognition, and bank card four-factor authentication to adaptively select a combination of verification methods based on the risk level, thereby strengthening the uniqueness and credibility of the user's identity. The central platform module analyzes and determines the risk level based on the collected user operation data, and isolates permissions by using user identity and access control policies to ensure that operations and data cannot be accessed interchangeably. 3.The intelligent workforce settlement and compliance service system for flexible workforce scenario of claim 2, wherein: The management module analyzes the user's requirements, adaptively modifies the non-standard contract by combining contextual analysis, and annotates and parses the rights and obligations of both parties on the non-standard contract by combining historical information in the database. The historical information in the database includes example descriptions that match the rights and obligations in the annotations; The risk-sharing level is precisely optimized by combining the modified non-standard contract with matching example descriptions through the central platform module, and then confirmed by the user.

4. The system for smart workforce billing and compliance services for flexible workforce scenarios as claimed in claim 3 wherein: The management module determines the task, task income, identity attributes, tax location, and salary payment information data based on the confirmed standard or non-standard contract. The management module estimates risk and profit based on the identified tasks and instance descriptions, and determines the average market profit by searching for similar identified tasks at the current time point, generating an analysis report for users to query.

5. The system for smart workforce billing and compliance services for flexible workforce scenarios as claimed in claim 4 wherein: The declaration module dynamically identifies tax liability based on data such as the determined task, task income, identity attributes, tax location, and salary payment information. When income exceeds the tax threshold, the withholding policy is activated through the declaration module according to the region, and the individual income tax calculation, withholding declaration and tax form generation are completed automatically.

6. The intelligent employment settlement and compliance service system for flexible employment scenarios according to claim 5, characterized in that: The declaration module connects to the e-tax bureau, tax SaaS system and third-party tax service platform through API interface to realize the automatic submission of tax declaration data; After the declaration is completed, the declaration module automatically receives and synchronizes tax voucher documents and tax records to the user's independent account space; The declaration module uses an adapter pattern to encapsulate the interface protocols of different tax platforms, supporting parallel declarations across multiple platforms. The declaration module automatically matches the optimal declaration path based on the place of employment and synchronizes the tax payment certificate and electronic payment receipt with one click.

7. The intelligent employment settlement and compliance service system for flexible employment scenarios according to claim 7, characterized in that: After the contract template is determined, the management module initiates a two-way signing process through the electronic signature platform. During the signing process, the mobile phone numbers of all parties are verified for real-name authentication. The signing timestamp, operation IP address and device information are recorded during the signing process and stored as a signing log. The management module uploads the hash value, signing time, and signer identifier of the signed contract to the blockchain for evidence storage, obtains the blockchain evidence storage result, and generates tamper-proof electronic evidence. The blockchain-based evidence storage results are associated with the contract documents and stored in the user's independent account space, supporting post-event verification and judicial retrieval.

8. The intelligent employment settlement and compliance service system for flexible employment scenarios according to claim 2, characterized in that: The security module performs identity verification at each stage of task execution, contract signing, and salary payment, and cross-compares the facial images, ID card information, and bank card information collected at each stage. When the comparison results are inconsistent, a risk warning is generated and subsequent operations are suspended.

Images