AI-Powered Automated
Waste Segregation
Transforming urban waste management at the first mile. Automated sorting. Zero resident effort. Real-time IoT data.
Behavior change takes time. Space makes it harder. Most Nepali homes have no room for 3–4 bins and compact housing shrinks that even more.
Nepal's Waste Problem Starts at the Source
When all waste is mixed, valuable materials are lost. Automating recovery before landfilling helps us recycle, reuse, and build a circular economy.
70% of waste is mixed at the source, making recovery nearly impossible.
Labor-intensive, unsafe, and inaccurate processes drive up municipal costs.
Contamination reduces recyclable market value by up to 80%.
No real-time data on waste volume, composition, or bin fill levels.
Automating the “First Mile” of Waste Management
“WASTE THAT SORTS ITSELF.”
Zero Behavior Change
Residents dispose of waste as usual. Waste is collected and transported to the AI-powered sorting facility.
Automated Sorting & Material Grading
AI vision and sensors identify and classify material type. Automated mechanisms sort materials into separate streams.
Data-Driven Waste Intelligence
Real-time insights into material flow, contamination, and recovery. Enables smarter operational and recycling decisions.
The 7-Step Automated Processing FlowAI + Sensor Fusion
The Only “Zero-Effort” Solution in the Market
We eliminate the “Human Factor” — the weakest link in traditional waste management.
| FEATURE | MANUAL MRF | CONVENTIONAL MRF | LHOTA SYSTEM |
|---|---|---|---|
| User Effort | High | Medium | LOW (Zero Effort) |
| Sorting Accuracy | Low (Human) | Medium | HIGH (AI Vision) |
| Processing Speed | Slow | Medium | HIGH (Automated) |
| Data Insights | None | Limited | ADVANCED (IoT Telemetry) |
Early Traction & Ecosystem Validation
Active pilot discussions, municipal engagement, and manufacturing R&D underway in Nepal.
MRF Pilots
2 active discussions for MRF Pilot + 2 Scheduled
Lalitpur Metro
Lalitpur Ward 1, 12 & 18 (Municipal Discussion)
Tech Partners
2 Tech Partners (Under Discussion)
Dataset R&D
AI Model & Local Dataset Initiated
Manufacturing
Bhairab Nath Iron Industries Pvt. Ltd. (Hardware R&D)
Tapping into NPR 6.3B+ Dry Waste Opportunity
Nepal's urban population is growing at 3.2% annually. Multiple revenue streams across hardware and software.
293 urban municipalities · 300,000 MT/year dry waste nationwide
High-density metro clusters · 75,500–150,000 MT/year addressable volume
Kathmandu • Pokhara • Biratnagar · Initial 3–5 year deployment focus
Three Diversified Revenue Streams
Direct Sales
One-time sale of AI system hardware and robotic arms to existing Materials Recovery Facilities, with proprietary AI software provided through an ongoing subscription.
Lease Model
Hardware and AI system provided through a monthly or annual lease, lowering upfront costs and covering maintenance.
Software Layer
Ongoing AI software access, data insights, and system management — the recurring layer that powers both sales and lease customers.
Multi-Disciplinary Execution Team
Deep expertise spanning AI, computer vision, industrial automation, and municipal urban planning.
Samrat Tamrakar
PRODUCT VISION • OPSProduct strategy, business development, fundraising, partnerships, team leadership, and execution.
AI / ML Lead
AI • COMPUTER VISIONSpecialized in Computer Vision, Object Detection, local packaging model training, and NIR sensor fusion.
Hardware Lead
HARDWARE • IOT • CADMechanical Engineer specializing in industrial automation, conveyor systems, robotic integration, and hardware design for automated MRFs.
Operations Lead
GOVT RELATIONS • COMPLIANCEUrban Planner with deep connections in Kathmandu Metropolitan City (KMC). Expert in municipal policy and regulatory compliance.
BUILDING FOR NEPAL • SCALING WITH IMPACT
Join Us in Building the Infrastructure for a Cleaner Tomorrow
Seeking seed funding to build, train, and validate our AI sorting model on localized waste-stream data — the critical step before our first pilot deployment in Nepal.