PROPOSAL: Ministry of Interior, Saudi Arabia Multi-Modal AI-Powered VISION-based Park Surveillance & Autonomous Patrol System

REAL-TIME VIDEO Analytics with Autonomous Patrol System. Powered by POLYTRON.AII
This Agreement is between __________________________________________________________________, a company incorporated in _____________________________________________________________ having its registered office ________________________________________________________________________________________ (the “CUSTOMER”), and VIZZIO TECHNOLOGIES PTE LTD, a company incorporated in Singapore having its registered office at 55 UBI AVENUE 3, ASPIAL ONE, LEVEL 3, SINGAPORE 408868 (the “SERVICE PROVIDER”).
This Agreement sets out the proposal whereby the CUSTOMER will engage the SERVICE PROVIDER to perform the Services (“SERVICES”) required for the project, details of which are contained in this Agreement (“PROJECT”) and on the terms and conditions hereunder.
The proposal in this Agreement is intended only for the CUSTOMER and may contain confidential and/or privileged material. Any review, dissemination or other use of, or taking of any action in reliance upon, this information by persons or entities other than the intended recipient is prohibited.
This Agreement when executed by or on behalf of the CUSTOMER and the SERVICE PROVIDER respectively will constitute a legal and valid contract binding upon both parties.


The Ministry of Interior (MoI; Arabic: وزارة الداخلية) is one of the governmental bodies of Saudi Arabia responsible for national security, naturalisation, immigration, and customs in Saudi Arabia and is a vital institution that plays a central role in maintaining the Kingdom's internal security and public order through its comprehensive and multifaceted functions.
This project is a testbed to create an AI-Powered Autonomous Visual Pollution Detection, Surveillance and Patrol System for managing, monitoring and maintenance of parks in the Kingdom.
As urban areas continue to expand, the importance of maintaining clean and safe public parks becomes increasingly critical. Public parks not only enhance the aesthetic appeal of cities but also contribute significantly to the well-being and health of residents. To effectively manage and maintain the cleanliness of parks, we propose the implementation of an AI-Powered VISION-based Park Surveillance & Autonomous Patrol System. This advanced system leverages cutting-edge technology, multi-modal AI training, tracking and detection to ensure parks are kept clean, safe and free of garbage, providing a pleasant and hygienic environment for all visitors.
The primary objectives of the AI-Powered Autonomous Visual Pollution Detection, Surveillance, and Patrol System are to:
Ensure Cleanliness: Maintain high standards of cleanliness in public parks through continuous monitoring and immediate detection of litter and waste.
Enhance Efficiency: Enhance the efficiency of park maintenance operations by automating the detection and reporting of pollution and safety incidents. Our advanced system leverages cutting-edge AI technology to continuously monitor the park environment, identifying and categorizing various types of pollution and safety hazards in real-time.
Promote Sustainability: Support sustainable park management practices by minimising the need for manual inspections and interventions.
Improve Public Health and Safety: Reduce health hazards and enhance the safety and enjoyment of park visitors by promptly addressing cleanliness and safety issues.
Continuous Self-Learning AI
By feeding this historical data into machine learning models, the AI can learn from past incidents. The system can identify subtle patterns and correlations that may not be immediately apparent, enhancing its ability to predict and detect future incidents with greater accuracy.


The proposed architecture comprises of the following components.

AI SOFTWARE Agent for Continuous Surveillance, Monitoring & Tracking

Equipped with advanced 3D digital reality scenes captured using our state-of-the-art AI 3D modeling software, we have developed a virtual, software-based autonomous AI agent (BOT) designed to "patrol" parks. This innovative system continuously captures real-time images and videos of the surroundings, performing sophisticated analytics and detection tasks. It monitors for anomalies and promptly triggers alerts and notifications whenever unusual or unauthorised activities are detected. This comprehensive solution ensures enhanced surveillance, safety, and efficient management of park environments.
Utilize advanced 3D navigation systems to cover extensive areas efficiently, the vision-based AI AGENT is capable of avoiding obstacles and adhering to pre-defined patrol routes.

Autonomous AI-Powered Virtual Patrol System

One of the unique value proposition we present in our solution is a software-based, AI-Powered Autonomous Virtual Patrol System.
Powered by next-gen, multi-modal, multi-faceted foundation models, we’re bringing you Video Intelligence that has a holistic understanding of your space, built directly into POLYTRON ONE AI-Powered Virtual Patrol platform.
Traditional computer vision techniques used in CCTV based solution primarily rely on analysing visual data (images/videos) using pre-trained models, often focusing on isolated visual cues. They also rely heavily on predefined rules and lotsa trained data sets, leading to a higher rate of false positives. Conventional Video Analytics also often requires manual updating of rules and trained models due to reliance on static computer-vision based training data.
In contrast, the Autonomous VIRTUAL PATROL Guard is equipped with advanced MULTI-MODAL AI capable of segmenting text, audio, images, and videos to gain deeper insights and understanding of the environment as it navigates the factory floor. It functions similarly to a human patrolling the area while performing their duties.
The AI Virtual Patrol Guard operates through an automated software-based agent or bot that navigates the virtual environment, mimicking the actions of a physical patrol on the factory floor. This agent observes and analyses the surroundings, leveraging advanced computer vision and data analytics to identify anomalies and instances of non-compliance. By "walking the ground" virtually, it continuously monitors the environment, promptly triggering alerts whenever it detects irregularities or deviations from compliance standards.
In the above video demonstration, there is no need for manual clicks or human intervention. Every movement you observe in the video is not controlled by a human operator using a mouse. The patrolling and navigation are managed by an AI route-navigation engine that traverses the space autonomously, simulating the actions a human would take during a ground patrol.
This innovative solution transforms the concept of surveillance by offering a fully autonomous, AI-driven 3D virtual tour. Without requiring any human intervention or mouse clicks, the AI system autonomously patrols the 3D virtual space, continuously scanning for any discrepancies or safety hazards. Leveraging advanced POLYTRON LIVE 3D cameras, the system seamlessly integrates video streams into a spatial 3D geometry. Each camera acts as an observant eye, constantly sending video streams to our 3D scene to monitor the environment. The backend's powerful real-time video analysis capabilities ensure that any anomalies, such as falls, fire & smoke, or compliance breaches like missing protective gear, are immediately detected and reported. Alerts are then communicated to command and control centers.
This AI-powered LIVE 3D Virtual Patrol System, combining LIVE video and 3D scene integration, can be configured to conduct surveillance and security duties at specific, pre-set intervals.
What sets this system apart is its use of a zero-shot generalisation engine, enabling the AI to recognise and react to even unfamiliar objects, poses and situations, enhancing the scope and reliability of the AI patrol & surveillance.
The tasks performed by the AI Virtual Patrol Bot is as follows:
Continuous Monitoring: Unlike human security personnel who require breaks and shifts, an autonomous software agent can operate around the clock without fatigue. This continuous monitoring ensures that virtual environments, such as production equipments and assets, are under constant surveillance, reducing the window of opportunity for failure & security breaches.
Scalability: Software agents can be deployed at scale across multiple virtual environments (parks) simultaneously, across the entire Kingdom. It's a software solution, no deployment of humans. This scalability allows Foxconn to enhance their security measures without the need to hire additional personnel, making it a cost-effective solution for expanding surveillance coverage.
Real-Time Threat Detection: These agents can detect anomalies and potential threats in real time. Using machine learning and pattern recognition, they can identify unusual activities that may signify a security breach, such as un-authorised access attempts or suspicious data transfers. Immediate detection allows for quicker responses, potentially mitigating damages.
Automated Response: Beyond simple monitoring and detection, our AI Virtual Patrol have the capability to automatically respond to security and safety compliance breaches. For instance, they can isolate affected areas, send notifications, revoke access privileges, or initiate backup protocols without human intervention, thus speeding up response times and minimising human error.
Data Analysis and Forensics: Autonomous software agents can also collect and analyze data on security incidents, providing insights that can be used to strengthen future security measures. This continuous learning process allows them to adapt to new threats and improve their detection algorithms over time.
Cost Efficiency: By automating routine surveillance tasks via AI VIRTUAL PATROL GUARD, FII can reduce the manpower required for security duties, thereby decreasing operational costs. Additionally, the reduction in security breaches can lead to significant savings in potential losses and recovery costs.
Integration with Physical Security: In a complex and hybrid outdoor environments such as parks where physical and virtual security are both critical, autonomous agents can integrate with physical security systems (IOTs, Sensors, Conventional CCTV, POLYTRON Camera etc) to provide a comprehensive security overview. For example, a breach in virtual security could trigger physical alerts, ensuring a coordinated response across both domains.
These AUTONOMOUS AI AGENTS (Virtual Patrol) signify a shift from reactive to proactive security measures. By harnessing advanced technologies like AI and machine learning, they not only enhance the effectiveness of security operations but also adapt to increasingly complex environments, such as factory floors, while addressing the growing importance of AI. This evolution is crucial as businesses and institutions rely more on digital infrastructures and as the nature and scope of threats continue to evolve.
The AI Virtual Patrol is also available on mobile and tablet devices, acting as a companion app, enabling security personnel to carry out inspections and compliance checks using just their mobile phones.

AI-Powered Vision-based Analytics & Detection System

Incorporates state-of-the-art AI algorithms capable of detecting various types of waste and litter, including plastics, paper, food wrappers, and organic waste. We will create machine learning models trained on extensive datasets of images and videos that depict littering and safety hazard behaviours. This training will enable the AI to recognise actions associated with waste disposal and safety concerns. Additionally, we will implement pose-estimation algorithms to detect specific movements and objects related to littering, potential hazards, and other safety risks. Detailed analysis covered in this scope of work includes the following:
Demographics Detection (Male/Female)
Face Detection
Throw Garbage Analytics and Detection
Crowd & Over-Crowding Detection
Dwell time & Heat maps Generation
People Loitering in an area
People being stationary in an area
Detection of Left Objects
Detection of Abandoned Objects
Vehicle Overstay in parking lots/ areas
Identifying violations at the parking site
Detection of Parking Utilisation Areas
Fire Detection
Smoke Detection
The ability to detect fire in greenery areas and urban areas
Detect flames coming out from vehicles/waste containers and closed areas like warehouses
Aggression Detection
People/Object Counting
Cameras tampering detection
The system employs a network of high-resolution cameras and sensors strategically placed throughout the park. These devices capture real-time data, which is then processed by AI algorithms capable of detecting litter, waste, graffiti, hazardous materials, and potential safety hazards such as broken equipment or obstructed pathways.
Machine learning models trained to recognise and differentiate between types of garbage, ensuring accurate detection and classification.
Upon identifying a pollution or safety incident, the system immediately generates detailed reports, including the type, location, and severity of the issue. This information is automatically sent to the park maintenance team, enabling a swift and targeted response.
By automating the detection and reporting process, the system reduces the need for manual inspections, allowing maintenance staff to focus their efforts on addressing identified issues. This leads to more efficient use of resources and ensures that maintenance tasks are prioritized based on real-time data.
Continuous monitoring and rapid reporting help maintain a high standard of cleanliness and safety within the park. Prompt attention to pollution and safety hazards prevents minor issues from escalating into major problems, enhancing the overall visitor experience.
The system collects and analyses data over time, providing valuable insights into patterns and trends related to pollution and safety incidents. This information can be used to optimize maintenance schedules, allocate resources more effectively, and implement preventive measures.
The AI-powered solution is scalable and can be adapted to parks of various sizes and configurations. It can be easily integrated with existing park management systems, ensuring a seamless enhancement of current operations.
By maintaining a cleaner and safer park environment, the system contributes to environmental sustainability and public health. Additionally, the efficiency gains and resource optimization result in cost savings for park management.

Automated Reporting, Notification System & Continuous Self-Learning AI

The system meticulously logs each incident of pollution and safety hazards detected, along with the associated alerts and notifications. This includes detailed information such as the type of issue, exact location, time of occurrence, and response actions taken.
The system archives all alerts and notifications, creating a comprehensive database of past incidents. This historical data serves as a valuable resource for training the AI, enabling it to become smarter and more effective over time.
Integrates with existing maintenance workflows to dispatch cleaning crews and safety officers promptly to the identified areas.
The archived data provides a transparent record of all incidents and responses. This can be useful for reporting to stakeholders, ensuring accountability, and demonstrating the effectiveness of the park management’s efforts. This archived data can also be analysed to identify patterns and recurring issues. For example, the system might detect that certain areas of the park are more prone to littering at specific times or that particular types of waste are more common during certain seasons.
The system archives all alerts and notifications, creating a comprehensive database of past incidents. This historical data serves as a valuable resource for training the AI, enabling it to become smarter and more effective over time. As the system continues to operate and gather more data, it continuously refines its algorithms. This adaptive learning process means that the AI gets progressively better at identifying and responding to issues, making the system more reliable and efficient over time.
Historical data supports informed decision-making by providing a factual basis for evaluating the success of past interventions and planning future actions. This ensures that decisions are data-driven rather than based on assumptions. The historical data allows park management to assess the effectiveness of various maintenance strategies. For instance, they can compare the frequency and severity of incidents before and after implementing new cleaning schedules or installing additional waste bins.
The AI can use historical data to predict potential future incidents before they occur. For example, if a certain type of safety hazard has historically occurred under specific conditions, the AI can alert the maintenance team to take preemptive measures.
Insights gained from historical data help in optimising resource allocation. If the data shows that certain areas are consistently problematic, more resources can be directed there. Conversely, areas with fewer issues might require less frequent monitoring.

Centralised Monitoring and Control System

We propose the implementation of a centralised unified dashboard specifically designed for the Ministry of Interior (MOI) and park authorities. This advanced REAL-TIME IMMERSIVE & INTERACTIVE 3D Digital Twin dashboard will facilitate comprehensive real-time monitoring and management of parks, integrating data from various sources (CCTV, Sensors) to provide a cohesive and efficient surveillance system.
Park authorities and MOI officials will have a unified platform to oversee park operations. The dashboard will display live feeds, environmental metrics, and incident reports, providing a holistic view of the park’s status at any given moment.
The system will generate customisable alerts and notifications for various incidents such as pollution detection, safety hazards, and unauthorised activities. These alerts will be displayed on the dashboard and sent to relevant personnel via email, SMS, or push notifications.
The dashboard will offer detailed analytics and reporting features, allowing authorities to track trends, identify recurring issues, and evaluate the effectiveness of maintenance and security measures. Historical data can be reviewed to improve decision-making and resource allocation.
The centralised system will facilitate better communication and collaboration between MOI and park authorities. Shared access to real-time data and alerts ensures that all parties are informed and can coordinate their responses effectively.
The dashboard will be scalable to accommodate the monitoring needs of multiple parks and adaptable to various operational requirements. It can be expanded to include additional data sources and enhanced functionalities as needed.
By centralising monitoring and alert management, the dashboard reduces the time and effort required to oversee park operations, allowing authorities to respond more quickly to incidents.
Real-time alerts and comprehensive data analysis enable proactive management of safety hazards and pollution, ensuring that parks remain safe and clean for visitors.
Access to detailed analytics and historical data supports data-driven decision-making, helping authorities optimize resource allocation and improve overall park management strategies.
The centralised dashboard provides a clear and transparent view of park operations, facilitating accountability and enabling stakeholders to track the effectiveness of management efforts.
In summary, automating the patrolling, surveillance, detection and reporting of pollution and safety incidents significantly improves the efficiency of park maintenance operations. This advanced system not only ensures a cleaner and safer environment but also enhances resource management, operational efficiency, and long-term sustainability. This proactive approach ensures that issues are quickly identified and resolved, maintaining a safe, clean, and pleasant environment for park visitors.


Machine learning (ML) and deep learning (DL) are powerful tools for deploying solutions to detect and analyze littering behavior using video analytics. Here's a step-by-step guide on how these technologies can be used to develop and deploy a "Throw Garbage Analytics and Detection" system:

1. Data Collection & Preparation

Step 1: Collect Data

Video Footage: Gather video footage from CCTV cameras from Parks where littering and safety hazards might occur.
Annotated Data: Annotate the video footage with labels indicating instances of littering. This involves marking frames where garbage is thrown or where litter appears.

Step 2: Preprocess Data

Frame Extraction: Extract frames from the video footage to create a dataset of images.
Normalisation: Normalize the images to a standard size and format.
Data Augmentation: Apply data augmentation techniques such as rotation, scaling, and flipping to increase the variability of the training dataset.

2. Model Training

Step 3: Choose the Model Architecture

Object Detection Models: Employ a object detection model such as YOLO, SSD (Single Shot MultiBox Detector), and/or Faster R-CNN (Region-based Convolutional Neural Networks) for detecting objects in images.
Behavior Recognition Models: For recognising actions (e.g., throwing garbage), we will employ models like RNNs (Recurrent Neural Networks) or 3D Convolutional Neural Networks.

Step 4: Train the Model

Supervised Learning: Use the annotated dataset to train the model. The training process involves feeding the images into the model and adjusting the model parameters to minimize the prediction error.
Loss Function and Optimisation: An appropriate loss function (e.g., cross-entropy loss for classification) will be chosen and an optimisation algorithm (e.g., Adam or SGD) deployed to train the model.

3. Model Validation and Testing

Step 5: Validate the Model
Validation Set: Use a separate validation dataset to tune the model parameters and prevent overfitting.
Performance Metrics: Evaluate the model using metrics such as precision, recall, F1-score, and accuracy.
Step 6: Test the Model
Test Dataset: Use a test dataset to assess the model's performance in real-world scenarios.
Real-Time Testing: Deploy the model on live video streams to test its effectiveness in real-time detection.

4. Deployment

Step 7: Integration with CCTV System
The deployment will be a hybrid solution leveraging on EDGE, Cloud and On-Premise installation of the analytics. For Edge Computing, we will implement the model on edge devices (e.g., NVIDIA Jetson, Google Coral) for real-time processing at the camera location.
Step 8: Real-Time Analytics
Detection Pipeline: Set up a pipeline to process live video feeds, detect littering and safety incidents, and generate alerts.
Alert System: Integrate with centralised, multi-channel (SMS, Email, Browser, Audio) alert system to send notifications to relevant authorities when littering or safety risks are detected.

5. Continuous Improvement

Step 9: Feedback Loop
Incident Logging: Log detected incidents and their outcomes to create a feedback loop.
Model Retraining: Periodically retrain the model with new data to improve its accuracy and adapt to new behaviours.

6. Hardware

POLYTRON ONE SERVER Specification as follows:

Unit Price (US$)
Unified Video Management Server to aggregate video feeds from CCTV for recording, archival, analytics and near-real-time “AI-Model Training”
US$ 75,000 for integrating any number of video feeds into POLYTRON ONE VMS from MOI existing cameras
US$ 75,000
License Fee to sign for 3 years. Renewable every year.
POLYTRON ONE SERVER (Industrial Grade)
US$ 25,000
Maintenance Fee for Server at 15% annual = US$ 16,500 starting 2nd year. Contract to sign for 3 years. First year exempted.
POLYTRON SENTRY SERVER (Multi-Channel REAL-TiME Push Notification System)
US$ 5,000
Maintenance Fee for Server at 15% annual = US$ 4,500 starting 2nd year. Contract to sign for 3 years. First year exempted.
AI Model Training & Deployment
Free for Proof of Concept Work.
Continuous Model re-training and update @ 15% annual US$ 24,750 starting 2n year. Contract to sign for 3 years. First year exempted.
Unified Dashboard Application Development and feeds/data integration
Free for Proof of Concept Work.
Development of a RBAC unified dashboard to manage the video streams, integrating a multi-channel alerts and notification system, and incorporating reporting and archival database.
LUNA Visualisation Server
Free for Proof of Concept Work.
One-time setup and installation fee. To connect all analytics data and cctv video feeds data to dashboard.
US$ 105,000
Total Pricing for 3 years.
There are no rows in this table
NOTE: Deployment of engineering resources on site for development is not included in the above pricing table. This should b


The CUSTOMER shall pay the SERVICE PROVIDER the total contract sum of US$ 105,000 in the following instalments:
40% on the execution by the CUSTOMER and the SERVICE PROVIDER of this Agreement;
40% during the development phase upon completion of trained AI models and deployment of Multi-Channel Push Notification Server - POLYTRON SENTRY.
10$ upon completion of dashboard integrating analytics and real-time video stream processing via POLYTRON ONE Video Management Server;
10% upon delivery of all outstanding items to be provided by the SERVICE PROVIDER under this Agreement,
in each case within 14 working days of the date of the invoice issued by the SERVICE PROVIDER in respect of the relevant instalment payable.
The CUSTOMER shall make all payments due under this Agreement without any deduction or withholding whatsoever. If, by law, the CUSTOMER is unable to make such payments without deduction or withholding, it shall pay the SERVICE PROVIDER an additional amount so that the net amount received by the SERVICE PROVIDER equals the full amount that would have been received had no such deduction or withholding been made. If the CUSTOMER fails to pay any amount due and payable under this Agreement to the SERVICE PROVIDER on the due date, the CUSTOMER shall pay interest on such amount (from the time of default up to the time of actual payment) at a rate per annum equal to two percent (2%) above the then prevailing prime lending rate of DBS Bank Limited in Singapore.


All payments shall be made by bank transfer to the bank account of the SERVICE PROVIDER indicated in the Invoice or such other payment method as agreed by the SERVICE PROVIDER.


The CUSTOMER undertakes with the SERVICE PROVIDER that it will install a splash screen on each and every social media platform of the CUSTOMER relating to the Project, including, without limitation, the CUSTOMER’s applications and websites, on which the logos of the SERVICE PROVIDER and the phrases “POWERED BY VIZZIO.AI” and “POWERED BY POLYTRON.AI” shall be visible and prominently displayed.
The CUSTOMER further undertakes with the SERVICE PROVIDER that the CUSTOMER shall display the logos of the SERVICE PROVIDER and the words “POWERED BY VIZZIO.AI” and “POWERED BY POLYTRON.AI” in a prominent and visible position on all the CUSTOMER’S product literature relating to the Project, including, without limitation, videos, texts, audio recordings, and PDFs.
Nothing in this Agreement shall prevent or prohibit the SERVICE PROVIDER from publishing and promoting its involvement in the Project on any social media or platform in a manner the SERVICE PROVIDER deems fit. Additionally, this Agreement does not restrict the SERVICE PROVIDER from engaging in normal marketing or sales efforts related to the sale or licensing of its products and services to any third party or from participating in any other project with any third party.


The SERVICE PROVIDER will (a) provide the Services with all due care, skill and ability; and (b) keep the CUSTOMER informed of the progress of the Services. The SERVICE PROVIDER must comply with all applicable laws, regulations and codes applicable to the performance of the Services, including those relating to anti-bribery, anti-corruption and data protection in performing the Services.


Each party undertakes that it will not at any time use or disclose any confidential information concerning the business, affairs, customers or suppliers of the other party, except for disclosure to its employees, officers or advisors on a need-to-know basis, or disclosure required by any law, court or governmental or regulatory authority.


All Intellectual Property Rights owned by the SERVICE PROVIDER will remain vested in the SERVICE PROVIDER and shall not be assigned or licensed under this Agreement unless otherwise stated in the pricing clause for items that are licensed.
Nothing contained in this Agreement shall, by express grant, implication, estoppel or otherwise, create in either party any right, title, interest, or licence in or to the inventions, patents computer software or software documentation of the other party.
Except as provided in this Agreement, neither party shall use the name, or any proprietary marks or logo of the other party for any purpose whatsoever, whether in relation to any publication, publicity, advertisement, press release or otherwise, without obtaining the other party’s prior consent in writing, all of which restrictions shall survive the termination of this Agreement (howsoever caused).


The SERVICE PROVIDER warrants that (a) this Agreement and the performance thereof do not and will not violate any contract that applies to the Service Provider, and (b) the deliverables provided by the SERVICE PROVIDER do not and will not infringe on the intellectual property rights of any third parties. The CUSTOMER warrants that the use or incorporation of any material into the deliverables provided by the SERVICE PROVIDER do not and will not infringe on the intellectual property rights of any third parties.
The SERVICE PROVIDER products and services are free from material defects and substantially conform to the applicable warranties for such products and services. The software included in the intellectual property owned by the SERVICE PROVIDER and, to the knowledge of the SERVICE PROVIDER, all other software included in the intellectual property owned by the SERVICE PROVIDER does not contain (i) any clock, timer, counter or other limiting or disabling code, design, routine or any viruses, Trojan horses or other disabling or disruptive codes or commands that would cause the intellectual property owned by the SERVICE PROVIDERcontained therein to be erased, made inoperable or rendered incapable of performing in accordance with its performance specifications and descriptions, or otherwise limit or restrict the ability of the SERVICE PROVIDER or any of its subsidiaries to use the Service Provider Intellectual Property; and (ii) any back doors or other undocumented access mechanism allowing unauthorised access to, and viewing, manipulation, modification or other changes to, the intellectual property owned by the SERVICE PROVIDER.
Rectification of defects/issues with NIL cost to the CUSTOMER for 12 months. Faulty hardware and software issues will be rectified by the SERVICE PROVIDER at no cost to the CUSTOMER.


Either party may terminate this Agreement by giving notice of seven (7) days after (and not before) the first instalment of forty per cent (40%) of the total contract is price paid. The SERVICE PROVIDER may terminate this Agreement immediately if the CUSTOMER fails to pay any amount due and payable by it under this Agreement for more than seven (7) days whereupon the SERVICE PROVIDER shall have no further obligation under this Agreement.
Any termination by either party under this Agreement shall not affect any right or obligation of either party accrued prior to such termination including without limitation, the obligation of the CUSTOMER to pay for any deliverable rendered (whether wholly or in part) by the SERVICE PROVIDER under this Agreement.
Upon termination, all deliverables of the SERVICE PROVIDER provided under this Agreement shall be uninstalled and returned to the SERVICE PROVIDER together with all data and other Confidential Information that the CUSTOMER has in its possession.


During the term of the Agreement and for twenty-four (24) months after the end of the term, the CUSTOMER will not, without the prior written consent of the SERVICE PROVIDER: (a) encourage any employees or service providers of the SERVICE PROVIDERto stop working for the SERVICE PROVIDER; (b) encourage any customers or clients to stop doing business with the SERVICE PROVIDER, or (c) hire anyone who worked for the SERVICE PROVIDER over the twelve (12) months preceding the end of the term of this Agreement.


Neither party will be liable to the other for any indirect or consequential loss or damages (including any indirect loss of business, revenues, goodwill, anticipated savings, wasted expenditure or profits) arising out of or in connection with this Agreement, in each case whether arising from tort (including negligence), breach of contract or otherwise. Save as aforesaid, the maximum aggregate liability of each party arising out of or in connection with this Agreement, whether in tort (including negligence), breach of contract or otherwise, shall not exceed the total sum paid by the CUSTOMER and received by the SERVICE PROVIDER.


Neither party may assign or transfer any of its rights or obligations to another party without the prior written approval of the other party. This Agreement may only be amended with the consent of both parties. This Agreement constitutes the entire agreement of the parties and supersedes all oral negotiations and prior writings with respect to the subject matter hereof. If any provision of this Agreement becomes invalid or unenforceable, it shall be deemed modified (to the minimum extent necessary) to make it valid and enforceable, or where such modification is not possible, deemed deleted and shall not affect the validity and enforceability of the remaining provisions.


This Agreement and any dispute or claim arising out of or in connection with it or its subject matter or formation (including non-contractual disputes or claims) shall be governed by and construed in accordance with the laws of the Republic of Singapore.


Any dispute arising out of or in connection with this Agreement, including any question regarding its existence, validity or termination, shall be referred to and finally resolved by arbitration administered by the Singapore International Arbitration Centre (“SIAC”) in accordance with the Arbitration Rules of SIAC for the time being in force, which rules are deemed to be incorporated by reference in this clause.
The number of arbitrators shall be three (3). The seat, or legal place, of arbitration shall be in Singapore. The language to be used in the arbitral proceedings shall be English.

This Agreement has been entered into on the date stated at the beginning of THIS AGREEMENT.


By ____________________________________
Name ________________________________
Title __________________________________
Date __________________________________
VIZZIO Technologies Pte Ltd

By ____________________________________
Name ________________________________
Title __________________________________
Date __________________________________


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