TECH OFFERS

Critical facilities and infrastructures face growing risks from equipment failures, costly downtime, and safety hazards, while traditional inspections often lack the speed and accuracy required to address these challenges. This innovation combines physical non-destructive testing (NDT) with AIoT-driven predictive analytics to deliver continuous, real-time monitoring that enhances safety, efficiency, and resilience. As an advanced IoT predictive maintenance technology, the platform enables faster fault identification and proactive intervention in mission-critical environments. Engineered with business continuity and rapid incident response at its core, the system detects early anomalies, prioritizes risks, and enables proactive maintenance to reduce disruptions and ensure compliance. Its key advantage lies in a proprietary dataset of over 10 million hours of real-world operational data from HVAC, motor, and pump systems in metropolitan environments, enriched with expert domain labelling. This unique resource powers machine learning models with superior accuracy, outperforming conventional predictive tools that lack real-world grounding. The platform is also the first industrial transformer-based multimodal AI system, integrating diverse sensing modalities with unmatched precision. Its scalable, modular design supports multi-sensing, multi-modal applications across diverse sectors. By shifting from reactive or scheduled maintenance to predictive, condition-based asset management, the solution bridges gaps left by inspections and supervisory control and data acquisition (SCADA) systems, resulting in safer operations, optimized resource use, and measurable ROI.  The technology owner is seeking collaboration with industrial partners, including property owners, operators of power plants and utilities, transportation providers, government agencies, and industrial facility managers, who aim to minimize downtime, extend asset lifecycles, and strengthen resilience against failures. Physical Sensors & NDT Hardware Vibration, current, RPM, thermal, acoustic, and analogue data converter IoT-enabled data acquisition units for real-time streaming Edge/cloud computing station for on-site signal pre-processing AIoT Platform & Software Industrial transformer-based multimodal AI engine Machine learning models trained with >10M hours of real-world operation data Multi-sensing and multi-model analytics integrating video, audio, and environmental signals Cloud-native dashboard with predictive analytics and risk prioritization Integration API with BACNET, Modbus connection Continuity & Response Layer Automated anomaly detection & early-warning alerts Seamless integration of Incident response with existing SCADA or BMS systems Actionable recommendations for optimize maintenance scheduling and resource allocation Scalability & Integration Modular design for HVAC, moto-and-pump, power systems, and critical infrastructure API/SDK for seamless integration with enterprise asset management software Cybersecurity-ready architecture for mission-critical operations This technology delivers ready-to-adopt modular solutions, including AIoT predictive maintenance platforms, smart NDT-enabled sensors, multi-modal industrial monitoring systems, and cloud-based asset health dashboards. Potential applications include: Energy & Utilities: Predictive monitoring of transformers, turbines, and pumps to prevent unplanned outages and extend asset lifecycles Transportation Infrastructure: Monitoring of rail, metro, and airport motor-driven systems to enhance safety, reliability, and service continuity Commercial Properties & Data Centres: Protection of HVAC, motor, pump, and IT infrastructure to maintain occupant comfort and ensure IT uptime Industrial Facilities: Continuous monitoring of motors and machinery to minimise costly breakdowns and unplanned downtime Disaster Resilience & Recovery: Rapid condition assessment after earthquakes, floods, or accidents to confirm system integrity, identify urgent repairs, and support faster recovery and continuity of essential services Future Expansion: Scalable multi-sensing analytics for smart cities, water treatment plants, and public safety infrastructure Superior Accuracy: Validated by hospitals and power plants in Hong Kong, the multi-modal, transformer-based AI generates a machine health index, predicting potential failures up to 6 months in advance Proprietary Dataset: Trained on over 10 million hours of real-world machine data, enriched with domain expert labelling, delivering a competitive advantage with every new deployment Plug-and-Play Simplicity: Designed for fast implementation with integrated sensing intelligence, eliminating reliance on costly expert interpretation Proven ROI & ESG Impact: Achieved 2–10x ROI, extended asset lifecycles by more than 25%, and reduced energy consumption by over 18%, turning costly maintenance into a strategic advantage AIoT Predictive Analytics, Non Destructive Testing, Industrial Transformer, Multimodal System, Multi Sensing Analytics, Critical Infrastructure, Business Continuity, Incident Response, Predictive Maintenance, Condition Based Maintenance Infocomm, Artificial Intelligence, Internet of Things, Smart Cities

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 packaging, 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 organic additive that enhances barrier properties of bioplastics. Incorporated directly during melt processing, the organic additive reduces the water vapour transmission rate (WVTR), enabling bioplastics to provide effective moisture protection for applications such as bioplastic food packaging. 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 recognised as a key enabler of innovation, operational efficiency, and competitive advantage. As companies accelerate adoption, a rapid deployable approach has become essential, especially for industries seeking an AI visual inspection system that supports automation and fast scaling. However, despite its transformative potential, AI adoption remains a challenge for many organisations. High development costs, specialised 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 – making automated deployment strategies and rapid deployable AI architectures increasingly valuable. 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 and acting as a scalable, automated AI visual inspection system suitable for multiple industries. 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

The global push for sustainability is driving demand for innovative solutions to reduce waste and conserve resources. While the focus has often been on synthetic materials like plastics, millions of tons of agricultural waste remain underutilized. Instead of being landfilled or incinerated, this renewable feedstock offers a major opportunity to support a circular economy and lessen dependence on virgin resources, especially as industries seek new ways to upcycle agricultural by-products into higher-value materials. These advancements also align with broader efforts to strengthen sustainable agriculture in Singapore as the nation seeks eco-friendly material innovations. This technology is a proprietary, chemical-free process that converts agricultural by-products into durable, eco-friendly materials. By harnessing diverse agricultural waste streams, this process yields thin plates and modular elements that can replace conventional raw materials in applications such as roofing, flooring, furniture surfaces, and wall furnishings. Designed for circularity, these materials can be broken down and reintroduced as feedstock at the end of their lifecycle, minimising waste and maximising resource efficiency in ways that further support sustainable agriculture in Singapore. The technology owner is actively seeking R&D co-development and out-licensing of the developed IP to companies intersted in advancing sustainable materials and scaling this circular economy solution.  The technology offers an innovative approach to material science, converting diverse agricultural waste, e.g. palm fronds, coconut husk, into high-performance alternative materials through a chemical-free, direct conversion process. Key features of this process technology include: Eliminates the need for harsh chemical pre-treatments common in other bio-composite methods Produces new materials with immeasurable recyclability as a primary feedstock Offers broad feedstock versatility, creating materials of superior functional properties Adaptable to allow seamless integration into various product forms e.g., flat panels, intricate moulded components etc The technology's primary application is in the building and construction industry, where it offers a much-needed sustainable alternative to conventional materials. This versatile technology supports a wide range of products, including but not limited to: Non-structural panels - engineered panels for walls, subflooring, floor tiles, providing sustainable alternatives to traditional plywood, particle board, and plasterboard. Insulation materials - this process yields potentially effective thermal and acoustic insulation boards or loose-fill materials for walls, and floors. Interior finishings – for aesthetics and decorative purposes e.g. wall panels, floor tiles, and surface coverings. Moulded components - the technology allows for the creation of custom-moulded elements and therefore offers design flexibility. Sustainable packaging – able to develop sustainable and biodegradable packaging solutions. Other material alternatives - includes sustainable substitutes like recycled plastic lumber and pavers, broadening the scope of eco-friendly construction possibilities. Recycled plastic composite materials alternatives - create advanced composite materials by blending agricultural waste with recycled plastics, enhancing properties and opening new avenues for product development. Offers sustainable impact and circularity – transforms agricultural waste into durable, recyclable materials through a green, chemical-free process, reducing landfill waste and carbon emissions. Cost-effective and scalable – utilises abundant, low-cost feedstock to deliver competitively priced, high-quality alternatives that reduce dependence on virgin raw materials. Versatile applications – provides customizable, high-performance materials suitable for diverse building and construction uses, enhancing both design flexibility and functionality. green building, materials, sustainable, chemical free, composite, agricultural valorisation, valorisation, circular economy, sustainability, eco-friendly, building materials, recycled material Materials, Composites, Sustainability, Circular Economy

Rising energy consumption and electricity costs pose significant challenges for businesses across all sectors, from light commercial operations to heavy industries. Moreover, sustainability has become a crucial component of corporate strategy. Electrical energy optimisation is not only about cost savings but also about resource conservation, power stability, equipment protection, and long-term sustainable development, making electrical energy saving a strategic priority for modern enterprises. The technology owner has developed a transformer-based voltage optimisation solution to reduce energy consumption and billing costs, optimise electrical power supply, extend equipment lifespan, and lower carbon emissions. This technology allows electrical equipment to run at an optimal voltage level while keeping the current within the optimum range for best efficiency, providing an immediate and practical way to reduce consumption and deliver electrical energy saving results. Industrial Internet of Things (IIoT) is integrated within the equipment to capture data and users have 24/7 access to a cloud-based platform to monitor, evaluate and make informed decisions on their power and energy usage as well as perform carbon reporting. The technology owner is keen to collaborate with industrial partners such as building management, property owners, industrial facility management in manufacturing sectors, equipment builders, energy consultants etc. The technology is also available for licensing to OEM partners to further co-develop by integrating into building management systems (BMS) and other solutions. Key features of this solution include: High efficiency of over 99% with minimal inherent consumption and losses 6–12% reduction in power consumption and electricity bill Improve the quality of overall electrical power supply IIoT-enabled, with integrated smart sensors and cloud-based data communication Real-time remote energy monitoring, analysis, and evaluation via a 24/7 on-demand platform Compact design with a less than 0.72m2 footprint (space-saving) Easy to install Customisable capacity Low maintenance requirements The digital voltage optimisation system is applicable for both commercial and industrial applications, especially industrial sectors with energy intensive equipment like motors, heating and cooling apparatus. The potential applications include but are not limited to: Commercial buildings (hotels, shopping malls, supermarkets, office buildings, restaurants, etc) Industrial facilities (factories, warehouses, chemical plants, fabrication plants, cleanrooms, etc.) Other infrastructure (airports, hospitals, MRT train stations, sports complexes, institutes, etc.) The patented technology offers the following unique features: Delivers power metrics to a dedicated platform for monitoring and reporting Short ROI period of 18–24 months Improves overall electrical system efficiency Increases electrical equipment lifespan Reduces electrical bills without affecting operations Lowers carbon footprint towards Net-Zero target Energy efficiency, Reduce energy consumption, Lower carbon emissions, Sustainability, Voltage optimization Energy, Sensor, Network, Power Conversion, Power Quality & Energy Management, Electronics, Power Management, Sustainability, Low Carbon Economy

With the rapid growth of electric vehicles, renewable energy storage, and high-power electronics, the demand for reliable battery thermal management systems (BTMS) is surging. Effective Li-ion battery thermal management is becoming increasingly critical as higher intensify risks of overheating, safety hazards, and reduced lifespan, underscoring the need for advanced cooling solutions. To address these challenges, a novel fabrication technique has been developed to produce a flexible, leak-proof, thermally conductive, and electrically insulating composite. This material combines a polymer matrix, phase change material (PCM), and thermally conductive fillers. Unlike conventional approaches and passive cooling methods, the technology employs a low-temperature solvent evaporation process using styrene-butadiene-styrene (SBS), paraffin (PA), and expanded graphite (EG), resulting a thermally enhanced flexible composite phase change material (FPCM) designed for external thermal management of Li-ion batteries. This process enables improved dispersion, strong interfacial compatibility, and structural integrity while significantly reducing energy consumption during fabrication. The optimized FPCMs demonstrate enhanced thermal conductivity (up to 1.38 W/m·K), robust flexibility under mechanical deformation and excellent phase change stability. Thermal performance tests on lithium-ion batteries under various charge–discharge conditions showed up to 17 °C reductions in peak battery temperature and improved capacity retention at high C-rates, further validating its advantages for Li-ion battery thermal management in demanding environments. It proved the FPCM’s reliability, scalability, and energy efficiency for advanced BTMS applications, particularly in environments demanding mechanical adaptability and high safety standards. The technology is available for R&D collaboration, licensing, and test-bedding with industry partners such as battery manufacturers, suppliers, and BTMS system integrators. First-of-its-kind fabrication of flexible, leak-proof, and thermally conductive composites by integrating polymer matrices, PCMs, and thermal conductive fillers Solvent-based mixing and evaporation process ensures uniform component dispersion, optimized thermal conductivity, and electrical insulation properties Encapsulation of PCMs within flexible polymer matrix with thermally conductive fillers, achieve leak-proof functionality even during phase transitions Scalable method to produce thin-film composites with superior thermal performance, durability, and flexibility, offering a versatile thermal management solution The technology can be applied to a wide range of thermal management systems, including: Energy storage and Li-ion battery cooling for electric vehicles (EVs) and hybrid vehicles High-power semiconductor devices (e.g. motor controllers, motor housings, power electronics) Consumer electronics and avionics requiring compact, safe thermal solutions Data centres for high-performance / AI servers Fuel cells and other advanced energy systems requiring indirect cooling methods Developing PCMs that are simultaneously leak-proof, flexible, and highly thermally conductive has long been a challenge. Conventional approaches typically focus on either encapsulation to prevent leakage or additives to improve conductivity but seldom succeed in combining both in one system. This innovation addresses the gap by delivering: Leak-proof encapsulation within a flexible polymer matrix, maintaining structural integrity during phase transitions and under mechanical stress Improved thermal conductivity gradients vis thermally conductive fillers, overcoming the inherent low conductivity of PCMs A unique combination of flexibility, leakage prevention, and high thermal efficiency, making it ideal for demanding applications Li-ion batteries, Battery thermal management, Flexible Phase change materials, External thermoregulation, Passive cooling Materials, Composites, Energy, Battery & SuperCapacitor, Electronics, Power Management

This technology is an AI-powered logistics orchestration platform designed to optimise global logistics management, warehouse operations, order fulfilment, and transportation across distributed networks. It integrates advanced algorithms for demand forecasting, route optimisation, and real-time inventory visibility. By connecting multiple warehouse operators and transportation providers into a unified system, the platform enables businesses to access flexible, on-demand logistics capacity without the need for owning physical assets. The system is built with modular APIs, allowing seamless integration with e-commerce platforms, ERP systems, and third-party logistics providers. Its scalable architecture supports rapid deployment in diverse market environments, making it suitable for businesses facing seasonal demand fluctuations or seeking cross-border operational efficiency. With its advanced capabilities, the platform strengthens global logistics management strategies and supports companies looking to enhance efficiency and resilience in their supply chains. AI-Driven Forecasting: Machine learning models analyze historical sales, promotions, and market trends to predict demand with high accuracy. Dynamic Fulfilment Routing: Automated allocation of orders to optimal fulfilment centers based on location, capacity, and cost parameters. Real-Time Inventory Synchronization: Continuous data updates across multiple warehouses to maintain accurate stock levels. Multi-Modal Transport Coordination: Integration with domestic and cross-border carriers, enabling flexible transport modes (road, air, sea). API-First Architecture: Supports plug-and-play integration with ERP, WMS, OMS, and e-commerce platforms. Scalable Cloud Infrastructure: Handles high transaction volumes with robust uptime and disaster recovery protocols. Analytics Dashboard: Centralized interface for monitoring KPIs, delivery performance, and operational bottlenecks. E-commerce fulfilment for domestic and cross-border markets Omnichannel retail distribution networks 3PL coordination platforms Reverse logistics and returns management SME access to on-demand warehousing capacity This technology delivers asset-light, AI-driven logistics orchestration that enables businesses to flexibly access and optimize warehouse and transportation resources across a distributed network—without owning physical assets. Key differentiators include: Network-Orchestrator Model – Connects multiple independent logistics providers into a unified, real-time network. Dynamic, AI-Powered Allocation – Routes orders to optimal fulfilment centers and transport modes based on cost, location, and capacity. Seamless API Integration – Designed to integrate quickly with ERP, WMS, OMS, and e-commerce platforms, reducing deployment time and IT overhead. Scalable, Pay-Per-Use Structure – Allows businesses to expand or contract logistics capacity instantly, ideal for seasonal demand or market entry strategies. Border Capability – Built for both domestic and cross-border trade, supporting multi-modal transport coordination and customs-ready workflows. Unlike conventional warehouse or transport management systems, this platform acts as a logistics network orchestrator, enabling businesses to dynamically access, allocate, and optimize logistics resources across multiple independent providers. It eliminates the need for fixed contracts or owned facilities, offering a pay-per-use model supported by AI-driven decision-making. This ensures cost efficiency, operational flexibility, and scalability—critical factors for fast-moving consumer industries and global trade players. Infocomm, Artificial Intelligence

Conventional solar monitoring at the inverter level is reactive and labour-intensive, with issues like shading, soiling, mismatch, or degradation often detected only after energy losses occur. Troubleshooting requires manual checks, slowing response times and driving up costs, which limits the efficiency of solar asset management for large-scale operations. This technology provides a digital O&M control panel that delivers real-time, module-level visibility and control for advanced solar asset management. Coupling module-level power electronics with advanced software, it captures second-by-second data on voltage, current, temperature, and faults from each module. The platform integrates with existing inverter and SCADA systems, is inverter-agnostic, and can be retrofitted selectively where risks or losses are the highest. By detecting anomalies early, quantifying avoided losses, and prioritising interventions by ROI, the technology turns monitoring into proactive operations. Operators can execute remote module-level actions, such as isolating or restoring modules - before sending crews, reducing downtime and cost. Built-in safety features also meet rapid shutdown requirements and generate auditable compliance records to strengthen long-term energy performance. By closing the loop from sensing to analytics to remote action, this technology maximizes energy yield, accelerates response, and lowers the total cost of solar plant operations. In real-world deployments, the system has achieved up to a 50% reduction in management and O&M costs, and a 4–15% increase in overall power generation efficiency, while significantly strengthening fire-safety assurance through rapid isolation of faulty panels or hotspots for improved energy reliability. The technology owner is seeking collaborations with asset owners, O&M service providers, and EPCs/developers for test-bedding and licensing. Smart Module devices: Real-time module data capture, per-module optimization, and rapid shutdown for safety and efficiency. Connected edge network: Low-power mesh links modules to an on-site gateway, which securely aggregates and normalizes data. The gateway supports Ethernet/LTE backhaul for reliable connectivity, enables remote diagnostics, and delivers over-the-air firmware updates. Digital O&M platform: Module-level visualization, anomaly detection, automated workflows, remote control, and audit-ready logs—transforming monitoring into proactive operations. Solar EPCs & Developers: Improve system bankability at shade-affected or complex sites and reduce post-commissioning performance risk. O&M Service Providers: Enable ROI-based task prioritization, remote interventions, and verifiable reporting while reducing on-site maintenance visits. Insurers: Leverage verified performance and fault data to support cleaner claims, lower loss severity, and enable risk-based premiums. Asset Owners & Investors: Strengthen yield reliability, reduce operational risk, and enhance long-term asset value and investor confidence. Closed-Loop Digital O&M: Transforms intelligent electronics—whether proprietary or third-party—into a unified control plane to sense, analyse, act, and verify in real time. Automated, ROI-Driven Operations: Executes predefined O&M workflows (thresholds, triage, remote actions, dispatch, escalation) and prioritizes tasks by avoided energy loss or financial impact. Remote Optimization & Control: Enables operators to isolate or restore affected zones, apply targeted performance tuning, and verify fixes remotely, minimizing site visits and downtime. Continuous Learning & Improvement: Built-in measurement and verification (M&V) tools learn across sites and auto-refine O&M rules for sustained yield enhancement. Hardware-Agnostic & Scalable: Integrates with existing inverters and SCADA systems, supporting selective retrofit deployment where justified. Quantified Impact: Proven to achieve 4–15% higher power generation, up to 50% reduction in O&M costs, and enhanced fire safety through rapid fault isolation and compliance-ready shutdowns. Energy, Solar, Sustainability, Low Carbon Economy

Enterprises today face mounting challenges from legacy systems, fragmented data silos, and complex integration issues that slow down digital and AI initiatives. This AI-powered automation platform transforms integration from a technical bottleneck into a strategic accelerator, enabling organizations to unlock trapped data assets worth billions. By automating up to 70% of manual coding, the platform accelerates processing speeds by up to 10x while reducing operational costs. Its visual drag-and-drop interface democratizes data access, addressing the $5.5 trillion global skills gap by removing the need for specialized coding expertise. Enterprises can cut data preparation efforts from 80% to 20% of project cycles, connecting legacy mainframes seamlessly with modern cloud applications. The urgency is clear: the data integration market is projected to reach $47.6 billion by 2034, yet 95% of IT leaders cite integration as the main barrier to AI adoption. Meanwhile, silos cost enterprises hundreds of thousands annually, and up to 80% of data projects fail due to poor preparation. This platform empowers organizations to process millions of records in minutes across hybrid, cloud, and on-premises environments. Early adopters already report 171–295% ROI within three years, six-month payback periods, and over $2.4 million in productivity gains. With 70% of new applications expected to leverage low-code/no-code by 2026, this solution positions enterprises to lead the next wave of intelligent automation. 1. Low-code visual interface — drag-and-drop workflow designer for ETL (Extract, Transform, Load) without heavy coding. 2. Broad connectivity — supports diverse data formats and protocols for integration with: Legacy mainframe systems (IBM IMS, DB2, VSAM, CICS) Modern databases Cloud services APIs IoT devices 3. Flexible deployment options — on-premises, private cloud, public cloud, or hybrid; containerized on Kubernetes for easy scaling and management. 4. Unified real-time computing architecture — includes: Event message storage Operational logic management Built-in data monitoring Real-time statistical computation 5. Processing modes — supports both batch and streaming data processing for near real-time synchronization. 6. No-code API generation — instantly create RESTful APIs without microservices coding. 7. Multi-API integration — combine outputs from multiple third-party APIs in a single workflow. 8. Automated data format conversion — convert JSON, XML, CSV, and other formats without custom scripts. 9. Built-in debugging console — instant result checks and error tracking to speed up development. 10.Centralized monitoring & alerting — end-to-end oversight of integration pipelines, infrastructure, and app performance. 11. Lightweight, high-throughput — typical unit requires 2 vCPU + 4GB RAM, capable of processing millions of records in minutes. 12. Enterprise-grade resilience — scalable, secure, and compliant with regulatory and operational requirements. The technology provider is seeking partners with multinational corporations, enterprises, and system integrators to transform integration from a technical bottleneck into a strategic enabler, delivering scalable, secure, and compliant solutions that accelerate digital transformation and data-driven decision-making. 1. Banking & Financial Services Modernises legacy core banking systems by integrating mainframe and cloud data. Automates ETL workflows for compliance, reporting, and AI-driven fraud detection. Reduces operational costs and shortens reporting cycles. 2. Healthcare Unifies patient, lab, and imaging data from multiple systems for holistic care. Enables real-time alerts and analytics for faster clinical decisions. Supports paperless workflows for patient onboarding and records management. 3. Telecommunications Connects customer, billing, and network data from disparate platforms. Enables real-time service monitoring and customer experience optimisation. Reduces integration time for mergers, acquisitions, or system upgrades. 4. Manufacturing Integrates shop-floor IoT, supply chain, and ERP systems. Enables predictive maintenance, quality control analytics, and production optimisation. 5. Government & Public Sector Consolidates siloed departmental databases for unified citizen services. Automates reporting for compliance, ESG initiatives, and budget monitoring. 6. Cross-Industry Applications Real-time data synchronisation between legacy and modern systems. Low-code API generation to quickly integrate new applications. Hybrid cloud deployment for flexible, secure data operations. 7. Agritech / Smart Farming Automates data collection from IoT sensors (soil moisture, weather, crop health). Processes and integrates sensor, drone, and satellite data in real time. Enables precision agriculture—optimised irrigation, fertiliser use, and pest control. Supports predictive analytics for yield forecasting and early issue detection. Rising Digital Transformation Demand – Enterprises urgently need agile, low-code data platforms to modernize infrastructure and accelerate innovation. Hybrid Cloud & Legacy Integration Gap – Strong demand for solutions bridging mainframes, cloud, APIs, and IoT in a seamless, cost-effective way. AI & Analytics Growth – Timely, integrated data is now a critical enabler for AI adoption and real-time decision-making across industries. Talent Shortage in Legacy Systems – Scarcity of mainframe/ETL specialists drives adoption of low-code tools that reduce technical dependency. Cost & Efficiency Pressures – Enterprises seek platforms that cut IT spend while delivering faster deployment and operational savings. A versatile solution that powers AI, advanced analytics, and digital transformation across diverse sectors, including finance, healthcare, telecom, manufacturing, agritech, and beyond with many UVPs; here are the top five: Significant Cost Savings – Reduces total cost of ownership by up to 90% compared to traditional ETL/data tools. Unified Data Access – Connects legacy mainframes, modern databases, cloud apps, APIs, and IoT into one seamless platform. Low-Code Speed – Drag-and-drop workflows cut development effort by up to 80% and deliver deployment in days. High Performance, Low Resource – Processes millions of records in minutes with minimal hardware (2 vCPU, 4GB RAM per unit). Near Real-Time Insights – Enables faster, data-driven decisions with clean, integrated data for AI and analytics. Low-Code ELT, Data Processing & Integration, Visual Workflow Automation, Legacy System Modernization, Hybrid Cloud Deployment Infocomm, Enterprise & Productivity, Internet of Things, Healthcare ICT, Logistics, Value-Added Services