Impact Portfolio
From enterprise solutions built for industry leaders to products we conceived, engineered, and brought to market — a curated look at the work that defines us.
AI Fire & Safety Monitoring System
The AI Fire & Safety Monitoring System is an intelligent workplace safety platform that transforms existing CCTV infrastructure into a proactive, AI-powered monitoring solution. Using advanced Computer Vision, the system continuously analyzes live camera feeds to detect fire hazards, safety violations, and restricted area intrusions in real time.
Real-time Detection
Continuously analyzes live camera feeds using edge-deployed computer vision models to detect fire, smoke, and temperature warnings in under two seconds.
The Challenge
Traditional safety monitoring relies heavily on manual supervision, making it difficult to continuously monitor multiple camera feeds. Delayed detection of fire hazards, missing PPE, and restricted area intrusions can lead to accidents and compliance issues.
Our Solution
Developed a scalable AI platform that analyzes live CCTV feeds without new hardware. The system automatically detects fire/smoke, PPE violations, restricted zone intrusions, and unsafe behavior, streaming alerts to a central dashboard.
Key Metrics Achieved
- Detected hazards in under 2 seconds
- Increased PPE compliance to 98.4%
- Automated 24/7 compliance logging
“Implementing the AI Fire & Safety system transformed our safety protocols. We went from reactive incident response to proactive prevention, detecting hazards instantly before they escalate.”
Last-mile informal vendor discovery platform.
Bittesy is a hyper-local vendor discovery platform designed for the dense, fast-moving urban landscape of Indian cities. It bridges the gap between everyday users and small businesses, street vendors, local shops, and informal sellers that remain virtually invisible digitally.
Micro-Local Navigation
Calculates optimized real-world walking and auto-rickshaw path networks for the last 500 meters, taking dense city alleyways (galis) into account.
The Challenge
Millions of small, informal vendors in India operate without any digital presence. A hardware store in a gali, a tailor two streets away, or a vegetable seller serve their communities daily but cannot be found digitally. Existing mapping platforms fail to solve discovery for this informal, micro-local commerce segment.
Our Solution
Built a low-friction discovery platform that maps local vendors on a live neighborhood map. Users can search by category (food, services, goods) and navigate real-world walking paths. Registration is optimized for mobile-only, non-technical users and relies on community vouching for fresh data.
Key Metrics Achieved
- Mapped 15,000+ informal vendors
- Increased micro-vendor foot traffic by 30%
- Zero-cost digital footprint for small businesses
“Bittesy did what mainstream maps couldn't. It brought our small local market stalls online, generating a 30% increase in foot traffic for vendors who have never owned a website.”
High-security dating app with AI identity verification.
Swayya is a highly secure dating application prioritizing user trust, data privacy, and seamless scalability. The project achieved a frictionless signup flow on the frontend combined with enterprise-grade security and automated AI moderation on the backend.
Video Liveness Audit
Employs an advanced multi-step verification pipeline integrating selfie matching, government ID ingestion, and biometric liveness checks.
The Challenge
Traditional dating apps struggle with fake profiles, identity theft, and user safety. Safeguarding sensitive personal information under strict data privacy regulations without adding friction to onboarding is a major hurdle.
Our Solution
Developed Swayya, a production-ready dating platform with enterprise-grade encryption and an AI-driven multi-step verification pipeline. Integrates social SSO, passwordless logins, and asynchronous liveness checks to ensure safety and scale.
Key Metrics Achieved
- AI-powered liveness checks deployed
- 100% encryption of user data at rest
- Zero friction 2FA onboarding experience
“Swayya sets a new standard for dating platforms. By automating identity verification and securing sensitive user data at rest, we built a social ecosystem that is both highly secure and incredibly fluid.”
AI Retail Intelligence & Store Operations Platform
The AI Retail Intelligence Platform is an advanced computer vision solution for retail stores, supermarkets, and large chains. By leveraging existing CCTV infrastructure, the platform continuously analyzes in-store activities to improve operational efficiency, employee productivity, customer experience, inventory management, and overall store security — acting as a virtual store manager.
Employee & Counter Ops
Monitors employee presence, uniform compliance, cashier availability, and idle time. Detects unattended billing counters and staffing gaps to optimize operations in real time.
The Challenge
Large retail stores face inconsistent employee performance, poor customer service, theft, inventory shortages, and inefficient monitoring. Traditional CCTV systems only record events, requiring manual review after incidents. Managers struggle to monitor cashier availability, enforce dress codes, detect suspicious behavior, prevent shoplifting, and maintain service quality across locations.
Our Solution
Developed an AI-powered retail operations platform that transforms existing surveillance cameras into intelligent business assistants. The system tracks employee attendance and behavior, monitors customer interactions, detects theft and suspicious activities, analyzes shelf inventory levels, and generates instant alerts when business rules are violated — all from a centralized dashboard.
Key Metrics Achieved
- Reduced operational losses by 40%
- Real-time shelf stock-out detection
- Automated policy compliance monitoring
“The platform turned our existing cameras into intelligent operations tools. We now detect stock-outs in real time, catch policy violations instantly, and have cut shrinkage losses by 40% across all store locations.”