Freelance AI Chatbot Developers in IslamabadFreelance AI Chatbot Developers in Islamabad
AI SaaS Dev | LLMs, Agents, Voice & Automation | Web, Mobile
New to Contra
AI SaaS Dev | LLMs, Agents, Voice & Automation | Web, Mobile
Cover image for InForm - AI-Driven Physiotherapy App
InForm - AI-Driven Physiotherapy App for Diagnosis, Rehab & Recovery Tracking The core problem it solves: Patients struggle to get timely, structured physiotherapy guidance, while physiotherapists are overwhelmed managing cases, tracking progress, and creating personalized rehab plans manually. Existing systems either lack intelligence or lack control. This product creates a complete digital workflow where diagnosis, communication, and recovery are all connected into a single system. What was built: A full AI-powered physiotherapy platform with mobile apps for patients and a web-based admin system for physiotherapists. Patients begin by submitting structured symptom data through guided questionnaires. Instead of jumping directly to conclusions, the system uses an AI diagnosis engine to analyze patterns and generate internal clinical suggestions. These suggestions are never shown to patients, they act as decision support for physiotherapists, ensuring every diagnosis remains human-approved. Once a case is created, physiotherapists review patient data, validate or override AI recommendations, and communicate directly through an in-app messaging system. Every interaction is tied to a structured case, ensuring context is never lost. The system then moves into recovery management. Physiotherapists create personalized rehab plans with multi-phase programs, exercise libraries, and video guidance. Patients follow these plans inside the app, logging progress, completing KPI-based milestones, and moving through recovery phases in a structured way. A key part of the system is the progress tracking engine. Patients log metrics, complete phase-based goals, and unlock new stages only when criteria are met. Physiotherapists get real-time visibility into adherence, performance, and patient feedback, making the system both trackable and measurable. Alongside this, an intelligent chatbot handles general queries and reduces load on physiotherapists. When confidence is low or cases become complex, the system escalates conversations into structured cases with full context preserved. Technical architecture: Built as a scalable mobile-first system using React Native for patient apps and React.js for the admin panel, with a Node.js/Nest.js backend and Python powering AI-driven diagnosis logic. Data is managed through PostgreSQL, with secure authentication and encrypted communication layers. The AI layer is designed as a support system, not a replacement. It uses LLM-based reasoning to assist diagnosis and continuously improves through feedback loops based on physiotherapist decisions, creating a human-in-the-loop learning system. Deployed on cloud infrastructure (AWS/GCP), with Stripe integration for subscription-based access and a modular architecture designed for future AI expansion. Business model built in from day one: Subscription-based access for patients, with clear pathways to expand into AI-assisted rehab recommendations, outcome analytics, and protocol optimization. The system is designed to evolve into a data-driven recovery platform where every patient interaction improves future treatment accuracy, turning clinical workflows into scalable intelligence.
0
87
Cover image for BudgetNest โ€” AI-Powered Personal Finance
BudgetNest โ€” AI-Powered Personal Finance SaaS Most people don't track their finances because the friction is too high. BudgetNest removes that friction entirely, every transaction captured automatically, categorised intelligently, and surfaced through analytics that actually help people make better decisions. The core problem it solves: Manual expense logging fails because people forget, get lazy, or simply don't have time. BudgetNest built an automated capture layer that works across every channel a user already operates in i.e. SMS alerts, bank emails, receipt photos, WhatsApp messages, and voice notes in English and Urdu. The system deduplicates intelligently across all input sources so nothing gets logged twice regardless of how it came in. What was built: A complete AI finance platform with five distinct automated capture modes SMS and email parsing for bank transaction alerts, PDF and image bank statement upload with AI extraction, OCR receipt scanning via camera, a WhatsApp bot that accepts text, images, and voice notes, and multilingual voice input for manual cash payments. Every transaction flows through an LLM-powered categorisation engine that auto-assigns categories and subcategories, recognises vendors, and learns from behaviour over time. Beyond capture, the system includes smart budgeting with AI-driven suggestions based on spending patterns, subscription detection for recurring transactions, shared expense and split-bill tracking, fraud detection for unusual transactions, and forecasting that projects deficit against income. Dashboards surface everything through charts, trend lines, and weekly and monthly summaries. Technical architecture: React Native across iOS and Android, Node.js and FastAPI backend, PostgreSQL and MongoDB, AWS infrastructure with EC2, S3, and RDS, Python-based NLP and OCR pipeline using Transformers and Tesseract, Twilio WhatsApp integration, Gmail API for email parsing, and Firebase for push notifications. Business model built in from day one: Freemium with premium automation features, B2B white-label capability for microfinance institutions and NGOs, and the OCR and SMS parsing logic architected as standalone APIs for third-party licensing meaning the AI layer has revenue potential independent of the consumer app.
1
118
๐Ÿš€ AI & Fullstack Developer | MERN Expert ๐Ÿš€
$10k+
Earned
5x
Hired
5.0
Rating
28
Followers
๐Ÿš€ AI & Fullstack Developer | MERN Expert ๐Ÿš€
Full Stack Developer| n8n | Framer| Kajabee| Webflow Expert
1x
Hired
43
Followers
Full Stack Developer| n8n | Framer| Kajabee| Webflow Expert