Industry: Healthcare | Duration: 8 months | Location: Pakistan

Client Need: Reduce long patient wait times and support diagnosis at primary clinics through an intelligent triage assistant.

🩺 The Challenge

Clinics lacked triage automation, suffered physician overload, and had no unified system for recording patient history or suggesting diagnoses, resulting in 3+ hour wait times and high inconsistency.

💡 Our Solution

• Built an AI-powered symptom checker using BERT-based NLP
• Connected real-time vital signs (BP, O2, Pulse, Temp)
• Introduced risk classification (Urgent / Routine / Referral)
• Developed a lightweight EHR-lite module with full patient history
• Deployed via Docker and ONNX for edge compatibility

🧩 Technology Stack

Frontend: React.js, Tailwind CSS
Backend: Python (FastAPI)
AI Models: BERT (NLP), Decision Trees, ICD-10 mapping
Database: PostgreSQL, Redis
Deployment: Docker, ONNX runtime

🚀 Results Achieved

“SmartCare AI helped us handle twice the patient volume with the same staff. We’re not just treating patients faster — we’re treating them smarter.”
— Clinic Director, Rawalpindi Pilot Facility

📈 Expansion & Future Plan

After a successful pilot at 3 clinics, SmartCare AI is scaling to 12+ locations with multilingual support (Urdu & Pashto), national eHealth integration, and doctor-patient smart routing planned.

Industry: Fintech | Duration: 6 months | Region: UK, UAE

Client Need: Develop a secure, transparent, and audit-friendly financial application using blockchain to handle transactions, contracts, and reporting in a decentralized environment.

🧩 The Challenge

Traditional ledger systems faced trust issues, manual auditing, and lacked real-time accountability. The client needed a platform that could:

• Prevent double-spending and manual entry errors
• Enable tamper-proof transaction logs
• Automate recurring contracts/payments with smart contracts
• Offer easy auditing and financial reporting

💡 Our Solution

• Developed a decentralized finance app powered by Ethereum blockchain
• Implemented smart contracts for invoices, recurring payments, and settlements
• Created a secure, role-based dashboard for admins, auditors, and clients
• Integrated real-time reporting and ledger export tools
• Gas-fee optimization for contract execution

🧪 Technology Stack

Frontend: React.js, Chakra UI
Backend: Node.js, NestJS
Blockchain: Solidity, Web3.js, Hardhat
Database: MongoDB
Deployment: IPFS for contracts, AWS EC2 for APIs

📊 Results Achieved

“We no longer fear audits or compliance issues. Finwise not only improved efficiency but built trust with our clients and investors.”

📈 Future Outlook

The next phase involves integration with DeFi protocols for investment automation and expansion into crypto-to-fiat payment bridges for cross-border transactions.

Industry: Agriculture | Duration: 9 months | Region: Pakistan (Pilot), UAE (Commercial)

Client Need: Help farmers monitor soil health, optimize irrigation, and increase crop yield using a tech-enabled, low-cost smart farming system.

🌱 The Challenge

Farmers had no visibility into their soil moisture, pH levels, or crop health. Water was being overused, fertilizer timing was guesswork, and yield loss was frequent. The client wanted a system that:

• Provides real-time data from fields
• Works in low-internet, rural conditions
• Is affordable for small to mid-sized farms
• Can guide decisions on watering, fertilizing, and harvesting

💡 Our Solution

• Developed battery-powered IoT sensor nodes (soil moisture, pH, temp, light)
• Used LoRaWAN for long-range, low-power communication in remote areas
• Created a web/mobile dashboard with visual alerts, crop logs, and trend charts
• AI module for watering & fertilizing predictions using historical data
• SMS fallback alerts for areas with no smartphone access

🧪 Technology Stack

Hardware: ESP32 + LoRa Sensors (Soil, Temp, Humidity, pH)
Gateway: Raspberry Pi + The Things Network (TTN)
Backend: Node.js, Express, MongoDB
Frontend: Vue.js, Chart.js
AI: Time-series regression for crop advisory engine

📊 Results Achieved

“AgriSense gave us a way to listen to our fields. Our water bills dropped, and we got our best harvest in 6 years.”

🚜 What's Next

The client is now expanding to 100+ farms across Punjab and UAE’s desert farming projects, with plans to integrate drone-based NDVI imaging and multilingual voice-based farmer support.

Industry: EdTech | Duration: 7 months | Region: UK, Pakistan, UAE

Client Need: Ensure integrity in online exams by preventing cheating and automating invigilation across hundreds of simultaneous test sessions.

🎓 The Challenge

Universities and certification bodies faced growing concerns over cheating during remote exams. Manual invigilation was impractical, inconsistent, and costly. The client required a scalable solution that could:

• Verify student identity using facial recognition
• Monitor behavior using webcam and mic
• Detect cheating patterns using AI
• Generate auto-flagged exam reports

💡 Our Solution

• Built a browser-based exam platform with secure lock-in mode
• Integrated face detection and ID matching (via webcam)
• Used AI to monitor eye movement, voice frequency, phone/glare detection
• Created auto-flagging system with timestamps & severity scores
• Offline exam fallback for low-connectivity zones with upload syncing

🧪 Technology Stack

Frontend: React.js, WebRTC, Tailwind CSS
Backend: Node.js, Firebase, MongoDB
AI Models: OpenCV, Dlib, TensorFlow.js (face tracking, behavior detection)
Deployment: Google Cloud + Local Failover Mode

📊 Results Achieved

“EduProctor gave our platform credibility. We’ve been able to scale to 10x more students without sacrificing exam integrity.”

📚 Future Plans

EduProctor is expanding support to voice-based authentication, real-time plagiarism tracking, and integrations with Moodle, Canvas, and Microsoft Teams for seamless LMS integration.

Industry: Logistics & Transportation | Duration: 5 months | Region: UAE, Pakistan

Client Need: Streamline the management of delivery vehicles, reduce fuel costs, and enable live tracking for dispatchers and customers.

🚛 The Challenge

The logistics company was struggling with:

• No real-time visibility into vehicle location
• Manual trip logging and driver performance issues
• Fuel wastage due to inefficient routing
• Customer dissatisfaction due to unpredictable ETAs

💡 Our Solution

• Built a web dashboard and mobile app for fleet operators and drivers
• Integrated live GPS tracking using GSM modules and Google Maps API
• Route optimization based on real-time traffic & delivery zones
• Auto-generated trip reports with fuel consumption & distance logs
• Driver behavior analysis (speeding, idle time, hard braking)

🧪 Technology Stack

Frontend: Angular, Ionic (Mobile)
Backend: NestJS, PostgreSQL, Firebase for push notifications
Mapping: Google Maps API, Mapbox
Devices: Queclink GPS Trackers, SIMCom GSM modules

📊 Results Achieved

“With InoFleet, we gained real-time control over every delivery. It’s helped cut fuel bills, reduce idle time, and make customers happier.”

📦 Future Roadmap

InoFleet is now being extended to support cold chain tracking (temperature + humidity sensors), auto maintenance reminders, and predictive delivery ETA using AI-based traffic models.

Industry: Security & Smart Buildings | Duration: 4 months | Region: Pakistan, UAE

Client Need: Replace traditional ID card access with a secure and contactless face recognition system for offices, events, and gated facilities.

🔐 The Challenge

The client needed to modernize their access control system with:

• Zero-contact entry post-COVID
• Real-time entry logs with photo proof
• High accuracy even in varying lighting conditions
• Easy admin dashboard for managing permissions

💡 Our Solution

• Built an AI-based facial recognition system with liveness detection
• Connected hardware module with Raspberry Pi + IR camera
• Developed a secure cloud dashboard to manage users and access rules
• SMS/email notifications for unauthorized access attempts
• Offline fallback for network downtime with auto-sync

🧪 Technology Stack

Frontend: Vue.js (Admin Dashboard), Bootstrap
Backend: Python (Flask), Firebase Auth
AI Models: OpenCV, Dlib, FaceNet with liveness detection
Hardware: Raspberry Pi 4, IR Cam, Servo Motor Lock System
Cloud: AWS EC2 + Firebase Realtime DB

📊 Results Achieved

“We wanted tech that was smart, secure, and easy to use. SafePass checked all the boxes — now we use it for everything from staff entry to guest check-ins.”

🏢 What’s Next

The client is integrating SafePass with elevator control, time-based access scheduling, and plans to deploy voice-activated access for VIP zones.

Industry: LegalTech | Duration: 6 months | Region: US, Pakistan

Client Need: Streamline and digitize the creation, signing, and tracking of legal documents using blockchain to ensure tamper-proof, transparent, and verifiable contracts.

⚖️ The Challenge

Legal firms were managing contracts via outdated processes that were prone to:

• Manual document tracking and versioning
• Unauthorized modifications post-signing
• Insecure email-based approvals and slow notarization
• No visibility into agreement lifecycle or audit trail

💡 Our Solution

• Built a smart contract-based document automation platform
• Enabled real-time version control and blockchain notarization
• Created legal templates for NDAs, service agreements, and MoUs
• Integrated e-signature workflow and blockchain-based timestamping
• Included permission-based access and role-level visibility

🧪 Technology Stack

Frontend: React.js, Material UI
Backend: Node.js, NestJS
Blockchain: Solidity (Ethereum), IPFS for file storage
Identity & Signature: Firebase Auth, MetaMask Integration
Smart Contract Tools: Hardhat, Ethers.js

📊 Results Achieved

“LegalChain eliminated paperwork delays and improved compliance. It’s now our go-to tool for legal document handling.”

📄 What’s Next

The roadmap includes multilingual smart contracts, decentralized arbitration mechanisms, and integration with global regulatory document APIs.

Industry: Government / Urban Infrastructure | Duration: 9 months | Region: UAE (Pilot), Pakistan (Rollout)

Client Need: Integrate data from city sensors, traffic cams, and public systems into a unified platform to monitor, optimize, and predict urban service needs.

🏙️ The Challenge

Municipal authorities struggled with siloed systems and no real-time analytics. Key challenges included:

• No centralized dashboard to view city health metrics
• Delayed response to traffic congestion, weather alerts, or utility failures
• Lack of predictive insights for planning or resource allocation
• No integration between departments (waste, traffic, energy)

💡 Our Solution

• Built a live dashboard with data pipelines from 10+ public and private systems
• Used IoT edge nodes to collect data from cameras, pollution sensors, and traffic lights
• Integrated GIS-based maps for traffic, weather, waste collection, and utilities
• Implemented an AI-based event alert engine for anomaly detection (e.g., traffic jams, air quality)
• Enabled public-facing open data API for transparency and citizen engagement

🧪 Technology Stack

Frontend: Angular, Leaflet Maps, Highcharts
Backend: Python (FastAPI), Apache Kafka, PostgreSQL (PostGIS)
IoT: LoRa/ESP32 edge gateways, MQTT
AI & Alerts: Scikit-learn (Anomaly Detection), CRON AI Video Feeds
Cloud: Azure IoT Hub, Google Cloud Dataflow

📊 Results Achieved

“CityPulse became the control center for our city. It connected our teams, empowered citizens, and made real-time governance possible.”

🌐 What’s Next

Expansion plans include predictive modeling for waste collection, air quality forecasting, and integrations with citizen-reporting mobile apps for civic issues.

Industry: Healthcare | Duration: 6 months | Region: Pakistan, UAE

Client Need: Develop a platform that enables patient record sharing and seamless referral workflows between hospitals, clinics, and labs.

🏥 The Challenge

Healthcare providers often work in silos, leading to:

• Redundant tests due to lack of medical history
• Patient referral delays across hospitals
• No unified EHR system for different levels of care
• Manual and paper-based communication

💡 Our Solution

• Built a centralized yet permissioned EHR platform with secure access
• Enabled patient data sharing between hospitals, clinics, and labs
• Created referral workflows with status tracking and automated notifications
• Built in ICD-10 mapping, lab report uploads, and prescription sync
• Enabled patients to view their records and control who sees what

🧪 Technology Stack

Frontend: Angular, Ionic (Patient Portal)
Backend: Node.js, MongoDB, JWT
Security: AES-256 encryption, OAuth 2.0
Interoperability: FHIR-compliant API modules
Deployment: On-premise (hospitals) + Cloud sync

📊 Results Achieved

“HealthLink made our multi-location hospital network feel like a single unit. Patient care became faster, smarter, and safer.”

🔗 What’s Next

The roadmap includes HL7 integration with national health registries, AI-based diagnostic summaries, and a multilingual version for patient-facing features.

Industry: Education & Corporate Training | Duration: 5 months | Region: Pakistan, KSA

Client Need: Build a lightweight but powerful LMS to manage courses, assignments, certification, and learner analytics for both academic and corporate clients.

📚 The Challenge

Off-the-shelf LMS platforms were either too expensive or lacked local language support, mobile responsiveness, and integration capabilities. Specific issues:

• No mobile app for learners on low-end devices
• Complex UI and limited reporting for instructors
• Lack of video hosting & file submission workflows
• No automation for certifications or quiz scoring

💡 Our Solution

• Developed a multilingual LMS platform with full responsive support
• Instructor dashboard with drag & drop course builder
• Quiz builder, assignment submissions, gradebook & discussion forums
• Auto certificate generation using PDF templates
• Offline video support and progress sync in mobile app

🧪 Technology Stack

Frontend: Angular, Ionic, Bootstrap
Backend: Laravel, MySQL
Media: HLS video player, Cloudinary for media hosting
Mobile App: Capacitor (Android & iOS)
Integrations: Zoom API, Google Drive, SMS Gateway

📊 Results Achieved

“We’ve trained over 10,000 professionals in 3 countries using InoLMS. It's fast, accessible, and tailored to our needs.”

🎯 Future Goals

Expanding with AI-powered adaptive learning, SCORM/xAPI support, and gamification tools (badges, progress bars, leaderboards) to increase learner engagement.

Industry: Retail & E-commerce | Duration: 4 months | Region: Pakistan, Bahrain

Client Need: Build a predictive dashboard for inventory planning, sales trend forecasting, and stockout prevention for retail chains with physical and online stores.

🛍️ The Challenge

Retail stores were experiencing:

• Frequent overstocking and understocking of fast-moving items
• Lack of centralized visibility across outlets
• No real-time sales tracking or data-driven demand planning
• Inventory write-offs and customer churn due to stockouts

💡 Our Solution

• Built a visual dashboard to monitor inventory, sales, and restocking alerts
• Used time-series forecasting (Prophet + LSTM) for daily and seasonal demand prediction
• Connected POS data streams from multiple stores and warehouses
• Automated reorder suggestions and supplier management triggers
• Added exportable insights for procurement and finance teams

🧪 Technology Stack

Frontend: React.js, Chart.js, DataTables
Backend: Django, Celery, Redis
AI/ML: Prophet, LSTM (TensorFlow)
Database: PostgreSQL, Firebase (for syncing POS data)
Deployment: Docker on AWS ECS

📊 Results Achieved

“RetailEdge gave us the visibility and confidence to make smarter stocking decisions. We now prevent losses before they happen.”

📦 Next Steps

We're integrating barcode scanners, supplier APIs, and an AI-driven promotion engine that recommends sale strategies based on slow-moving stock and predicted seasonal demand.

Industry: Industrial Automation | Duration: 6 months | Region: Pakistan, Malaysia

Client Need: Automate quality assurance in manufacturing lines using computer vision to detect defects in real time and reduce human error.

🏭 The Challenge

Manual quality inspection was inconsistent, slow, and prone to errors. Challenges included:

• Undetected surface defects leading to costly returns
• No real-time detection or flagging of faulty products
• Operator fatigue affecting inspection accuracy
• No digital record or traceability of QA checks

💡 Our Solution

• Developed a real-time visual inspection system using AI + camera feeds
• Trained custom object detection models (YOLOv5, EfficientDet) for defects
• Integrated system with conveyor belt to auto stop on detection
• Logged each inspection with timestamp, defect type, and image snapshot
• Deployed a dashboard for analytics, trend reports, and improvement insights

🧪 Technology Stack

AI Models: YOLOv5, EfficientDet, OpenCV
Backend: Python (Flask), FastAPI
Hardware: Raspberry Pi + Pi Cam, USB Industrial Cameras
Dashboard: React.js + Recharts + MQTT Broker
Deployment: On-premise Edge Devices with Local Sync

📊 Results Achieved

“VisionBot has saved us hours of labor daily and helped us catch defects no human eye could catch consistently. It paid for itself in 2 months.”

🔧 What’s Next

We’re integrating multi-angle 3D scanning, anomaly heatmaps, and predictive defect analysis to reduce future defects and suggest root cause remediation automatically.