Sub-contracting system of cloud sub-contracting platform and a contractor platform

Abstract

The invention is a Cloud Sub-Contracting Platform that integrates AI-driven matchmaking, escrow payment systems, expert validation, safety analytics, and AI-powered dispute resolution to resolve systemic challenges in the construction industry. In accordance with a first aspect of the invention, there is provided a cloud-based project contracting Platform comprising: a module for matching projects with contractors using artificial intelligence (AI); a contract generation module; an escrow payment system; a project tracking module; and a dispute resolution module.

Description

1 SUB-CONTRACTING SYSTEM OF CLOUD SUB-CONTRACTING PLATFORM AND A CONTRACTOR PLATFORM TECHNICAL FIELD 5 The present invention relates to a Cloud Sub-Contracting Platform, and particularly, although not exclusively, to a Cloud Sub-Contracting Platform that integrates AI-driven matchmaking, escrow payment systems, expert validation, safety analytics, and AI-powered dispute resolution to resolve systemic challenges in the construction industry. 10 BACKGROUND In various industries, including the construction industry as well as general commercial environments, the project owner and a contractor (vendor / purchaser or service provider and service user) may run into conflicts due to mismatched capabilities, disputes as to project requirements and 15 cost disputes. These conflicts may be the fault of either party or both parties. Despite these risks, project allocation and orders are often made without sufficient information or due diligence, often with resistance to change, historical reasons, past connections or pricing being the main factors. Whilst these are important aspects of the decision making process, often new 20 capabilities or project suitability may be at risk of being overlooked, resulting in a less effective engagement or purchasing process. SUMMARY OF THE INVENTION 25 The invention is a Cloud Sub-Contracting Platform that integrates AI-driven matchmaking, escrow payment systems, expert validation, safety analytics, and AI-powered dispute resolution to resolve systemic challenges in the construction industry. In accordance with a first aspect of the invention, there is provided a cloud-based project contracting 30 Platform comprising: a module for matching projects with contractors using artificial intelligence (AI); a contract generation module; an escrow payment system; a project tracking module; and a dispute resolution module. In an embodiment, the matching of projects with contractors is based on project requirements and 35 contractor profiles stored in a database. In an embodiment, the platform further comprises means for analyzing historical performance data of contractors to enhance matchmaking accuracy. 40 In an embodiment, the contract generation module automatically generates contracts incorporating payment terms managed through the escrow payment system. In an embodiment, the platform further comprises a project milestones module for tracking progress and triggering automated notifications based on predefined milestones. 45 In an embodiment, the AI analyzes project data to predict potential risks and recommend mitigation strategies. HK 20138788 A 2 In an embodiment, the dispute resolution module facilitates automated mediation by suggesting penalties or compensation for breaches. In an embodiment, the platform further comprises APIs enabling data exchange between modules 5 and external systems. In an embodiment, the platform is arranged to scale operations efficiently, supporting projects of varying sizes and complexities. 10 The Cloud Sub-Contracting Platform in some examples offers a unique advantage in the construction industry as well as any tendering, purchasing or procurement industries where parties must meet together to perform a commercial or industrial transaction. Preferably, the platform is designed to streamline the process of connecting construction or other related commerce or industry’s project managers with sub-contractors, enabling efficient contract management, payment processing, and 15 dispute resolution through the use of advanced artificial intelligence (AI) and machine learning tools. In some examples, the Platform aims to address long-standing inefficiencies in the construction sector by automating key processes, enhancing transparency, and ensuring fair outcomes for both project developers and subcontractors. 20 The construction industry and other commercial environments may have complex workflows, fragmented supply chains, and inefficiencies in managing projects and contractor relationships. Traditional methods of connecting project developers with sub-contractors may result in high administrative costs, delayed payments, poor contract management, limited oversight of project 25 progress, and unresolved disputes. These challenges can lead to delays, increased costs, and a lack of trust between parties. In this example embodiment, the Cloud Sub-Contracting Platform is arranged to address some of these issues by creating a digital ecosystem that leverages AI-driven tools to match project 30 requirements with the most suitable subcontractors, automate contract generation, manage payments securely through an escrow system, track project progress in real time, and resolve disputes efficiently. In turn, an advantage of some examples of the Platform may reduce costs, improve efficiency, enhance safety, and foster trust between all parties involved. 35 Some of the problems in which the examples of the platform may address include, without limitations: 1. Inefficient Contractor Matching: Traditional methods of identifying and engaging sub- contractors often rely on manual processes or outdated databases, leading to mismatches between project requirements and subcontractor capabilities. 40 2. Payment Delays and Disputes: Without a secure and transparent payment system or a trust system, subcontractors may face delays in receiving payments, which can lead to cash flow issues and strained relationships with project developers. Similarly, developers do not wish to overpay for work which will not be performed to the necessary standard or requirements. 3. Difficult Contract Management: Contracts are frequently lengthy, ambiguous, and difficult to 45 enforce, leading to disputes and legal complications. HK 20138788 A 3 4. Lack of Progress Tracking: Limited oversight over project milestones and progress can result in missed deadlines, quality issues, and safety risks, whilst tracking done by professionals may not be communicated or tracked efficiently. 5. Dispute Resolution Challenges: Disputes between project developers and subcontractors are often resolved slowly and ineffectively due to a lack of structured mechanisms. 5 Examples of the Platform may attempt to address the aforementioned challenges by providing a comprehensive solution that integrates AI, machine learning, and cloud-based technologies. In one example embodiment, the invention includes several modules arranged to performed project related functions. These modules include: 10 1. Sub-Contractor Matching Engine • This module is arranged to use generative AI or other forms of AI to analyze project requirements, such as scope of work, budget, timeline, and safety standards, and matches them with the most suitable subcontractors based on their expertise, availability, and past performance. 15 • Data Exchange: Project developers input detailed project specifications into the Platform. The AI engine then accesses a database of pre-verified subcontractor profiles to identify potential candidates. Subcontractors are notified via the Platform about matching opportunities. 2. Contract Generation Module • Function: Once a match is identified, this module generates customized contracts tailored to 20 the project's needs. Contracts include clear terms and conditions, pricing structures, timelines, and responsibilities for both parties. • Data Exchange: The Platform collects information from both the project developer and subcontractor to populate contract templates. This ensures that all relevant details are included, reducing ambiguity and potential disputes. 25 3. Escrow Payment System • Function: Payments between project developers and subcontractors are processed through a secure escrow system. Funds are released only when predefined milestones are met and verified by the Platform. • Data Exchange: Project developers deposit funds into the escrow account via the Platform, 30 which tracks payments and releases them to subcontractors upon verification of completed tasks. 4. Project Tracking & Safety Tools • Function: The Platform provides real-time tracking of project progress, safety metrics, and compliance with regulations. This module uses AI to monitor site activity, identify potential risks, and alert relevant parties. 35 • Data Exchange: Subcontractors submit updates on their progress through the Platform, which are verified by project developers. Safety data is collected from IoT devices and other sources to ensure compliance. 5. Dispute Resolution System • Function: In the event of a dispute, this module facilitates resolution by providing automated 40 mediation tools, legal templates, and access to neutral third-party arbitrators. • Data Exchange: Disputes are logged on the Platform, which then provides both parties with structured communication channels and resources to resolve issues. 6. Continuous Learning Module • Function: The Platform continuously improves its matching algorithms, contract templates, 45 and dispute resolution mechanisms by analyzing data from past projects, including feedback or disputes between project owners and contractors. HK 20138788 A 4 • Data Exchange: Feedback from project developers and subcontractors is collected and used to refine AI models and improve future operations. In turn, examples of the Cloud Sub-Contracting Platform may offer several advantages over traditional project management systems, including: 5 1. Cost Savings: By reducing administrative overhead, minimizing disputes, and optimizing resource allocation, the Platform lowers overall project costs. 2. Improved Safety: Real-time monitoring of safety metrics ensures compliance with regulations and reduces the risk of accidents. 3. Faster Dispute Resolution: The automated dispute resolution system reduces delays and 10 provides a structured framework for resolving conflicts. 4. Enhanced Trust: Transparent operations, secure payments, and fair contract terms foster trust between project developers and subcontractors. 5. Scalability: The Platform can be adapted to projects of varying sizes and complexity, making it suitable for both small-scale and large-scale construction efforts. 15 In some other example embodiments, the system may be arranged to be used in Applications beyond the construction industry, including in other commercial, purchasing, procurement, or professional settings, including, but not limited to • Manufacturing 20 • Education • Entertainment • IT and technology • Logistics and supply chain management • Science and Research 25 • Healthcare The Platform's modular design allows it to be customized for different industries, further expanding its utility in these other areas. BRIEF DESCRIPTION OF THE DRAWINGS 30 Embodiments of the present invention will now be described, by way of example, with reference to the accompanying drawings in which: Figure 1 is a block diagram of a cloud sub-contracting platform in accordance with one embodiment 35 of the present invention. DESCRIPTION OF THE PREFERRED EMBODIMENTS With reference to Figure 1, there is shown an example embodiment of a cloud-based project 40 contracting Platform comprising: a module for matching projects with contractors using artificial intelligence (AI); a contract generation module; an escrow payment system; a project tracking module; and a dispute resolution module. In some embodiments, the matching of projects with contractors is based on project requirements and contractor profiles stored in a database. In another embodiment, the platform further comprises means for analyzing historical performance data of 45 contractors to enhance matchmaking accuracy. HK 20138788 A 5 In this example embodiment, the platform may be arranged to operate for connecting construction project managers with sub-contractors in the construction industry, although this can work with various other supplier, vendor, purchasing, engaging or tendering industries. In some examples, the platform may allow these contracts to be better managed between the project owner and the project contractor. The platforms may attempt to manage these contracts by use of AI systems to 5 process project requirements and contractor profiles, and to find a better match between them as based on the profile information. Additionally, the platform may also include project tracking to see that the projects are following milestones, an escrow payment system so that payments may be made at an appropriate time. Also, the platform may also include a dispute resolution process to process legal contracts so that contracts can be executed and if there is a dispute, be called upon for 10 AI processing, in the hope that the dispute can be resolved. Accordingly, an example use of the platform may be within a construction company wishes to build a swimming pool, the company may engage an expert landscaper to dig a hole, further by engaging a pool builder. The company may use the platform to find a suitable landscaper with the right profile or 15 tools. Then the platform may use AI to better match the company with the landscaper, then formulate the contracts with AI, and then track the progress of the project by use of sensors or drone data (images etc). Payments at appropriate milestones may also be made and transferred to the landscaper and finally, if there are any disputes, these will be processed with AI in an attempt to resolve any dispute. 20 In some example embodiments of the platform, the platform includes the following modules or functions. These include, without limitations: 1.1.1 AI-Powered Precision Matchmaking: 25 - In some example embodiments, the platform uses AI to analyze project specifications, stakeholder performance / safety records, financial health, and workflow breakdowns to match subcontractors / suppliers with developers. The platform may also use a new method, involving Machine learning algorithms process multi-dimensional data (e.g., historical project success rates, dispute history) to recommend optimal matches, reducing mismatches and delays. This may be 30 advantageous when compared with current systems (e.g., BuildZoom, Procore) which offers none of these features. 1.1.2. Escrow-Managed Financial Ecosystem: - In some example embodiments, partner banks provide secured escrow payments and transaction 35 guarantees, addressing trust deficits in traditional subcontracting. New Step: Payments are released only upon AI-validated milestone completions, eliminating payment disputes and bankruptcies. 1.1.3. Integrated Expertise Validation: - In some example embodiments, contracts are standardized by Quantity Surveying (QS) experts, 40 and AI-generated recommendations are validated by professionals. Innovation: Combines AI automation with human oversight for dispute resolution and contract administration. In this example, the platforms include an AI Analysis Precision Matchmaking system, which forms an important component of the Cloud Sub-Contracting Platform. It is designed to address inefficiencies 45 in traditional subcontractor selection. The system leverages artificial intelligence to analyze multi- dimensional datasets, including project specifications (e.g., scope, budget, technical requirements), subcontractor profiles (e.g., historical performance, safety compliance records, financial stability), HK 20138788 A 6 and industry benchmarks (e.g., regional cost averages, regulatory standards) and in turn allow these factors to be more carefully and fairly considered in when comparing and awarding tasks to contractors and sub-contractors or other related parties. The AI employs machine learning algorithms trained on historical project data to identify patterns 5 that correlate subcontractor capabilities with project success. For example, neural networks evaluate compatibility between a subcontractor’s expertise in high-rise construction and a developer’s project requirements for a skyscraper. Natural Language Processing (NLP) further parses unstructured data, such as project descriptions or dispute logs, to identify risk factors (e.g., delays, cost overruns). Different types of AI tools may be used, including Large Language Models (LLMs) 10 with RAGs to process the different information and to formulate an assessment, score or pattern. A Multi-Criteria Decision Analysis (MCDA) framework may also be included to dynamically assess or weigh, or assign weights to factors like cost efficiency, reliability, and safety compliance to generate a ranked shortlist of subcontractors. This process eliminates biases inherent in manual selection and 15 ensures alignment with project-specific needs. The AI’s recommendations are validated by Quantity Surveying (QS) experts to ensure technical feasibility, creating a hybrid model that combines automation with human oversight. 1.1.4. Safety Analytics & Cost Transparency: 20 - AI monitors site safety risks and allocates budgets directly to on-site activities, reducing subcontracting layers and improving oversight. - Outcome: Fewer accidents and cost inflation due to real-time financial / safety data tracking. 1.1.5. Advanced AI-Driven Dispute Resolution System: 25 - AI Judge / Adjudicator: A proprietary algorithm analyzes contractual terms, project progress data, communication logs, and historical dispute patterns to generate impartial resolutions. - New Method: - Natural Language Processing (NLP) interprets contract clauses and identifies breaches. - Predictive analytics assesses liability and proposes settlements based on industry precedents. 30 - Stakeholders receive AI-generated resolution drafts within hours, bypassing months-long litigation. - Human-AI Synergy: Dispute outcomes are reviewed by legal / QS experts for fairness, ensuring compliance with regulations while retaining efficiency. - Outcome: Reduces dispute resolution costs by 60–70% and time by 80%, fostering trust and 35 collaboration. 1.2 Advantages over Current Systems: - Competitors (e.g., BuildZoom, Procore) focus narrowly on project management or lack integrated financial / trust mechanisms. 40 - / / Escrow.com / Briq offer standalone financial tools but fail to unify workflows or automate dispute resolution. - Examples of the current platform uniquely combines AI, financial security, expert validation, and AI adjudication into an end-to-end ecosystem, eliminating intermediaries and fostering transparency. 45 1.3 Operational Flow: HK 20138788 A 7 In one example, the platform is arranged to operate via the follow processes and would integrate AI- driven automation, financial security, and expert collaboration into a seamless workflow process. These processes include: 1. Project Submission: Developers submit project specifications (e.g., blueprints, budgets) to the 5 platform. AI implemented modules, including any machine learning systems, may be arranged to parses this data to identify critical requirements. 2. AI-Driven Matchmaking: Neural networks analyze subcontractor profiles and project needs to generate a ranked shortlist of suitable subcontractors, see for example in paragraphs 1.1.1 above. 10 3. AI assisted Contract Validation by Experts: AI drafts standardized contracts using templates pre- validated by QS and legal experts. Stakeholders negotiate terms via an AI-assisted interface. These terms may be used to generate a contract which can be considered by all parties and if agreed, the contracts may be digitally signed and stored for execution, performance or dispute consideration or 15 resolution. 4. AI assisted Escrow Payment Execution : Partner banks establish escrow accounts, with funds released upon AI-verified milestone completions (e.g., structural work validated via IoT sensors). 20 5. Execution Monitoring (AI assisted Project and Site Management): - Real-Time Progress Tracking: IoT devices (e.g., sensors, drones) and subcontractor updates feed data into the AI, monitoring milestones (e.g., foundation completion) and resource allocation. - Safety Compliance: Computer vision analyzes site camera feeds to detect hazards (e.g., unsafe scaffolding), triggering instant alerts. 25 - Predictive Risk Management: Machine learning models pre-empt delays by analyzing variables like weather patterns or supply chain disruptions, recommending mitigations (e.g., resequencing tasks). These tracking processes of the project progress can in turn be used for project management, payment or dispute resolution. Results of the tracking progress may also be used to update the profiles of the subcontractors or other stakeholders which in turn may affect their subsequent 30 performance rating and future suitability of being suggested for new projects. 6. AI assisted Dispute Resolution System: The AI adjudicator analyzes contractual terms, project logs, and stakeholder claims to propose resolutions. Legal / QS experts review outcomes for compliance. 35 With reference to Figure 1, the user of the platform may experience the following processes: 1.3.1. Developer submits project specs to the platform. 1.3.2. AI analyzes data (stakeholder records, cost breakdowns) to recommend subcontractors. 1.3.3. Contracts are standardized and validated by QS experts. 1.3.4. Escrow accounts are activated, with payments tied to AI-verified milestones. 40 1.3.5. Dispute Resolution: - AI adjudicator flags potential conflicts during project execution. - If disputes arise, NLP scans contracts, project logs, and stakeholder claims. - AI proposes resolutions (e.g., compensation adjustments, timeline revisions) within hours. - Experts review and finalize outcomes, ensuring legal compliance. 45 1.3.6. Safety analytics tools monitor progress and flag risks in real time. 1.3.7. Continuous learning improves AI accuracy with each project. HK 20138788 A 8 1.4 Advantages of the system may offer superior or more positive outcomes for all stakeholders as projects suitability, costs may be better managed. Progress, management and dispute resolution may also be suitable tracked and processed, when necessary, by examples of the platform. Some example benefits of the platform may include in some examples: - Reduced construction costs (20–30% savings via fewer subcontracting layers). 5 - 50% fewer payment disputes and accidents. - 60–70% faster, cheaper dispute resolutions compared to traditional litigation. - Increased trust and participation in the industry, promoting sustainable growth. HK 20138788 A Field of claim The invention is a Cloud Sub-Contracting Platform that integrates AI-driven matchmaking, escrow payment systems, expert validation, safety analytics, and AI-powered dispute resolution to resolve systemic challenges in the construction industry. In accordance with a first aspect of the invention, there is provided a cloud-based project contracting Platform comprising: a module for matching projects with contractors using artificial intelligence (AI); a contract generation module; an escrow payment system; a project tracking module; and a dispute resolution module. In an embodiment, the matching of projects with contractors is based on project requirements and contractor profiles stored in a database. In an embodiment, the platform further comprises means for analyzing historical performance data of contractors to enhance matchmaking accuracy. In an embodiment, the contract generation module automatically generates contracts incorporating payment terms managed through the escrow payment system. In an embodiment, the platform further comprises a project milestones module for tracking progress and triggering automated notifications based on predefined milestones. In an embodiment, the AI analyzes project data to predict potential risks and recommend mitigation strategies. In an embodiment, the dispute resolution module facilitates automated mediation by suggesting penalties or compensation for breaches. In an embodiment, the platform further comprises APIs enabling data exchange between modules and external systems. In an embodiment, the platform is arranged to scale operations efficiently, supporting projects of varying sizes and complexities. The Cloud Sub-Contracting Platform in some examples offers a unique advantage in the construction industry as well as any tendering, purchasing or procurement industries where parties must meet together to perform a commercial or industrial transaction. Preferably, the platform is designed to streamline the process of connecting construction or other related commerce or industry’s project managers with sub-contractors, enabling efficient contract management, payment processing, and dispute resolution through the use of advanced artificial intelligence (AI) and machine learning tools. In some examples, the Platform aims to address long-standing inefficiencies in the construction sector by automating key processes, enhancing transparency, and ensuring fair outcomes for both project developers and subcontractors. The construction industry and other commercial environments may have complex workflows, fragmented supply chains, and inefficiencies in managing projects and contractor relationships. Traditional methods of connecting project developers with sub-contractors may result in high administrative costs, delayed payments, poor contract management, limited oversight of project progress, and unresolved disputes. These challenges can lead to delays, increased costs, and a lack of trust between parties. 9 HK 20138788 A In this example embodiment, the Cloud Sub-Contracting Platform is arranged to address some of these issues by creating a digital ecosystem that leverages AI-driven tools to match project requirements with the most suitable subcontractors, automate contract generation, manage payments securely through an escrow system, track project progress in real time, and resolve disputes efficiently. In turn, an advantage of some examples of the Platform may reduce costs, improve efficiency, enhance safety, and foster trust between all parties involved. Some of the problems in which the examples of the platform may address include, without limitations: 1. Inefficient Contractor Matching: Traditional methods of identifying and engaging sub- contractors often rely on manual processes or outdated databases, leading to mismatches between project requirements and subcontractor capabilities. 2. Payment Delays and Disputes: Without a secure and transparent payment system or a trust system, subcontractors may face delays in receiving payments, which can lead to cash flow issues and strained relationships with project developers. Similarly, developers do not wish to overpay for work which will not be performed to the necessary standard or requirements. 3. Difficult Contract Management: Contracts are frequently lengthy, ambiguous, and difficult to enforce, leading to disputes and legal complications. 4. Lack of Progress Tracking: Limited oversight over project milestones and progress can result in missed deadlines, quality issues, and safety risks, whilst tracking done by professionals may not be communicated or tracked efficiently. 5. Dispute Resolution Challenges: Disputes between project developers and subcontractors are often resolved slowly and ineffectively due to a lack of structured mechanisms. Examples of the Platform may attempt to address the aforementioned challenges by providing a comprehensive solution that integrates AI, machine learning, and cloud-based technologies. In one example embodiment, the invention includes several modules arranged to performed project related functions. These modules include: 1. Sub-Contractor Matching Engine • This module is arranged to use generative AI or other forms of AI to analyze project requirements, such as scope of work, budget, timeline, and safety standards, and matches them with the most suitable subcontractors based on their expertise, availability, and past performance. • Data Exchange: Project developers input detailed project specifications into the Platform. The AI engine then accesses a database of pre-verified subcontractor profiles to identify potential candidates. Subcontractors are notified via the Platform about matching opportunities. 2. Contract Generation Module • Function: Once a match is identified, this module generates customized contracts tailored to the project's needs. Contracts include clear terms and conditions, pricing structures, timelines, and responsibilities for both parties. • Data Exchange: The Platform collects information from both the project developer and subcontractor to populate contract templates. This ensures that all relevant details are included, reducing ambiguity and potential disputes. 3. Escrow Payment System • Function: Payments between project developers and subcontractors are processed through a secure escrow system. Funds are released only when predefined milestones are met and verified by the Platform. • Data Exchange: Project developers deposit funds into the escrow account via the Platform, which tracks payments and releases them to subcontractors upon verification of completed tasks. 10 HK 20138788 A 4. Project Tracking & Safety Tools • Function: The Platform provides real-time tracking of project progress, safety metrics, and compliance with regulations. This module uses AI to monitor site activity, identify potential risks, and alert relevant parties. • Data Exchange: Subcontractors submit updates on their progress through the Platform, which are verified by project developers. Safety data is collected from IoT devices and other sources to ensure compliance. 5. Dispute Resolution System • Function: In the event of a dispute, this module facilitates resolution by providing automated mediation tools, legal templates, and access to neutral third-party arbitrators. • Data Exchange: Disputes are logged on the Platform, which then provides both parties with structured communication channels and resources to resolve issues. 6. Continuous Learning Module • Function: The Platform continuously improves its matching algorithms, contract templates, and dispute resolution mechanisms by analyzing data from past projects, including feedback or disputes between project owners and contractors. • Data Exchange: Feedback from project developers and subcontractors is collected and used to refine AI models and improve future operations. 11 HK 20138788 A Claims 1. A cloud-based project contracting Platform comprising a module for matching projects with contractors using artificial intelligence (AI); a contract generation module; an escrow payment system; a project tracking module; and a dispute resolution module; 2. A cloud-based project contracting Platform of claim 1, wherein the matching of projects with contractors is based on project requirements and contractor profiles stored in a database; 3. A cloud-based project contracting Platform of claims 1 and 2, further comprising means for analyzing historical performance data of contractors to enhance matchmaking accuracy; 4. A cloud-based project contracting Platform of claims 1 to 3, wherein the contract generation module automatically generates contracts incorporating payment terms managed through the escrow payment system; 5. A cloud-based project contracting Platform of claims 1 to 4, further comprising a project milestones module for tracking progress and triggering automated notifications based on predefined milestones; 6. A cloud-based project contracting Platform of claims 1 and 5, wherein the AI analyzes project data to predict potential risks and recommend mitigation strategies; 7. A cloud-based project contracting Platform of claims 1 to 6, wherein the dispute resolution module facilitates automated mediation by suggesting penalties or compensation for breaches; 8. A cloud-based project contracting Platform of claims 1 to 7, further comprises APIs enabling data exchange between modules and external systems; and 9. A cloud-based project contracting Platform of claims 1 to 8, wherein the platform is arranged to scale operations efficiently, supporting projects of varying sizes and complexities. 1 HK 20138788 A • Completed Projects • Refined AI Models • Risk Management Reports AI-driven stakeholder matching Figure 1 Project monitoring – use of AI for project & site management AI Assisted Dispute Resolution • Project Specifications • Stakeholder Data AI assisted contract validation by experts AI assisted escrow payment execution 1 HK 20138788 A

Images