KAISPE Announces New Features Updates for Quarter 2

Improved user experience, payment integration, and admin control across all platforms

Karachi, July 22, 2025 – KASIPE has announced the successful rollout of major product enhancements for Quarter 2, covering updates to the Vendor Portal, AutoRecruit, KPOD Solution, and now extended to additional modules including Customer Portal, Field Service, Purchase Requisition, Travel & Expense, and Time N Go. These changes bring smoother admin control, better mobile and multilingual support, and deeper system integration with Microsoft technologies.

“Our goal is to make life easier for users by giving them more control, faster tools, and smoother workflows. These updates are a big step in that direction.”— Imran Mahmood, CEO of KAISPE

Key Highlights by Product:

Vendor Portal – SRM

• New quote approval system for easier comparison and structured decision-making.
• Real-time notifications for vendors and internal teams.
• Improved APIs to support third-party integrations.
• Subscription updates:
• Stripe integration for invoice payments
• Admins can now upgrade users, downgrade plans, or cancel and switch to Free Plan

KPOD Solution – Proof of Delivery

• Automated email alerts at each stage of order delivery (created, dispatched, assigned, delivered)
• Stripe-enabled payments
• Self-service options for managing subscriptions (upgrade, downgrade, cancel)

AutoRecruit – E-Recruitment Portal

• Admins can apply on behalf of candidates
• Applicants get automatic confirmation emails
• Backend API improvements
• Subscription tools same as Vendor Portal: Stripe payments, upgrade/downgrade, free plan migration

Customer Portal

• Role-based quote creation and user access control
• Standardized order status tracking (Approval, Processing, Delivery, etc.)
• Cosmetic consistency across sections
• Customer request creation (manual by admins/sales)
• Status-based email notifications
• Multi-language support
• Downloadable account statements
• Stripe payment integration and full subscription control

Travel & Expense Report

• Multi-language interface
• Multi-site support
• Admin configuration now available within the app (no SharePoint needed)
• Integrated with Microsoft Dynamics 365 F&O

Field Service

• Improved contract management
• Dynamics 365 Field Service integration
• Arabic language support

Purchase Requisition

• Mobile/tablet-friendly interface updates
• Admin setup without SharePoint
• Enhanced warehouse logic for partial/complete fulfillment
• Dashboard customization by user roles
• Arabic language support

Time N Go

• Arabic language interface now available
• Multi-site time tracking
• Exportable time log reports
• New Project Management Tools (inspired by ActiTime): Add/manage customers, projects, and tasks for accurate time tracking

Inventory Management

• Core app design and development completed

Sales Field

• Modernized UI/UX for a more intuitive sales experience

What This Means

With upgraded features across all platforms, teams can now offer faster on-boarding, smooth operations, and stronger product positioning to customers.

For more information or to request a demo, please contact KAISPE marketing team.

Sameen Ansar, KAISPE LLC, info@kaispe.com

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What is Connected Field Service?

Connected Field Service is an innovative solution that integrates the Internet of Things (IoT) with field service operations. This helps businesses manage and maintain their assets. They can monitor their assets by connecting IoT-enabled devices to a centralized platform. Thus, helping them detect anomalies, and take proactive measures to prevent failures. This integration enables automated workflows, such as generating maintenance requests or requesting technicians. Connected field service not only improves business operations and reduces downtime but also improves customer satisfaction. As it helps deliver timely, intelligent, and predictive maintenance services.

Importance of Predictive Maintenance

Predictive maintenance for connected field assets helps organizations move from reactive measures to proactive service model with the help of IoT. This happens through collecting real-time data using IoT devices to help identify issues that may occur in the future, thus, preventing from costly repairs. This not only reduces downtime but also cuts down maintenance expenses and makes sure that operations move smoothly. Additionally, predictive maintenance enhances customer satisfaction through timely issue resolution and builds trust with transparent, informed service delivery.

Benefits of Predictive Maintenance

1. Cost Efficiency: Predictive maintenance helps avoid expensive repairs and replacement costs by addressing problems early.
2. Increased Uptime: Real-time monitoring and quick response ensure equipment remains operational, minimizing production delays.
3. Safety Improvements: Identifying issues before they escalate prevents accidents, ensuring worker safety.
4. Sustainability: Efficient maintenance reduces energy consumption and waste, supporting environmental goals.

With these benefits in mind, we’ll move forward into exploring real use cases of connected field service and how it utilizes predictive maintenance. We will be referring to:

KAISPE Field Service App

It is an AI-based power app that utilizes Agentic AI and Copilot to empowers field service teams to conduct inspections and services swiftly and securely using devices. It caters various industries, to manage services including facilitating inspections in construction sites, factory assets, infrastructure, and public works scenarios.

https://appsource.microsoft.com/en-us/product/dynamics-365/kaispellc.kspfiapp?tab=Overview

KAISPE IoT Device Portal

KAISPE IoT Portal is a fully functional web portal that allows users to manage and maintain IoT devices. It helps to create telemetry rules and examine device telemetry notifications, among other features. The portal leverages Microsoft Azure IoT as the underlying IoT platform.

https://azuremarketplace.microsoft.com/en-us/marketplace/apps/kaispellc.kaispe_iotwebportal?tab=Overview

KAISPE Power BI Dashboard

KAISPE Air Compressor dashboard’s design gives useful insights into air compressors health and maintenance requirements. Using this dashboard, customers can monitor and maintain the air compressors, installed on various locations and sites.

How Connected Field Service Achieves Predictive Maintenance

Integration of IoT and Field Service

Let’s take an example of an industrial grade air compressor. The compressor is already installed in a factory and needs to be monitored for any upfront maintenance needs. Sensors on the compressor emit the relevant telemetry information and this information comes into the device portal through Azure IoT. The Field Service app records the compressor as the customer asset and lists it in the IoT Device Portal as well. Field Service app is integrated with the device portal, so any violation of the rule(s) specified in the device portal will come as a notification to the Field Service app that will ultimately trigger the predictive maintenance job.

Monitoring and Maintenance with Real-Time Insights

There is a rule created in the device portal that says that the compressor temperature MUST be between 60 F and 80 F. On a typical production day, the compressor temperature shoots to 82 F and 85 F. When this telemetry reaches the device portal in real time, the relevant rule is kicked in and violated twice. That comes as a notification in Field Service app and based on the configuration settings, a maintenance job is created with relevant resources (frontline workers, maintenance equipment and tools) and assigned to the corresponding frontline team. The team visits customer assets on a scheduled date/time and addresses any potential issue upfront.

To continuously monitor the health of the compressor, field staff can also use Microsoft Power BI based dashboard. The dashboard provides the near real time analytics to get more relevant insights about asset’s health.

Understanding the Solution Architecture

The high level solution architecture highlights the integration of IoT devices, Azure IoT Hub, Blob Storage, Power Automate, and SharePoint. This setup enables efficient two-way communication within the ecosystem.

IoT devices continuously send telemetry data to Azure IoT Hub, which serves as the central hub for data ingestion and management. Then, Blob Storage stores the data for processing and analysis. Using Power Automate, the stored data triggers actions to generate records in SharePoint, a key part of the Field Service system. The integration also allows communication back to the IoT devices when required, creating a feedback loop that improves operational efficiency and supports real-time decision-making.

Future of Predictive Maintenance

The integration of predictive maintenance and connected field services is just the beginning. With advancements in AI and machine learning, businesses will soon be able to predict failures with even greater accuracy. Features like digital twins, which replicate physical assets in a virtual environment, will allow for advanced simulations and proactive planning. By combining these innovations with IoT systems, the future of industrial automation looks promising, offering unparalleled efficiency and resilience.

Conclusion

Using KAISPE solutions and services, businesses can improve the operational efficiency of physical assets through the application of specialized apps and analytics, resulting in reduced operating and maintenance costs, while improving uptime and production.

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Understanding the Role of AI in Construction

In construction, AI technologies are used to automate and optimize various tasks, including defect detection, project planning, resource allocation, and safety monitoring. The integration of AI in Construction Quality Control ensures that every project adheres to high standards, minimizing errors and defects.

Traditional Methods vs. AI Defect Detection

Traditionally, quality control in construction involved manual inspections, which were time-consuming, labor-intensive, and prone to human error. Inspectors relied on visual observations and checklists to identify defects, a process that often missed hidden or had flaws.

AI Defect Detection offers a modern alternative, utilizing machine learning algorithms and computer vision to identify defects with unparalleled accuracy. For instance, drones equipped with AI-powered cameras can scan construction sites and identify structural defects or material inconsistencies. This not only saves time but also provides a more detailed analysis than human inspectors.

How AI Defect Detection Works

1. Data Collection: AI systems collect data from various sources such as drones, cameras, and sensors. These devices capture high-resolution images and videos of construction sites.
2. Image Processing: Using computer vision, AI analyzes the images and videos to detect anomalies. For example, it can identify cracks in concrete, uneven surfaces, or misaligned beams.
3. Pattern Recognition: AI systems are trained on large datasets of construction defects, enabling them to recognize patterns and classify defects accurately.
4. Real-Time Reporting: Once a defect is detected, the system generates real-time reports, highlighting the issue and suggesting corrective actions. This ensures immediate intervention, preventing further complications.

Benefits of AI in Construction Quality Control

Enhanced Accuracy

AI systems are capable of detecting defects that are invisible to the naked eye. For example, thermal imaging cameras powered by AI can identify heat leaks or insulation gaps that would otherwise go unnoticed.

Cost Efficiency

By identifying defects early, AI helps reduce rework and material wastage. This translates into significant cost savings for construction companies.

Improved Safety

AI technologies can identify potential safety hazards, such as unstable structures or hazardous materials, ensuring a safer work environment for construction workers.

Faster Inspections

AI accelerates the inspection process, allowing construction projects to progress without delays. For instance, a drone can scan an entire construction site in a matter of hours, a task that would take days for a human inspector.

Data-Driven Decision Making

The insights provided by AI systems enable construction managers to make informed decisions. By analyzing historical data, AI can predict potential defects and recommend preventive measures.

Leveraging KAISPE Field Service Application

The KAISPE Field Service Application is a prime example of how AI can be effectively integrated into construction workflows. This application utilizes cutting-edge features such as:

• Virtual Assistant: A smart assistant that helps field workers with tasks like scheduling, troubleshooting, and accessing project information in real time.
• Object Detection: AI-driven object detection capabilities identify specific tools, equipment, or defects at the construction site, improving efficiency and accuracy.
• Abnormalities Finding: The application leverages Power Apps Canvas App to detect irregularities in construction processes, such as misalignments or material defects, ensuring that projects meet quality standards.
• Predictive Maintenance: The application monitors equipment performance and analyzes data to foresee potential failures. By providing timely maintenance recommendations, it helps minimize downtime, reduce repair costs, and ensure operational efficiency.

By combining these features, the KAISPE Field Service Application enhances operational efficiency and supports proactive problem-solving, aligning perfectly with the demands of modern Construction Quality Control.

Challenges and Limitations

While the benefits of AI Defect Detection are undeniable, its adoption in the construction industry is not without challenges:

• High Initial Costs: Implementing AI technologies requires significant investment in equipment, software, and training.
• Data Quality: The accuracy of AI systems depends on the quality of the data they are trained on. Poor-quality data can lead to incorrect predictions.
• Integration Issues: Integrating AI with existing construction processes and workflows can be complex.
• Resistance to Change: Many construction professionals are hesitant to adopt new technologies, preferring traditional methods.

The Future of AI in Construction

The future of AI Construction looks promising, with advancements in machine learning, computer vision, and robotics paving the way for even more sophisticated applications.

Artificial Intelligence (AI) is revolutionizing the construction industry by addressing inefficiencies, reducing costs, and enhancing safety. AI-powered tools enable smarter project planning and design, allowing architects and engineers to simulate various scenarios and optimize materials, timelines, and costs before construction begins.

Looking ahead, AI will play a critical role in predictive maintenance, resource optimization, and safety management. Sensors and AI-driven systems will monitor equipment and worker health, reducing accidents and downtime. Furthermore, sustainable construction practices will benefit from AI’s ability to design energy-efficient buildings and minimize material waste. As the industry embraces these advancements, the focus will shift toward workforce upskilling and ensuring seamless integration of AI technologies to unlock their full potential.

Conclusion

The integration of AI Defect Detection in Construction Quality Control is transforming the industry, offering unparalleled accuracy, efficiency, and safety. While challenges remain, making AI an indispensable tool for modern construction. As technology continues to evolve, the construction industry must embrace these innovations to stay competitive and deliver high-quality projects.

By adopting AI Construction solutions, companies can not only enhance their quality control processes but also set new benchmarks for excellence in the industry. The future of construction lies in leveraging AI to build safer, smarter, and more sustainable structures.

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