TECH OFFERS

AI-assisted Mechanical Computer-Aided Machining (AMCAM) is a hands-on educational platform designed to teach students the principles and real-world applications of AI agentic agency within CNC machining. Built upon an AI agentic agency blueprint, AMCAM provides a new learning environment that integrates CNC milling operations with a suite of intelligent, autonomous AI agents. The system features five specialised AI agents functioning as digital co-workers, modeling collaborative decision-making between humans and AI in modern manufacturing contexts. Through this setup, students not only gain practical CNC machining experience but also engage with a full AI decision loop. They can observe how AI agents communicate, reason, and act both independently and collectively. Beyond education, AMCAM also serves as a sandbox for SMEs and MNCs to co-develop pilot projects, in alignment with Singapore’s Smart Industry Readiness Index (SIRI). It supports the Industry Transformation Maps (ITMs), advancing national strategies to modernise the precision engineering and manufacturing sectors, while driving workforce transformation and enterprise growth. Key focus areas include deploying AI for predictive maintenance, quality control, supply chain optimisation, and energy efficiency. Other applications include digital twins, machine learning algorithms, and smart sensors to accelerate industry transformation. Introduction of AI Agentic Agency for Collaborative Learning: AMCAM uses Agentic AI, where digital agents act as collaborative partners, helping students understand AI-driven decision-making and preparing them for future human–AI collaboration in smart manufacturing environments. Augmenting Experiential Learning: AMCAM enhances traditional CNC milling training by introducing interactive systems that deepen engagement with the machining process, enabling students to gain both theoretical knowledge and practical, real-world experience. Addressing the Complexity of Machining Parameters: AMCAM helps learners master key maachining variables such as speed, feed rate, and tool condition by providing instant, intelligent feedback to guide effective parameter balancing and improve machining outcomes. Digitalisation of Legacy Machines : AMCAM upgrades legacy CNC machines with AI integration, enabling real-time diagnostics and performance monitoring to enhance learning and extend the usefulness of existing equipment. Real-Time Feedback: AMCAM uses a Simple Reflex Agent that adjusts machining parameters in real time based on vibration patterns, classifying performance into green, amber, and red alerts to enhance safety, minimize downtime, and ensure precise, responsive machining. Green Alert (Safe Cut): Steady-cutting conditions, no action. Amber Alert (Warning Cut): Medium instability, tool inspection performed. Red Alert (Danger Cut): Severe instability, emergency stop initiated.   Applicable in Education and Industry: AMCAM enhances education by visualizing complex machining concepts and supports industry by improving quality, productivity, and sustainability in large-scale manufacturing. AMCAM reduces machine downtime through predictive alerts, enhances product quality with AI-driven reliability, and optimizes material and energy use for more efficient and sustainable operations. AMCAM is suitable for a wide range of industries, including Precision Engineering, Manufacturing, Aerospace, and Marine & Offshore, where complex machining plays a critical role. It can also be applied as an educational tool for hands on learning in machining. Core functionalities include: Real-Time Monitoring: Continuous data collection through IIoT sensors. AI-Driven Anomaly Detection: Rapid identification and response to performance irregularities. Automated Remediation: Autonomous execution of corrective actions without human input. Collectively, these capabilities minimise machine downtime, reduce maintenance frequency, and lower dependency on highly specialised technicians. Innovative Learning Pedagogy: The educational model employs a deeper learning approach that merges explicit technical knowledge with dual heuristic inputs. Interdisciplinary and Future-Ready Learning: AMCAM promotes interdisciplinary education by combining machining fundamentals with AI and manufacturing. Learners engage with digital-twin environments, intelligent CNC programming, and predictive maintenance, aligning their skills with Industry 4.0 and 5.0 workforce needs. AI-Assisted Manufacturing: AMCAM empowers both learners and professionals with AI-assisted manufacturing capabilities, emphasizing system-level thinking, anomaly detection, and operations optimisation. This allows users to conduct predictive diagnostics and make data-informed decisions. Infocomm, Artificial Intelligence, Manufacturing, Subtractive Machining

Falls are a leading cause of injury and hospitalization among the elderly, often resulting in loss of independence and increased healthcare costs. Traditional walking aids provide basic support but lack the capability to proactively detect and prevent falls. This AI-Assisted Walking Cane is an innovative mobility aid developed to improve the safety and independence of elderly users and individuals with mobility challenges. By enabling real-time monitoring and intervention, it effectively bridges a critical gap in traditional walking aids and helps reduce the risk of falls. The primary target users are elderly individuals, patients undergoing physical rehabilitation, and people with neurological or musculoskeletal conditions that impact mobility. The technology owner seeks collaboration with partners across the healthcare, technology, and manufacturing sectors to support the product’s development, testing, and commercialization. Ideal partners include medical institutions and rehabilitation centres to provide clinical validation, user trials, and professional feedback; deep-tech companies with AI and data analytics expertise to develop and optimize algorithms for gait analysis and fall detection; assistive device manufacturers for prototyping, large-scale production, and quality assurance; institutes of higher learning for joint research in biomechanics, sensor technologies, and future applications; and eldercare service providers or community health organizations to facilitate pilot testing and deployment in real-world care settings. The AI-Assisted Walking Cane combines advanced hardware and software components, integrating sensors and artificial intelligence to monitor the user’s gait, detect abnormal walking patterns, and provide intelligent mobility support with proactive fall risk detection. Advanced Hardware Integration - The device features an embedded microcontroller, tilt sensor, accelerometer, gyroscope, and vibration motors that work together to continuously monitor the user’s gait, posture, and cane tilt during movement. Intelligent Fall Detection and Alerts - The device integrates an advanced algorithm that continuously analyses the user’s gait patterns and posture in real time. By detecting abnormal movements or signs of instability that may indicate a potential fall, the device provides immediate alerts through vibration or audio signals to prompt corrective action or notify caregivers. Connectivity and Data Insights - The device transmits collected data via Bluetooth or Wi-Fi to a companion mobile application, allowing users, caregivers, and healthcare professionals to track mobility trends and monitor progress.  User-Centric Design - The device is powered by a rechargeable, energy-efficient battery that supports extended use, and its lightweight, ergonomic design ensures comfort and ease of use for everyday mobility support. The AI-Assisted Walking Cane has broad potential across healthcare, rehabilitation, and assistive technology sectors, with applications in both clinical settings and home-based care to enhance mobility, safety, and independence for individuals with gait or balance challenges. Primary applications include real-time fall detection and prevention, gait monitoring to track rehabilitation progress, and early identification of mobility decline in elderly users or individuals with neurological or musculoskeletal conditions. The data collected also supports healthcare professionals in developing personalized therapy plans and targeted intervention strategies. This technology can serve as a foundation for a range of marketable products beyond the walking cane, including AI-enabled crutches, walkers, and wearable gait monitors. It also supports the development of companion mobile apps and cloud-based platforms for remote monitoring, caregiver alerts, and long-term mobility data analysis. This technology addresses the growing demand for intelligent assistive devices that enhance quality of life and reduce caregiver burden, offering a practical, scalable solution for improving mobility and safety in eldercare and rehabilitation settings. Unlike traditional walking canes that provide only basic physical support, the AI-Assisted Walking Cane incorporates sensors and AI algorithms to continuously analyse gait and detect instability in real time, offering proactive alerts and enhanced safety for users. Unlike existing smart canes that focus mainly on location tracking or emergency alerts, this technology emphasizes preventive care through real-time gait analysis and predictive fall detection, setting it apart from current state-of-the-art solutions. It also provides personalized alerts for users, promoting independence while ensuring safety. Furthermore, the system’s integration with mobile applications and healthcare platforms enables remote monitoring and data-driven decision-making—features not commonly found in basic mobility aids. Its affordability, ergonomic design, and low maintenance further enhance its market appeal. AI-assisted mobility aid, smart walking cane, fall detection, gait analysis, fall prevention, assistive device, rehabilitation, IoT, eldercare Electronics, Sensors & Instrumentation, Healthcare, Medical Devices

This technology leveraged multiple advanced components to deliver an immersive, data-driven BI (Business Intelligence) dashboard for smart building management. 3D visualization and integration formed the dashboard’s intuitive interface, utilizing a photorealistic 3D-scanned building. Technologies such as laser scanning and photogrammetry were used to create the digital twin. This 3D model was then integrated with real-time IoT data using Building Information Modeling (BIM) principles, enabling visualization of sensor data directly within the digital replica of the building. An IoT sensor network and data acquisition system played a crucial role, with various sensors deployed to monitor building performance, energy usage (including non-invasive water and power monitoring), and environmental conditions. These sensors transmitted data wirelessly,  using protocols such as MQTT and LoRaWAN to an IoT platform. For data processing and storage, an edge IoT platform served as the backbone for collecting, processing, and managing large volumes of real-time sensor data. Built-in rule engines enabled data enrichment and automated alerting. Finally, immersive dashboard development frameworks were pivotal in creating interactive user experience. Web-based 3D visualization libraries rendered the building model and integrated dynamic data overlays. While BI tools such as Tableau or Power BI may have supported traditional dashboard components, custom immersive development provided a more intuitive 3D environment for navigation and data exploration. The dashboard’s technical architecture adopted a multi-layered approach. The data acquisition layer leveraged diverse IoT sensors (e.g., environmental sensors and smart meters) communicating via protocols such as Modbus and LoRaWAN, connected through industrial IoT gateways. For non-invasive water and power measurements, ultrasonic or electromagnetic flow sensors and current transducers were integrated to minimize installation disruption. The data processing and storage layer utilized an edge-based IoT platform for secure data ingestion, real-time stream processing, and scalable storage. The visualization and interaction layer was built on a web-based Unity framework to render a photo-realistic 3D building model. This enabled immersive navigation and direct interaction with virtual representations of sensor locations. Drill-down capabilities supported granular data exploration from floor-level summaries to individual sensor readings, ensuring a comprehensive, data-driven operational overview.  The technology provider seeks partnerships with real estate developers, facility management firms, and building technology providers focused on smart, sustainable infrastructure. Collaboration may also involve hotel chains, mall operators, and data centre owners aiming to enhance operational efficiency and ESG performance. Real Estate & Facility Management Precision Utility Management: Real-time data from smart power and water meters enables precise consumption control. Facility managers can detect leaks or identify energy-intensive equipment instantly, reducing utility costs, an important factor in Singapore’s dense urban environment. Resource Efficiency & Compliance: The dashboard supports Singapore’s Green Mark certification and national water conservation initiatives by providing verifiable data on consumption reduction, efficiency performance, and improvement opportunities. Predictive Maintenance: Continuous monitoring of flow rates, pressure, and power quality allows early detection of potential plumbing or electrical issues, enabling proactive maintenance that minimizes costly outages. Occupant Engagement: Personalized dashboards within the immersive 3D model display each tenant’s consumption, fostering awareness and encouraging sustainable behavior aligned with national conservation drives. Commercial & Hospitality Operational Efficiency & Cost Savings: Hotels, shopping malls, and data centres can cut utility expenditures by identifying inefficiencies in real time, improving profitability and operational performance. ESG Reporting & Branding: Detailed utility data strengthens Environmental, Social, and Governance (ESG) reporting and highlights a reduced environmental footprint, enhancing brand reputation and appeal among sustainability-minded customers and investors. Enhanced Guest Experience (Hospitality): Optimised utility systems ensure stable comfort conditions, such as consistent air conditioning and water pressure, while supporting eco-friendly operations that resonate with modern travellers. The technology lies in its unprecedented integration of photorealistic 3D building visualization with granular, real-time IoT data on environmental conditions, power, and water utilities. It specifically leverages non-invasive measurement techniques, all delivered through an immersive and highly interactive dashboard. Unlike traditional BI dashboards that present data in flat, abstract formats, or existing BIM solutions that lack real-time sensor integration, this project provides an intuitive, spatial understanding of utility consumption. Stakeholders can virtually “walk through” a digital twin of their building to pinpoint locations of high-power draw or water leakage through visual data overlays. A key differentiator is the emphasis on non-invasive measurement, which enables seamless retrofitting into existing buildings with minimal disruption, significantly reducing adoption barriers for facility managers seeking immediate, data-driven insights into their utility footprint within Singapore’s dense built environment. This immersive experience transforms abstract data into actionable intelligence, fostering a deeper understanding of building performance. It drives resource conservation, enables rapid anomaly detection, and empowers more effective, data-driven decision-making for sustainability and operational efficiency, directly supporting Singapore’s Smart Nation and environmental objectives. Immersive, IoT, Dashboard, Sustainability, ESG, Green Mark Green Building, Sensor, Network, Building Control & Optimisation, Infocomm, Smart Cities, Sustainability, Sustainable Living

This AI-driven platform revolutionizes how construction and infrastructure projects are managed by transforming vast, unstructured project data into actionable intelligence. Built upon a large language model (LLM) trained on domain-specific data including regulatory requirements, contract documents, project schedules, communication logs, digital drawings, and specifications, the technology provides real-time insights and foresight across project lifecycles. It detects risks, predicts cost and schedule deviations, and highlights potential regulatory non-compliance before they escalate into major issues. By integrating across existing tools and data sources such as Microsoft Teams, WhatsApp, SharePoint, and email systems, the AI engine enables project stakeholders to make informed decisions through a single intelligent interface. Ideal collaboration partners include real estate developers, construction contractors, architecture and engineering consultants, and AI software integrators seeking to augment project performance through predictive analytics and knowledge automation. The platform combines AI-powered analytics, retrieval-augmented generation (RAG), and multi-source data integration to deliver deep insights across complex construction environments. Key components include: Data Ingestion Engine: Connects to structured and unstructured data sources (contracts, drawings, communications, etc.) for comprehensive knowledge assimilation. Construction LLM Core: Continuously trained on industry-specific datasets to identify risk factors, cost trends, and schedule slippage patterns. Risk and Compliance Module: Detects potential regulatory breaches, project scope deviations, and cost anomalies through automated reasoning. Search & Advisory Interface: Enables natural language queries for retrieving contextual project information, insights, and recommendations. It acts as an intelligent co-pilot for construction decision-making. Construction Project Management: Real-time detection of risks, non-compliance, and cost anomalies across multiple projects. Smart Infrastructure Development: Predictive analytics for large-scale public and private infrastructure programs. Software Integration for Built Environment: Embedding AI insights into existing ERP and workflow systems for developers and contractors. Complex Project Coordination: Enabling consultants and architects to query and visualize project intelligence across large digital datasets. This technology can be deployed by companies in construction, real estate development to improve efficiency, compliance, and profitability across the project lifecycle. This AI platform provides interpretive and predictive intelligence. Its unique strength lies in synthesizing information across disconnected systems. from contracts to chat messages, and generating foresight into cost overruns, schedule delays, and regulatory risks. By acting as a “digital advisor” that understands construction semantics, it helps project teams anticipate challenges, optimize resources, and make timely, data-driven decisions. This transforms reactive project management into proactive and predictive project governance. Construction, Cost Optimization, Risk Identification, Regulatory Compliance, AI, Analytics, Insights Infocomm, Big Data, Data Analytics, Data Mining & Data Visualisation, Artificial Intelligence

Speech and voice disorders can significantly affect a person’s ability to communicate and engage with others, especially during childhood development. While special education schools provide valuable support within their premises, there remains a critical need for tools that empower individuals to communicate more confidently in everyday environments. This assistive communication technology bridges that gap. It combines both hardware and software to help users, primarily children under 12, though suitable for anyone who requires speech assistance to express themselves more clearly. Importantly, the device is not meant to replace natural speech but to supplement it, providing users with an additional way to articulate words or phrases that may be difficult to pronounce. In doing so, it supports inclusive communication and helps individuals build confidence in social interactions. This technology can be deployed in collaboration with special education institutions, medical device manufacturers, and software developers focusing on speech therapy and assistive technologies. The solution comprises both hardware and software components integrated into a mobile application compatible with most smartphones. For children under 12, the system is paired with a small, lightweight device sourced from a non-conventional mobile phone maker to ensure portability and ease of use. A unique feature of the system is its “focus lock” mode: once the application is activated, it cannot be exited without caregiver intervention, preventing distraction and ensuring the child remains engaged with the communication task. Parents or caregivers can remotely upload new words or phrases, allowing the vocabulary database to grow in tandem with the user’s progress and learning needs. The solution has already been implemented at a special-needs school in Singapore. It holds strong potential for broader use across early childhood care, special education, and speech therapy centers both locally and globally. By listing the app on mainstream mobile app stores, it can reach families and caregivers worldwide seeking cost-effective, user-friendly communication support tools. Many current communication apps fail to sustain engagement because children can easily exit the application and become distracted by other phone functions. This solution eliminates that challenge through its “lock-in” mode, which keeps users focused on communication activities. Additionally, the system is designed to work on most existing mobile devices, reducing hardware costs. Caregivers benefit from the ability to customize vocabulary remotely, ensuring the tool evolves with each child’s development. The combination of affordability, flexibility, and sustained engagement makes this solution a practical and inclusive advancement over existing options in the market. Assitive Communication Device Healthcare, Telehealth, Medical Software & Imaging, Sustainability, Sustainable Living

Coronary artery disease (CAD) is the leading cause of death worldwide. Computed Tomography Coronary Angiography (CTCA), as a non-invasive alternative to invasive catheterized coronary angiography, has emerged as a recommended first-line investigation for CAD. However, the current practice of generating reports involves a time-intensive process, with CT specialists spending 3-6 hours annotating scans. Furthermore, there is a lack of effective tools for analysing coronary calcium scores, stenosis severity, and plaque characterization. This AI driven platform is for CT data processing that provides a streamlined 'one-stop' solution spanning from diagnosis to clinical management and prognosis. Its key features include: AI-driven platform for CTCA, catering to clinical, research, and industrial applications. Large, shareable, de-identified, Personal Data Protection Act-compliant real-world CT data. Precision toolkits for anonymization, coronary calcium scoring, epicardial adipose tissue (EAT), stenosis severity assessment, plaque quantification, CT fractional flow reserve (FFR), and reporting. The platform’s highly automated features assist physicians in interpreting and synthesizing large volumes of CT data, while minimizing bias, increasing reproducibility, and providing numerical insights in a graphical manner. It offers a comprehensive ‘one-stop’ solution for diagnosis and clinical management of CAD. Seamless integration: The DICOM-compliant parser ensures compatibility with diverse CT scanners without interfering with hospitals’ original workflow processes. AI-driven workflow: It supports fully automated analysis, including deep learning-based segmentation of the coronary artery tree, extraction of artery centrelines, tracking and acquisition of cross-section lumen images, artery labelling, stenosis and plaque detection, and quantification with high accuracy within minutes.  Comprehensive modules for CAD assessment: The technology offers a comprehensive assessment of coronary calcium score, EAT, stenosis, and plaque phonotypes. Mixed Asian registry database: It houses a vast repository of multi-ethnic imaging and non-imaging data, serving as a valuable resource for research and analysis. Annotation by SCCT-certified experts: All annotations are performed and quality-checked by experts certified by the Society of Cardiovascular Computed Tomography (SCCT). Secure and reliable data platform: The data platform is certified by the Ministry of Health Singapore, ensuring the safety and reliability of data access. The technology can be applied across various industries: Software as a clinical service for healthcare institutions: It provides comprehensive CAD assessment and personalized treatment as a software-as-a-service (SaaS) solution for healthcare institutions. Pharmaceuticals: It enables objective and quantitative measurement of the effectiveness of treatments. MedTech and digital health industry: By harnessing state-of-the-art technology and big data capabilities, it provides the development of customized foreground intellectual property, addressing the specific needs of individual companies. Local MedTech industry development: It offers tailored solutions designed specifically for small and medium-sized enterprises (SMEs) and startups, empowering them to compete globally, foster innovation in product development and services that align with market demands, and enhance patient care. It provides a thorough evaluation of the coronary arteries using deep learning algorithms and patented post-processing technologies. It serves as a ‘one stop’ platform that spans from diagnosis to clinical management and prognosis, and aiding in predicting therapy response in the pharmaceutical industry. Superior diagnostic performance: The AI toolkits deliver exceptional accuracy, surpassing 90%, while processing the data within minutes. This remarkable speed is 20 times faster than the standard diagnostic and reporting process, enabling efficient and timely decision-making. Unparalleled big data repository: The platform houses the largest mixed Asian CAD registry, comprising 5,000 patients (n=3 million images). This vast collection contains a wealth of real-world imaging and non-imaging data, representing a unique and invaluable resource that is unmatched elsewhere. Trusted ground truth: Every CT scan has been meticulously annotated and quality-checked by SCCT-certified experts. This rigorous process ensures the accuracy and reliability of the data, establishing a safe and dependable foundation for clinical decision-making. Healthcare, Telehealth, Medical Software & Imaging

Radiation therapy is a cornerstone of clinical cancer treatment. However, high doses often result in unavoidable damage to healthy tissues, as well as tumour resistance and metastasis, which limit its broader clinical application. Clinical imaging techniques have limitations in detecting very small tumours (< 5 mm) located deep within tissues, hindering early diagnosis and timely medical intervention. This technology introduces a next-generation theranostic platform for cancer imaging and therapy based on Organic Radio-Afterglow Nanoprobes (RANPs) designed for ultrasensitive deep-tissue cancer imaging with long afterglow signals and biomarker activation, enabling early detection and surgical precision/treatment. RANPs integrate three functional components: Radioabsorber – converts X-ray energy into radioluminescence. Radiosensitizer – activated by radioluminescence to generate singlet oxygen (1O2). Radioafterglow substrate – reacts with 1O2 to form intermediates that emit persistent afterglow. This platform also introduces a tumour-specific biomarker-activatable nanoprobe (tRANP) that allows for highly specific tumour detection and potential surgical removal of minute tumours (as small as 1 mm³) at an X-ray dose comparable to a single CT scan. The highly reactive oxygen species (1O2) generated from low-dose X-ray irradiation enables Radiodynamic Therapy (RDT) that can eradicate tumours and reduce metastasis demonstrating its potential for cancer treatment. This technology poses a strong fit to address personalized medicine. The technology owner is seeking to collaborate with Clinical and medical partners specializing in early detection, surgical and radiation oncology. Partners with experience translating nanomedicine or theranostic agents into clinical trials. Companies working on nanoparticle radiosensitizers, imaging agents, or radiotherapy platforms. Cascade X-ray energy transfer by organic molecules: By fine-tuning radioluminescence and 1O2 transfer among key nanoparticle components, this technology first demonstrated the mechanism of efficient conversion of X-ray energy into optical afterglow signals and 1O2 generation, enabling tumour theranostics in murine models.   Modular and customizable design: The modular composition and well-defined mechanism of RANPs allow the loading of various optical agents, enabling tunable emission wavelengths, radio afterglow brightness, and ROS generation efficiency to meet different cancer theranostic needs. Ultrasensitive cancer detection at incipient stage: Imaging and surgical removal of tiny tumours (below 1 mm³) can be achieved at an X-ray dose comparable to a clinical CT scan (mGy level) and 20 times lower than that required for inorganic materials. Precision cancer therapy with minimal X-ray dosages: The efficient radiodynamic 1O2 generation by tRANPs enables complete tumour eradication at X-ray doses lower than clinical radiotherapy and with drug doses one to two orders of magnitude lower than those required for most inorganic agents, thereby prolonging survival while minimizing radiation-related side effects. Oncology Diagnostics: Addresses the unmet need for early-stage tumour detection, especially in deep-seated tissues where existing imaging (MRI, CT, PET) has limitations. RANPs can be tailored to respond to specific disease biomarkers, facilitating the detection of other cancers and diseases (e.g., infectious diseases, diabetes). Tumour Staging: RANP signals correlate with increasing biomarker levels and tumour size. Cancer Therapeutics: Provides a safer, more effective alternative or complement to radiation therapy by lowering dosage and enhancing treatment outcomes. Due to their high X-ray sensitivity, RANPs can generate ROS for Radiodynamic Therapy (RDT) of cancer and potentially infectious diseases at any tissue depth reachable by X-rays, delivering precise and safe treatment of deep-seated diseases at a minimal dosage. Surgical Applications: Enables real-time intraoperative guidance for precise tumour removal and reduces recurrence rates. Bimodal Imaging Probes: The similarity in X-ray settings of computed tomography scanners and RANPs allows for the simultaneous acquisition of both anatomical and molecular information of diseases in a single computed tomography scan. Combined with whole-body CT scanning, low-dose X-rays can activate RANPs that have accumulated in potential metastatic sites, assisting in metastasis screening. Dual-Functionality Theranostics: This study developed an integrated organic nanoplatform for simultaneous cancer diagnosis and therapy. By adjusting the radiation dose from mGy to Gy levels, it enables rapid switching between imaging and treatment, achieving both imaging and therapy after a single injection of a single probe.   Minimized Side Effects: In contrast to traditional radiotherapy, which typically requires prolonged treatment cycles, high radiation doses, and causes notable side effects, RANP-mediated tumour therapy operates at radiation doses ~10 times lower than conventional radiotherapy, reducing collateral damage to healthy tissues and demonstrating substantial clinical potential, especially for X-ray-sensitive organs (e.g., liver). Tumour-Specific Targeting: RANPs offer exceptional sensitivity for tumour detection, capable of identifying tumours as small as 1 mm³— a level of precision that many current clinical imaging modalities cannot reach. When combined with standard hospital CT scanners, this technology can significantly enhance diagnostic sensitivity and accuracy, holding great promise for early cancer screening. Persistent Signal Advantage: Long signal half-lives improve imaging resolution, reduce background noise compared to real-time fluorescence imaging, and enable functionality at tissue depths of up to 15 cm. Biocompatible: Compared to inorganic materials, which often pose challenges in metabolism and potential toxicity, the components of the organic nanoparticles in this system exhibit excellent biocompatibility and safety, and they can be efficiently metabolized and cleared from the body. Cancer, Imaging, Diagnosis, Radiotherapy, Nanomedicine Healthcare, Diagnostics, Telehealth, Medical Software & Imaging

Bioplastics have emerged as a sustainable alternative to conventional petroleum-based plastics, offering biodegradability and reduced carbon footprint. However, their use in high-performance applications remains limited because of inherent material weaknesses. A key challenge is their poor barrier properties, particularly against water vapour and gases such as oxygen and carbon dioxide. This limitation prevents bioplastics from being widely adopted in packaging applications that demand strong protective qualities, such as food products, pharmaceuticals, and sensitive electronic components. In most cases, bioplastics are restricted to low-demand items like disposable bags or cutlery, where barrier performance is not critical. This technology addresses the key challenge of poor barrier properties by introducing a plant-waste-derived additive that enhances barrier properties of bioplastics. Incorporated directly during melt processing, the additive reduces the water vapour transmission rate (WVTR), enabling bioplastics to provide effective moisture protection. Because the additive is derived from upcycling of plant waste, it reinforces the sustainability narrative while aligning with circular economy principles. This technology also functions as a drop-in solution compatible with existing manufacturing processes, allowing packaging producers to adopt the technology without costly modifications. The technology owner is interested in co-development R&D opportunities and out-licensing of the developed IP with companies developing sustainable bioplastic products with enhanced barrier properties. This technology is an eco-friendly additive that enhances barrier performance in bioplastics. Key features of this additive include: Made from recycled plant waste Improves bioplastics’ ability to block water vapour without compromising on mechanical strength (tested according to ASTM F 1249-20) Drop-in solution – no changes required to current bioplastic manufacturing process The additive has been successfully tested with PBAT to decrease its WVTR. Food packaging: Sustainable packaging with effective moisture barrier properties is ideal for products like bakery items, cereals, snacks etc, catering to diverse shelf-life requirements. Medical and pharmaceutical packaging: Bioplastics with enhanced barrier properties can be used for packaging sensitive medical devices and pharmaceuticals that require protection from moisture or oxygen. Personal care and cosmetics: Sustainable packaging solutions cater to moisture-sensitive personal care products like lotions, creams, or shampoos. Agricultural: Biodegradable mulch films with improved water vapor control for agriculture. Offers a sustainable bioplastic additive as it is derived from plant waste Improves barrier protective properties of bioplastic by 25% Seamless integration with existing bioplastic manufacturing processes Plant Waste Valorisation, Bioplastic, Packaging, plant based, barrier, additive, water vapour transmission rate, WVTR, valorisation, processing Chemicals, Additives, Waste Management & Recycling, Food & Agriculture Waste Management, Sustainability, Circular Economy

In today’s rapidly evolving business landscape, digital transformation has become a strategic imperative for companies across industries. At the core of this transformation lies Artificial Intelligence (AI)—a technology that is increasingly recognized as a key enabler of innovation, operational efficiency, and competitive advantage. However, despite its transformative potential, AI adoption remains a challenge for many organizations. High development costs, specialized expertise requirements, and complex deployment pipelines often limit AI accessibility to large enterprises with dedicated AI engineering teams. Vision-based AI models, in particular, require extensive training, fine-tuning, and maintenance. Even after initial deployment, continuous retraining are necessary to ensure consistent performance, resulting in substantial costs and resource demands. To overcome these challenges, the technology owner has developed a suite of pre-trained, customisable, and continuously learning AI models that enable rapid deployment for automated visual inspection. Delivered through a modular AI platform, the solution empowers customers to build, customise, deploy and scale AI inspection solutions cost-effectively, without requiring deep AI expertise. The AI models can process both video footage and static images from conventional camera systems, transforming them into intelligent, AI-powered inspection tools adaptable to diverse use cases. The technology is available for R&D collaboration, licensing, and test-bedding with industry partners, including system integrators, manufacturers, and inspection service providers. Automated Visual Inspection Capabilities Pre-trained, state-of-the-art vision-based AI models with high accuracy Automated report generation powered by AI Continuous learning capability to ensure high accuracy and consistent performance Rapid and customizable deployment to meet diverse inspection needs Integration with Conventional Camera Systems Converts conventional cameras into smart inspection systems Compatible with different types of cameras and applications Local deployment services to ensure data security and privacy On-premise or cloud-based deployment available Data stored locally to support continuous learning and performance optimisation Ready-to-deploy vision-based AI models for inspection and safety This technology offer comprises a suite of visual AI models applicable to various types of visual inspection tasks, including but not limited to: Building façade inspection with BCA compliance Production line inspection Safety monitoring through CCTV Construction inspection (i.e. personal safety) Interior inspection Prohibited zone and compliance checks Vehicle Speed Detection Wellbeing and behaviour recognition Cost-efficient pre-trained AI model with high accuracy Rapid deployment and scalability across multiple use cases Customisable solutions tailored to different camera systems Cloud-based or on-premises deployment for flexibility and data sovereignty Continuous learning ensures sustained accuracy and adaptability over time Accelerates digital transformation by lowering the barrier to AI adoption AI, Smart Camera, Machine Vision, Visual Inspection, Safety Monitoring, Smart Factory, Product Inspection, Blockchain, Computer Vision, Video/Image Analysis Infocomm, Video/Image Analysis & Computer Vision, Video/Image Processing, Artificial Intelligence