Device Engineering Custom Firmware Development for Low-Power Vision Devices Client Background One of the top manufacturers of low-power vision devices for remote monitoring applications in the security, IoT, and agricultural sectors is our client. Their products are deployed in energy-constrained environments where long battery life and consistent performance are essential. These vision devices required efficient firmware to handle image processing tasks while consuming minimal power. With a focus on innovative technology and sustainability, the client sought a firmware solution to meet their specific performance needs. The devices required advanced image processing capabilities without sacrificing energy efficiency. Challenge The challenge was to develop custom firmware for low-power vision devices, enabling real-time image processing while maintaining extended battery life. The devices were required to function in remote and energy-limited environments, which meant power consumption needed to be minimized without compromising performance. Additionally, the firmware needed to integrate seamlessly with the existing hardware, ensuring smooth operation across various device models. The solution also had to be scalable, as the devices would be deployed in diverse, dynamic environments with varying conditions. Optimizing the trade-off between energy efficiency and processing speed was the primary hurdle in achieving a viable solution. Our Solution We developed custom firmware optimized for low-power vision devices, ensuring high-performance image processing with minimal power consumption. Energy-Efficient Algorithms: Implemented algorithms specifically designed to minimize energy consumption while delivering high-quality image processing. This enabled devices to operate longer on a single battery charge, enhancing overall device longevity. Real-Time Processing: Integrated efficient image processing methods that provided real-time analysis without causing significant power draw. The firmware maintained fast processing speeds to meet real-time monitoring demands, ensuring no delays in critical applications. Hardware Optimization: Tuned the firmware to the client’s hardware specifications, enhancing device performance while ensuring compatibility and stability across different models and environments. This helped maintain optimal performance even in varying operational conditions. Scalable Solution: Designed the firmware to be scalable, allowing easy adaptation for future device versions or increased processing demands without needing a complete redesign. This flexibility ensured that the solution could evolve with the client's growing needs. Seamless Integration: Integrated the custom firmware with the existing software ecosystem, allowing for smooth device operation, remote monitoring, and effortless updates. This streamlined the deployment process and reduced potential integration challenges. Outcome The custom firmware improved the performance and energy efficiency of the client’s vision devices, enabling them to operate optimally in energy-constrained environments. Extended Battery Life : The firmware significantly reduced power consumption, allowing devices to run for extended periods without needing frequent recharges or battery replacements. This led to a substantial decrease in maintenance and operational costs. Enhanced Real-Time Monitoring : The devices provided real-time image processing and monitoring, ensuring timely insights for applications like security and remote sensing. This enhanced the client’s ability to respond to incidents quickly and efficiently. Improved Device Reliability : By optimizing the firmware, the devices became more reliable, even in challenging conditions, ensuring consistent performance without downtime. This increased the trust in the technology and its applications. Cost Savings : Longer battery life and optimized processing reduced operational costs, particularly in remote areas where frequent servicing would be costly and impractical. The solution also reduced the total cost of ownership for the client. Future-Ready Solution : The scalable nature of the firmware allowed the client to easily upgrade or expand their product line without reengineering the core software. This gave the client a competitive edge by enabling them to keep up with technological advancements.

Product Engineering Financial Firm Upgrades Legacy System for Growth and Scalability Client Background: The client, a financial company that specializes in wealth advisory, transactional, and investment management services. Operating for over 20 years, the firm relied on a legacy system that had become increasingly difficult to maintain and scale. Initially designed to manage financial transactions, reports, and client data, the system had grown obsolete with the firm’s expansion. The firm faced growing demands for real-time data processing, enhanced security, and the ability to integrate with emerging technologies. The need for a modernized infrastructure became critical to remain competitive in a quickly evolving industry. Challenges: Large technical debt, inadequate performance, and an inability to grow effectively were the main problems with the company's legacy system. Operating inefficiencies grew as the system was unable to keep up with the expanding demands of the company. This resulted in slower transaction processing, more frequent system outages, and trouble integrating new features. Security flaws caused potential compliance issues, and manual procedures resulted in high operational costs. The business required a thorough modernization plan that would satisfy modern industry requirements, support expansion, and preserve system stability. Our Solutions: We combined code refactoring with the integration of modern DevOps practices to manage the client’s technical debt. Code Refactoring: We systematically revamped the outdated codebase to improve performance and maintainability. The process included removing redundant code, optimizing workflows, and making the system modular to facilitate easier updates and improvements in the future. DevOps Integration: We introduced DevOps practices, including continuous integration and continuous delivery (CI/CD), to automate and streamline the development and deployment process. This significantly improved the efficiency of system updates and reduced human error. System Stabilization: We focused on addressing legacy bugs and performance bottlenecks to stabilize the system. Performance optimizations were implemented to improve response times and ensure reliability during high-traffic periods. Scalability: The system’s architecture was redesigned to support scalability. We adopted microservices, enabling the firm to easily scale infrastructure in response to growing transaction volumes without disrupting core services. Ongoing Maintenance: A continuous monitoring system was put in place to track system performance and proactively identify issues before they become critical. This approach ensured that the system remained stable and efficient over time. Team Collaboration: Throughout the modernization process, we fostered close collaboration between the client’s IT, operations, and business teams. This partnership helped align technical efforts with the firm’s broader strategic goals and produced faster decision-making and improved problem-solving. Outcomes: Our solution significantly improved the firm’s operational capabilities, stabilized the system, and positioned it for future growth. Increased Efficiency : Modernized development processes and automated testing and deployment caused quicker system updates and reduced manual maintenance efforts. Reduced Downtime : The integration of monitoring and automated deployment resulted in fewer system outages, ensuring greater service availability and reliability. Faster Time to Market : With the DevOps approach, new features and updates were deployed more quickly, enhancing the firm’s ability to respond to market changes and customer demands. Scalable Infrastructure : The new system architecture enabled the firm to handle increasing transaction volumes and integrate new technologies without significant system reconfigurations. Ongoing Growth : The firm is now in a strong position to scale its operations in line with future business requirements, with a flexible system that can easily accommodate new features, security upgrades, and regulatory changes. Improved Collaboration : The modernization process fostered better teamwork, facilitating more efficient issue resolution and continuous system improvements across teams.

Data Engineering EdTech Platform Elevates Learner Experience Using Real-Time Analytics Client Background: Offering individualized and flexible learning solutions to students worldwide, our client is a top EdTech provider. Diverse learning styles, interests, and educational objectives can be accommodated by the platform's extensive catalog of online courses covering a wide range of topics. The platform's user base, which includes students from a wide range of educational and cultural backgrounds, has grown significantly over time. The client requires a system that can use data analytics to improve educational results and student engagement while delivering individualized learning experiences at scale. The platform hopes to improve academic achievement across its worldwide user base by dynamically adapting course content through greater insights into learner behavior. Challenges: The platform faced several challenges in optimizing the learner experience. Learner data was dispersed across multiple systems, which made it difficult to access and analyze efficiently. Without real-time analytics, the platform struggled to provide immediate feedback on student performance, preventing the learning process. Additionally, the absence of actionable insights caused generic learning paths that couldn’t cater to individual student needs, resulting in lower engagement. This lack of dynamic content adjustments based on real-time data further impacted student participation. Moreover, the platform lacked a systematic system to analyze student behavior, which limited its ability to make data-driven decisions for course content updates and improvements. Our Solutions: We implemented a real-time analytics solution to provide immediate insights into learner progress and optimize content delivery, ensuring a more personalized and efficient learning experience. Real-Time Data Processing: Data from all learner interactions was aggregated and analyzed in real time, enabling instant access to progress metrics and performance trends. This allowed the platform to continuously adapt to the evolving needs of the students. Personalized Learning Paths: The system automatically adjusts learning content based on individual progress, preferences, and performance, ensuring a customized experience for each student. This customization helped keep students engaged and motivated. Instant Feedback Mechanisms: Learners received immediate feedback on assignments and quizzes, enabling them to identify areas for improvement quickly. This timely feedback created a more responsive and interactive learning environment. Engagement Monitoring: The platform tracked engagement metrics in real time, allowing for dynamic course adjustments to maintain student interest and motivation. This feature ensured that content remained relevant and aligned with student needs. Advanced Reporting and Dashboards: A user-friendly dashboard provides instructors with a comprehensive overview of learner performance, helping them make informed decisions to improve outcomes. The real-time insights also enabled instructors to adapt their teaching strategies quickly. Outcomes: The implementation of real-time analytics transformed the learner experience, leading to improved engagement, personalized learning, and measurable academic success. Enhanced Personalization : Learners received content specific to their needs and progress, resulting in a more engaging and relevant learning journey. This helped improve overall student satisfaction and retention. Improved Student Engagement : With dynamic content updates and real-time feedback, student participation and motivation significantly increased. Students felt more connected to their learning process and were more likely to stay engaged. Faster Intervention : Instructors were able to identify struggling students more quickly and provide timely support, preventing potential dropouts. This proactive approach ensured students received the help they needed to succeed. Data-Driven Decisions : The analytics platform enabled the platform to make data-driven adjustments, continually improving course content and delivery. These insights created a more effective and responsive curriculum. Increased Retention Rates : As a result of improved engagement and personalized learning experiences, student retention rates saw a significant boost, helping the platform grow its user base. This contributed to the platform's long-term success and growth.

Camera Engineering LTE and Wi-Fi-Based Wireless Camera for Fleet Monitoring Client Background: The client, a leading fleet management company, operates an extensive vehicle network nationwide. With expertise in logistics and transportation, they prioritize safety, operational efficiency, and real-time tracking. To address growing operational needs, the company required an advanced solution for enhanced fleet monitoring and security via real-time video surveillance. They aimed to achieve high-quality video feeds and reliable connectivity to support timely, data-driven decisions. Challenges: The client faced significant difficulties in achieving real-time visibility into the status of their fleet. Unstable video transmission, especially in areas with poor network coverage, disrupted monitoring and delayed decision-making. Existing systems often experienced streaming delays, reducing their ability to respond quickly to security incidents or operational issues. Additionally, managing video data across varying mobile networks (LTE and Wi-Fi) was inefficient, with challenges in maintaining consistent quality while minimizing data usage. These limitations hindered their ability to monitor their large, distributed fleet effectively. The client sought a comprehensive solution to overcome these issues, ensuring continuous connectivity, consistent video quality, and efficient fleet monitoring. Our Solutions: We provided a modernized and scalable solution that addressed the client's connectivity and video monitoring challenges: Dual Network Connectivity: By implementing a hybrid solution that utilized both LTE and Wi-Fi, we ensured uninterrupted video streaming. The system intelligently switched between networks based on availability, providing seamless connectivity and optimized reliability for fleet monitoring, even in areas with weak signals. Local Video Processing: The cameras were enhanced with edge computing capabilities to process video data locally. This reduced bandwidth dependency and enabled faster processing while ensuring sensitive footage remained secure by minimizing transmission risks. Adaptive Streaming: An intelligent streaming system was developed to automatically adjust the video resolution based on available bandwidth. This feature maintained consistent video quality, reduced data usage, and ensured smooth video streaming in areas with fluctuating signal strength. Cloud-Based Monitoring Dashboard: We built a centralized dashboard for fleet managers, enabling real-time access to live and recorded video feeds. This platform also offered advanced analytics and alerts, helping managers make informed decisions quickly and efficiently. Scalable Infrastructure: Our solution was designed to grow with the client's fleet. The infrastructure could seamlessly accommodate additional vehicles and cameras, ensuring smooth scalability without requiring major system upgrades. Outcomes: The implementation of our solution led to substantial improvements in fleet management, security, and operational efficiency: Reduced Latency: With LTE and Wi-Fi integration, video transmission delays were significantly reduced, allowing near-instantaneous monitoring. This improvement facilitated faster responses to incidents and enhanced overall decision-making during critical operations. Consistent Video Quality: The adaptive streaming feature ensured high-quality video even in low-signal areas, improving the reliability of surveillance across various terrains and environments. Improved Operational Efficiency: Fleet managers were empowered to monitor real-time video feeds, optimize routes, and address driver behavior issues. These enhancements reduced inefficiencies, minimized delays, and improved overall fleet performance. Enhanced Security: Continuous, reliable video surveillance helped protect against theft, accidents, and unauthorized activities. Fleet managers could respond immediately to incidents, strengthening overall security measures. Seamless Scalability: The flexible design of the system allowed the client to expand their fleet monitoring capabilities effortlessly. This ensured cost-effective growth and sustained performance, even as the fleet size increased over time.

Artificial Intelligence Optimizing Supply Chain Operations with AI-Driven Forecasting Client Background: A leading global retail chain operates a vast network of suppliers, warehouses, and distribution centers. Serving millions of customers daily, it manages a diverse catalog of products across multiple regions. The company faced increasing challenges due to fluctuating demand patterns influenced by seasonal shifts, market trends, and regional preferences. With growing complexity in its operations, it looked for a data-driven solution to align demand with supply more effectively while improving overall efficiency. Challenges: The client struggled with inefficiencies in demand forecasting, inventory management, and logistics planning. Traditional methods failed to adapt to dynamic market conditions, leading to overstocking, stockouts, and increased operational costs. Inefficient inventory management escalated storage expenses while missed sales opportunities hurt revenue. Procurement delays and poor supplier coordination disrupted replenishment schedules, creating shipment delays that frustrated customers. Additionally, managing supply chain complexities across diverse regions underscored the need for an intelligent and scalable solution to support growth and evolving business requirements. Our Solutions: We implemented a custom-built artificial intelligence-based forecasting platform designed to enhance supply chain decision-making. Accurate Demand Prediction: The platform used advanced AI models to analyze historical sales data and external variables like market trends, providing actionable insights into future demand. This allowed the client to make timely adjustments to their procurement and production strategies. Streamlined Inventory Management: The system identified optimal stock levels, reducing unnecessary holding costs and ensuring products were always available where needed. It also offered immediate alerts for inventory adjustments to avoid disruptions. Real-Time Supplier Integration: A unified platform enabled seamless communication with suppliers, facilitating faster replenishment and improved stock availability. This ensured suppliers had sufficient lead time to fulfill orders efficiently. Localized Market Insights: AI algorithms analyzed seasonal and regional trends, allowing the client to adapt stock levels and assortments to meet specific market demands. These insights helped the client customize offerings for different regions. Scalable Architecture: The solution was designed to grow with the client, accommodating expanding operations and increasing product diversity without disruption. It supported integration with new tools and technologies for future improvements. Outcomes: The AI-based forecasting platform transformed the client’s supply chain by addressing the main obstacles and delivering real benefits. Enhanced Planning: The client gained accurate demand forecasts, enabling them to align production and inventory with actual customer needs. This improved their ability to anticipate and prepare for market fluctuations. Optimized Stock Levels: Inventory was maintained efficiently, reducing waste and ensuring the availability of critical products at all times. This contributed to significant savings in operational costs. Improved Customer Experience: On-time deliveries became more consistent, leading to better customer satisfaction and loyalty. Positive feedback from customers also strengthened the brand’s reputation. Operational Efficiency: Automated forecasting processes reduced the time required for planning, freeing up resources for strategic initiatives. Supply chain managers could focus on long-term goals rather than resolving day-to-day issues. Scalability and Flexibility: The platform supported the client’s expansion into new markets and product categories, ensuring smooth operations and long-term adaptability. Its scalability provided confidence for further growth initiatives.

OCR Revamping Insurance Claim Processing Client background: Our client is a major national insurance company specializing in personal and commercial insurance products. They provide health, vehicle, and home insurance services across the country. As their client base developed, they encountered difficulties in handling a significant amount of insurance claims. The manual claims processing approach resulted in considerable delays, mistakes, and increased operating expenses. Regami Solutions was contacted by the client to enhance their claims processing process. Regami had to figure out how to improve and expedite the procedure. Challenges: Given the growing volume and complexity of claims, the client's manual insurance claim processing system was proving to be unsustainable. The lack of automation led to delays, frequent errors, and rising operational costs as data had to be manually extracted from various claim formats. To fix these issues, the client required an extensive solution that could eliminate human interaction, improve data quality, and speed up the claims processing cycle. Regami Solutions was tasked with implementing an advanced technology solution that would effortlessly integrate with their existing infrastructure and optimize claims processing efficiency. Our Solutions: Utilizing OCR technology, we deployed our own AI platform, Percepta, to speed up the client's insurance claim procedure. Automated Data Extraction via Percepta OCR : Percepta OCR facilitated the automatic extraction of critical data from a range of claim-related documents, such as forms, medical records, and invoices. This reduced manual data entry, minimized errors, and streamlined data capture, significantly enhancing processing speed and accuracy. Reduction in Processing Time: By automating data extraction and categorization, the solution accelerated claims handling, cutting down the time required for claim approvals and resolution, thus improving operational efficiency and expediting service delivery. Easy Integration with Existing Systems: Percepta OCR was integrated effortlessly into the client's legacy claims management systems, ensuring a smooth implementation process. This integration minimized system disruption and provided a swift transition to the automated solution, ensuring business continuity. Scalability for Increasing Claim Volume: The solution’s scalability allowed the client to efficiently manage growing claim volumes without the need for additional manual resources, ensuring operational agility and supporting business growth. Enhanced Data Accuracy and Reduced Errors: The Percepta OCR system significantly improved data accuracy by reducing manual data input errors. This resulted in a more reliable and consistent claims processing workflow, minimizing the need for manual corrections and improving the overall quality of data. Analytics for Informed Decision-Making: Percepta OCR provided actionable insights and performance metrics, enabling the client to track claim data, identify process inefficiencies, and make data-driven decisions to improve the overall claims management process. Outcomes: The implementation of Percepta OCR resulted in significant improvements in our client's claims processing operations: Significant Reduction in Claim Backlog: By automating the claims processing workflow, the client was able to significantly reduce the claim backlog, ensuring quicker resolution and fewer delays in processing pending claims. Increased Claims Throughput: With automated data extraction and categorization, the client saw an increase in the number of claims processed per day, improving overall throughput and enhancing operational efficiency. 30% Reduction in Operational Costs : Automation reduced the reliance on manual labor, leading to a 30% decrease in operational costs. This enhanced overall operational efficiency and contributed to long-term cost savings. Enhanced Customer Satisfaction: T he reduced claims processing time and higher data accuracy contributed to improved customer satisfaction, with faster and more accurate claim settlements driving higher levels of trust and loyalty. Scalable Solution for the Future: The solution provided the scalability necessary to accommodate increased claims volumes, allowing the client to grow their business without the need to invest in additional manual resources. Improved Compliance and Risk Management: The Percepta OCR system ensured that claims were processed in compliance with industry regulations, reducing the risk of errors and compliance violations and maintaining the client’s reputation within the industry.

Enterprise Platform Services Revamping the E-commerce Platform with CDN Integration Client Background: Our client owns a leading e-commerce platform providing various consumer products. Maintaining optimal platform performance became crucial with a quickly growing customer base and significant seasonal traffic spikes. The platform serves millions of customers globally, with a focus on providing an easy shopping experience. However, as their user base expanded, they faced increasing challenges with site speed and performance, particularly during high-demand periods like Black Friday and holiday sales. The client needed an optimized solution to improve site reliability and customer retention, especially during peak shopping seasons. Challenges : The e-commerce platform experienced significant performance issues, including slow load times and high bounce rates during peak seasons. These performance problems negatively impacted the user experience, leading to lost sales opportunities. As traffic increased, the system struggled to handle the growing number of visitors, leading to slow page loads and delayed transactions. Without addressing these issues, customer satisfaction and retention were at risk, particularly during critical sales events. The client faced mounting pressure to provide a seamless experience during high-volume shopping periods. Our Solutions: We implemented performance optimization strategies to improve site speed, scalability, and reliability during peak shopping seasons, ensuring a seamless shopping experience for customers. Performance Auditing: We conducted a comprehensive audit of the platform’s architecture to identify difficulties and areas that needed optimization, including server load times and database queries. This enabled us to target specific areas that were slowing down the platform. Content Delivery Network (CDN) Integration: We integrated a CDN to deliver static content faster by caching it closer to users, ensuring quicker load times for customers across the globe. This reduced the strain on the primary server during high-traffic times. Database Optimization: We optimized database queries and indexing to improve data retrieval speed, minimizing delays during high-traffic periods. This was important for ensuring that the platform could handle large volumes of transactions without lag. Scalable Cloud Infrastructure: We migrated the platform to a scalable cloud infrastructure, enabling the system to automatically adjust resources based on traffic fluctuations and maintain peak performance during high-demand periods. This provided the flexibility to scale up or down as needed. Front-End Optimization: We optimized the platform’s front end, reducing the size of assets like images and scripts and implementing lazy loading to improve page load times and overall user experience. This improved the visual performance and responsiveness of the platform. Outcomes: The performance optimizations resulted in faster load times, higher user satisfaction, and improved customer retention, especially during peak seasons, ensuring a competitive edge during high-demand periods. Reduced Load Times: The platform's page load times were significantly reduced, resulting in a smoother shopping experience and decreased bounce rates. Customers could now browse products faster, leading to increased engagement. Increased Scalability: The platform now automatically scales during high-traffic periods, ensuring seamless operation and preventing performance degradation during peak sales events. The system adjusted efficiently without manual intervention. Higher Customer Retention: With improved performance, customer satisfaction increased, leading to better retention rates, particularly during busy sales periods like Black Friday. Customers were more likely to return due to the positive experience. Improved Sales Conversion: Faster load times and a more responsive platform contributed to higher sales conversion rates, as customers were able to complete their transactions without delays. The improved checkout process resulted in fewer abandoned carts. Enhanced Brand Reputation: The improvements in site performance strengthened the brand’s reputation for reliability, building trust, and encouraging repeat business from customers. A faster, more dependable platform built stronger brand loyalty.

Explore Regami's Edge AI/ML solutions vision-based tech for real-time data processing, low-latency insights, and optimized performance on edge devices Home Vision Engineering Edge AI/ML Shaping Smarter Devices with Edge AI and ML Capabilities Enhance decision-making and optimize operations with our advanced vision-based Edge AI and Machine Learning solutions, delivering real-time intelligence and actionable data insights at low latency. Contact Us Today Login to Get Brochure Real-Time Object Detection for Edge AI Cameras in Smart Cities View Case Study Smart City Case study Energy-Efficient Edge AI Solutions for Retail Inventory Monitoring View Case Study Retail Case study AI-Powered Anomaly Detection for Industrial IoT Vision Systems View Case Study Robotics Case Study At Regami, we specialize in empowering industries with advanced vision-based Edge AI and Machine Learning solutions. Our services are tailored to bring intelligence to the edge, where critical data is captured and processed in real-time. From visual inspection systems that streamline quality assurance to object recognition and environmental monitoring for smart cities, our solutions enable efficient, secure, and scalable applications. Leveraging the latest AI advancements, we optimize edge environments to drive rapid insights and performance improvements across sectors including manufacturing, healthcare, and public safety. Our expert team provides solutions customized for robust, real-time processing, enhancing decision-making and operational precision in even the most demanding environments. Additionally, we offer specialized platforms for specific Edge AI/ML tasks, including OCR (Percepta), facial recognition (Vektor+), Iris recognition (Optiva+) and license plate recognition (Clarity+), ensuring optimized performance and accuracy for your unique requirements. Custom Edge AI/ML Solutions on Edge Devices Name* Email* Service Required* Service Required Short answer Schedule a consultation with our experts. Submit Edge AI/ML AI Strategy & Consulting Guiding businesses to develop robust AI strategies tailored to their specific needs, ensuring seamless integration and measurable results. Know More Edge AI/ML AI Enablement Design Crafting scalable frameworks and architectures to bring AI capabilities to life on edge devices, enhancing operational efficiency. Know More Edge AI/ML Custom AI Solutions Building bespoke AI models and applications that address unique business challenges with precision and adaptability. Know More Edge AI/ML Smart Vision Design Creating intelligent vision systems that enhance automation and decision-making in industries like manufacturing, healthcare, and retail. Know More Edge AI/ML Machine Learning & Analytics Leveraging machine learning algorithms to transform raw data into actionable insights for predictive analytics and smarter operations. Know More Edge AI/ML Large Language Model (LLM) Implementing advanced language models to enable natural language processing, document analysis, and conversational AI on edge devices. Know More Edge Applications Powered by Regami's Edge AI/ML Regami combines Edge AI/ML solutions with device engineering expertise, enabling intelligent, high-performance hardware tailored for diverse applications. Listed below are the applications that benefit from our Edge AI/ML services. Smart Surveillance Cameras Real-time object detection, vehicle detection and facial recognition ensure enhanced surveillance & intelligence. AGV & Drones Autonomous navigation and aerial inspections powered by AI-enabled vision systems. Industrial Robots Intelligent quality control and defect detection for precision manufacturing lines. Medical Imaging Devices On-device analysis for quicker diagnostics in resource-limited settings. ALPR Camera Systems Real-time license plate recognition for efficient vehicle tracking and automated access control. AI-Enabled Driver Monitoring Systems Advanced driver behavior analysis to enhance safety and reduce accidents with edge-based AI. Bridging Gaps in Edge AI/ML With Tailored Solutions Customized AI Strategies for Industry-Specific Needs We consult and develop tailored AI strategies that meet the unique demands of various industries, optimizing model performance and relevance in specialized applications. Integrating High-Performance AI on Edge Devices Our solutions involve AI enablement designs that bring advanced computing power to edge devices, balancing performance needs with resource limitations. Optimizing Vision Systems for Dynamic Real-World Conditions Our smart vision designs use adaptive algorithms that respond to environmental changes, ensuring consistent performance under varying lighting, movement, and weather conditions. Extracting Actionable Insights from Large Data Streams By employing machine learning and analytics models, we turn vast amounts of raw data into actionable insights, enabling real-time decision-making with minimal latency. Ensuring Privacy and Compliance in Visual Data Processing Our solutions ensure that sensitive visual data remains secure, with encryption and compliance features integrated into every stage of data handling on edge devices. Deploying High-Resolution, Real-Time Processing at Scale Our Large Language Models (LLMs) and advanced image processing methods are optimized for handling large, high-resolution data streams in real time without compromising on speed or accuracy. Smart City Analytics with Custom AI Models Regami collaborated with a smart city project to implement custom AI models for real-time analytics, transforming urban data into actionable insights with high precision and adaptability. View Case Study Edge AI Design for Retail Automation Regami developed an AI-enabled retail automation system that operates on lightweight edge devices, achieving efficient processing and immediate insights for inventory management and customer interactions. View Case Study Adaptive Vision System for Public Safety Monitoring Regami worked with a public safety organization to design a smart vision system that adapted in real time to changing outdoor conditions, improving detection accuracy in challenging environments. View Case Study Automated Data Analytics for Industrial IoT Regami partnered with an industrial IoT client to implement ML-powered analytics, facilitating real-time monitoring and decision-making for improved process control and efficiency. View Case Study Compliant Facial Recognition for Healthcare Access Control Regami provided a healthcare organization with a HIPAA-compliant facial recognition system, offering secure and private access control that safeguarded patient data. View Case Study Real-Time Adaptive Analytics for Smarter Transit Management Regami collaborated with a transportation agency to deploy a high-resolution, real-time analytics system, optimizing traffic flow and resource management across multiple locations. View Case Study Healthcare Provider Addresses AI Model Transparency Challenges Implementing explainable AI methods helped the healthcare provider gain regulatory approval. This increased trust in their AI diagnostics, ensuring compliance with industry standards and improving model transparency. View Case Study Regami's Software Platforms and SDKs Resources Regami Over-the-Air Meridian ONVIF Percepta OCR Nova Android App Authenta Video KYC Clarity+ LPR Dexter+ Barcode/QR Recognition Vektor+ Facial Recognition Optiva+ Iris Recognition Regami's Hardware Platforms Neurex Smart Camera Platform AI-enabling vision for edge processing and automation.  Innova GigE Camera Low-latency ONVIF GigE cameras with on-board storage & PoE. MerlinPlus USB2.0 UVC Camera USB 2.0 UVC camera with on-board storage & dual streaming. Wave WiFi Camera Low-latency ONVIF WiFi cameras with on-board storage. Armor SerDes Camera HDR cameras with GMSL2/L3 & FPD-Link III/IV technologies.  Falcon USB3.0 UVC Camera High-speed, high-performance USB 3.0 UVC camera. Bolt MIPI Camera AI imaging and vision processing accelerated by GPU.  Merlin USB2.0 UVC Camera USB 2.0 UVC camera for high-performance capture. Standard You Trust, Platforms You Rely On Certifications FCC CE UL ATEX ETL RoHS REACH SoC2 HIPAA Processing Platforms NVIDIA NXP MediaTek Raspberry Pi TI STM Espressif Wireless Platforms uBlox Sierra Nordic Laird Quectel Microchip SimCom Innovation Insights: Explore Our Latest Articles The Future of Edge AI: Transforming Industries Edge AI is revolutionizing industries with real-time data processing. This article examines its impact on manufacturing, healthcare, and transportation, enhancing efficiency and decision-making. Explore Edge AI Overcoming Challenges in Machine Learning Deployment Deploying machine learning models presents several challenges. This article identifies common obstacles and offers strategies for successful implementation. Discover ML Ensuring Data Security in Edge AI Applications With the rise of Edge AI, data security is crucial. This article shares best practices for securing Edge AI applications to protect sensitive data and ensure compliance. Secure AI Related Services Vision Engineering Device Engineering One-stop device engineering services for developing smart, connected IoT solutions, from design and prototyping to manufacturing. Know More Vision Engineering Camera Engineering End-to-end camera engineering solutions for design, calibration, and performance enhancement. Know More Vision Engineering Cloud AI/ML Expert engineering services for building, training, and deploying AI/ML models on cloud infrastructures. Know More Ready to Bring Your Ideas to Life? First name* Email* By submitting, you also agree to receive our newsletter. Submit

Edge AI Energy-Efficient Edge AI Solutions for Retail Inventory Monitoring Client Background: A large retail chain specializing in consumer electronics and household goods faced difficulties managing inventory across multiple locations. The company struggled with real-time stock monitoring, which caused frequent stockouts, overstocking, and inefficient replenishment processes. They were looking for a solution that could provide accurate inventory tracking with minimal operational disruptions. The retailer also aimed to lower energy costs and reduce their environmental footprint while maintaining high levels of operational efficiency. Given the scale of their operations, they needed a solution that could be deployed across numerous stores and warehouses. Challenges: The client faced multiple challenges in maintaining inventory accuracy across their retail network. Traditional inventory management systems were reliant on centralized processing, which resulted in delays and inefficiencies. Additionally, these systems consumed significant amounts of energy, contributing to high operational costs. Effective stock level tracking was challenging due to the absence of on-site data processing, which prevented real-time inventory monitoring. The retailer also struggled with integrating new technologies into their existing infrastructure without disrupting daily operations. Finally, there was a growing need to implement more sustainable solutions to meet environmental goals. Our Solutions: We provided an energy-efficient edge AI solution that enabled real-time, on-site inventory monitoring, reducing both energy consumption and operational inefficiencies. Edge Data Processing : Our edge AI solution processes inventory data locally on-site, minimizing the need for centralized cloud processing and reducing energy consumption. This approach ensured faster data access, enabling quicker decision-making in real time. Predictive ML Insights : The system utilized machine learning algorithms to provide accurate, real-time inventory insights, improving stock management and minimizing human error. These insights also supported predictive analytics to forecast demand and optimize stock replenishment. Unified Integration: We ensured the edge AI solution seamlessly integrated with the retailer’s existing infrastructure, enhancing operational efficiency without disrupting business processes. This integration allowed for easy adoption across all store locations with minimal training required. Scalability: The solution was designed to scale across multiple store locations, providing consistent performance as the retailer expanded. With minimal adjustments, the solution could support both small stores and large distribution centers. Sustainable Technology: Our solution used energy-efficient hardware and optimized software to meet the retailer’s sustainability goals, reducing the environmental impact of their operations. The system also helped reduce the carbon footprint of the retailer’s overall operations by lowering energy demand. Outcomes: The energy-efficient edge AI solution significantly enhanced inventory accuracy and operational efficiency while supporting the retailer’s sustainability efforts. Reduced Energy Consumption: Local processing minimized the energy needed for inventory management, lowering operational costs. This reduction in cloud reliance further decreased the retailer’s overall energy consumption and operational expenses. Refined Inventory Tracking: AI-driven insights provided real-time updates, reducing stockouts and overstocking and ensuring better decision-making. This resulted in fewer lost sales and more efficient inventory turnover, improving the overall profitability. Enhanced Operational Efficiency: Streamlined operations allowed staff to focus on high-priority tasks, improving overall productivity. Automated inventory management freed up time for employees to engage in more value-added activities, driving customer satisfaction. Flexible System Expansion : The solution was designed for effortless rollout across various locations, ensuring uniform inventory management and performance consistency. This flexibility enabled the retailer to grow into new markets without major infrastructure modifications. Environmental Impact: By lowering energy consumption and carbon emissions, the retailer was able to meet sustainability targets thanks to the energy-efficient technology. This complemented the retailer's long-term sustainability goals and lessened its environmental impact.

Data Engineering Financial Institution Unifies Disparate Data Sources Client Background: A leading financial institution with operations spanning retail banking, investment services, and insurance products. The organization relied on multiple legacy systems and platforms to manage customer data, transactions, and compliance records. These systems generated large volumes of data that were stored in silos, preventing collaboration between departments. As they looked to expand their services, the client needed a unified data approach to drive efficiency and improve decision-making. Challenges: Significant difficulties in data management resulted from the institution's inability to integrate data from a variety of modern third-party platforms and outdated legacy systems. This inability to integrate seamlessly resulted in silos, where important data was segregated inside certain systems or departments. The absence of integration restricted access to insights, impeding cooperation and decision-making. Delayed data reporting impacted operational efficiency and obstructed the identification of key trends and opportunities. This ultimately resulted in missed opportunities for timely and accurate strategy development. They also required a solution that would comply with demanding financial regulations while ensuring scalability for future growth. Our Solutions: We implemented a unified data integration framework, breaking down silos and enabling seamless access to consolidated data. This approach ensured a cohesive data strategy, enhancing transparency and usability across all organizational levels. Centralized data platform: Built a centralized data warehouse to consolidate information from legacy systems and modern platforms. This unified structure ensured consistent access and reduced duplication. It also allowed for easier data retrieval and consistency across departments. Real-time ETL pipelines: Designed secure extract, transform, and load (ETL) pipelines to integrate data in real time, supporting accurate and up-to-date analytics. The pipelines were optimized to handle large data volumes without compromising performance. API integrations: Integrated third-party platforms through secure APIs, streamlining data exchange across diverse systems. This enabled the institution to connect with external services without manual intervention and maintain interoperability across platforms. Data governance framework: Established governance policies to ensure data integrity, security, and compliance with financial regulations. This included automated auditing and access control mechanisms to prevent unauthorized access. Interactive dashboards: Developed user-friendly dashboards with customizable views, enabling teams to analyze integrated data effortlessly and collaborate effectively. These dashboards provided actionable insights and reduced reliance on technical support for data visualization. Outcomes: The financial institution achieved a unified data ecosystem, improving decision-making and operational efficiency across departments. The integration also eliminated data silos, providing a single source of truth for the entire organization. Improved Data Access and Consistency : The creation of a centralized data warehouse eliminated data silos, providing teams with consistent access to accurate and unified information. This reduced duplication, improved data reliability, and enhanced collaboration across departments. Enhanced Real-time Analytics : The real-time ETL pipelines ensured continuous, accurate data integration, empowering teams with up-to-date analytics. This improved decision-making by providing real-time insights and handling large data volumes efficiently without sacrificing performance. Streamlined Data Exchange : Secure API integrations facilitated seamless data exchange between third-party platforms and internal systems. This automation reduced manual work, increased data accuracy, and ensured interoperability, streamlining workflows and enhancing operational efficiency. Strengthened Data Integrity and Compliance : The implementation of a robust data governance framework ensured the integrity, security, and compliance of the institution’s data. Automated auditing and access control mechanisms safeguarded sensitive information and maintained adherence to financial regulations. Empowered Data-Driven Collaboration : The development of interactive, customizable dashboards enabled teams to easily analyze integrated data and gain actionable insights. This reduced reliance on technical support and empowered users to make informed decisions and collaborate more effectively.

Device Engineering Ruggedized Enclosures for Industrial Vision Sensors in Extreme Environments Client Background The customer is one of the top producers of industrial vision sensors for use in vital applications like automation, surveillance, and quality control in industries like mining, oil and gas, and manufacturing. Their sensors are deployed in challenging environments where reliability and durability are paramount. With an expanding customer base and diverse industrial applications, they needed enclosures that could withstand the toughest conditions. They required a solution to protect their sensors from environmental hazards without compromising performance. The goal was to enhance the longevity and performance of these vision sensors in extreme settings. Challenge The client faced the challenge of ensuring that their vision sensors operated reliably in extreme industrial environments. These sensors were vulnerable to environmental hazards such as extreme temperatures, dust, moisture, and vibrations. Traditional enclosures did not offer the necessary protection against these harsh conditions. The client also needed a solution that could maintain sensor performance and longevity over extended periods in demanding environments. The rugged enclosures had to be designed to protect the sensitive components while ensuring uninterrupted operation in diverse settings. Finding a solution that balanced protection with sensor performance was a critical requirement. Our Solution We designed custom ruggedized enclosures that provided maximum protection for the client’s industrial vision sensors, ensuring reliable operation in extreme environments. Durable Materials: We used advanced materials like high-strength alloys and impact-resistant plastics to create durable enclosures that could withstand extreme temperatures and physical stress. These materials also offer long-lasting durability under continuous use in demanding industrial settings. Sealing and Protection: The enclosures were equipped with superior sealing to prevent dust, moisture, and contaminants from entering, ensuring the sensors remained operational even in harsh conditions. This protection also prevented sensor degradation, maintaining optimal performance over time. Vibration Resistance: The design incorporated shock-absorbing components to protect sensors from vibrations and impacts commonly encountered in industrial environments. This ensured that the sensors remained stable and accurate, even in environments prone to heavy machinery operation. Thermal Management: We included passive cooling and insulation features to maintain optimal sensor performance across a wide range of temperatures. These features ensured that the sensors operated within their thermal thresholds, preventing overheating or freezing in extreme conditions. Custom Fit and Integration: The ruggedized enclosures were customized to the specific needs of the client’s sensors, ensuring a perfect fit and seamless integration with the existing systems. This customization streamlined deployment and minimized any risk of incompatibility with other components. Outcome The custom ruggedized enclosures enhanced the performance and durability of the client’s vision sensors, enabling them to thrive in the most demanding industrial settings. Increased Sensor Longevity: The sturdy enclosures significantly reduced wear and tear, extending the lifespan of the sensors. This prolonged the time between replacements and minimized downtime, providing long-term reliability. Reliable Performance in Harsh Conditions: The vision sensors continued to perform accurately in extreme temperatures, vibrations, and environmental conditions. This allowed the client to trust their sensors in a variety of industrial applications without concerns about malfunctions. Reduced Maintenance Costs: The improved protection reduced the frequency of sensor failures, cutting down on maintenance and replacement costs. The enclosures’ durability also minimized service visits and repair times, resulting in cost savings. Seamless Deployment: The enclosures enabled the client to deploy their sensors across a wide range of industries, ensuring smooth operations without environmental concerns. This streamlined the deployment process and allowed the sensors to be used in multiple industrial applications efficiently. Enhanced Customer Satisfaction: The durable and reliable sensors resulted in improved customer satisfaction by meeting the operational demands of industries that require top-tier performance. The rugged solution bolstered the client's reputation for providing high-quality, dependable products.

Enterprise Platform Services ERP-Driven Growth: A Manufacturing Modernization Success Client Background: A mid-sized manufacturing company with a growing presence across North America managed multiple facilities catering to diverse customer demands. Their core operations included inventory management, order processing, procurement, and financial tracking, all handled through fragmented and legacy systems. While the company experienced consistent growth, its reliance on disconnected systems created difficulties in operations. Recognizing the need for modernization, the leadership team sought a scalable Enterprise Resource Planning (ERP) solution to unify their business processes, enable better collaboration, and support their expansion plans without compromising efficiency. Challenges: The use of manual inputs, which frequently resulted in mistakes and inefficiencies, interfered with the client's operations. Their departments operated in silos, each using disparate tools that made it challenging to consolidate information and implement a unified strategy. This fragmentation resulted in inconsistent data, undermining the accuracy of reports and insights necessary for informed decision-making. Manual workflows in key areas like inventory and order management caused significant delays, further straining operational efficiency. Furthermore, collaboration across teams was also limited due to the absence of centralized data access, creating barriers to effective communication and teamwork. Compounding these issues, the legacy systems lacked scalability, leaving the company unprepared to manage its sudden growth and risking future expansion opportunities. Our Solutions: We implemented a specific ERP solution that addressed their unique challenges by unifying their processes and delivering measurable improvements. Data Integration: A centralized database integrated all departments, ensuring everyone worked with consistent, up-to-date information. This simplified cross-departmental workflows and improved reporting accuracy. Automated Workflows: The ERP system automated repetitive manual tasks, such as inventory updates and order tracking. This reduced human errors and standardized processes across all locations. Real-Time Reporting and Insights: Customizable dashboards provide real-time analytics, empowering leadership to make informed decisions quickly and confidently. The system also highlighted critical performance metrics for faster action. Inventory Optimization: Advanced inventory management tools simplified stock tracking, minimized overstocking, and reduced stockouts. Predictive features also improved restocking efficiency. Scalable and Flexible Design: Built with scalability in mind, the ERP system could accommodate the client’s growth, adapting flawlessly as their operations expand. Outcomes: The deployment of the ERP solution had a transformative impact on the client’s operations, enabling significant improvements and setting the stage for future growth. Improved Data Accuracy: Centralized and integrated systems ensured consistent data across all departments, enhancing trust and reliability in reporting. Data consolidation also simplified compliance efforts. Faster Decision-Making: With readily available real-time insights, the leadership team was able to act swiftly on business opportunities and challenges, making decisions with greater confidence. Enhanced Employee Productivity: Automating routine tasks saves time and enables employees to focus on higher-value responsibilities, improving overall productivity. Team members report improved job satisfaction. Better Team Collaboration: The unified platform facilitated easy communication and collaboration, breaking down silos and improving teamwork across locations. Cross-functional projects became more efficient. Future-Proof Scalability: The new ERP system provided the flexibility to scale as the company grew, ensuring long-term operational stability. It was designed to support new features and integrations as needed.