915287193-ReNewWorks-AI-powered-Waste-to-Product-Startup.pptx

Waste to product

1. ReNewWorks AI- powered Waste- to-Product Startup COLLECT RECYCLE UPCYCLE SELL Transforming waste into valuable products with the power of AI Composite Tiles Footwear Components Stationery Furniture Eco- Hampers August 21, 2025 Circular Economy Innovation

2. Executive Summary ReNewWorks: AI- powered Waste- to- Product Startup ReNewWorks: Circular Economy Solution ReNewWorks is an AI-powered, waste-to-product startup designed to capitalize on circular economy principles. Our business model integrates the entire value chain: collecting post- consumer dry waste, processing it at local recycling facilities, and manufacturing high- value upcycled products. Waste Collection Incentivizing residents and businesses to collect plastic, paper, glass, and small e-waste Processing AI- driven sorting, washing, shredding, and conversion into feedstock Product Manufacturing Creating composite tiles, footwear components, stationery, and modular furniture AI Advantage Unlocking higher yields, reducing waste, and securing superior profit margins Market Opportunity India's waste- plastic recycling and recycled- plastics markets are expanding rapidly, representing a multi- billion dollar opportunity (IMARC Group). The broader EMS market is valued at over $29 billion in 2024, growing at a CAGR of 12.49% through 2031. Key Differentiators Strategic AI implementation for collection route optimization Automated sorting with computer vision systems Page 2 of 10 Manufacturing process control for maximum yield Demand forecasting to optimize production

3. Value Proposition ReNewWorks: AI- powered Waste- to- Product Startup Our model delivers specific benefits to four key stakeholder groups through a scalable circular- economy approach with measurable environmental impact. For Consumers Simple and rewarding way to participate in the circular economy Cash incentives or discount coupons for post-consumer dry waste Convenient recycling through accessible drop-off points and Reverse Vending Machines For Corporates & Retailers Reliable source of locally-made, sustainable products Construction materials like composite tiles for green building projects Unique corporate eco-gifts that align with CSR goals and enhance brand image For Municipalities Measurable system for diverting waste from landfills Helping municipalities meet regulatory targets Reducing carbon footprint and waste management costs For Investors & Judges Scalable, technology-first circular economy model AI integration driving operational efficiency and improved margins Strong, measurable environmental and social impact Page 3 of 10  ReNewWorks presents a robust investment case in India's rapidly expanding multi-billion dollar waste-plastic recycling market

4. Core Product Lines ReNewWorks: AI- powered Waste- to-Product Construction & Composite Tiles Non- structural tiles from composite mix of hard- to- recycle plastics and mineral fillers. Street Tiles Interlocking Pavers Decorative Interior Recycled-Plastic Footwear Components such as upper soles and filaments through extrusion and molding of recycled plastics. Upper Soles Filaments B2B Supply Stationery & Home Goods Eco- friendly consumer goods using recycled paper pulp and plastics. Notebooks Pen Holders Desk Organizers Office & Retail Furniture Durable, weather- resistant furniture from composite boards made of recycled plastic. Benches Display Racks Tables Corporate Eco- Hampers Bundled stationery, small decorative tiles, and other eco- home items into branded gift hampers. Stationery Tiles CSR Gifts Intelligent Waste Management Subscription- based SaaS solution to optimize waste collection and processing through AI. AI-Powered Sorting Route Optimization Partner Dashboards  Target Blended Gross Margin 45–60% All product lines collectively once AI- driven processes are optimized to reduce waste and improve yield. Page 4 of 10

5. Operational Workflow ReNewWorks: AI- powered Waste- to- Product Startup Key Process Benefits AI- driven sorting reduces contamination from 15% to less than 5% Dynamic route optimization reduces fuel consumption and emissions by up to 30% Process optimization maximizes material efficiency and yield Reverse Vending Machine (RVM) for incentivized waste collection AI Integration at Every Stage Collection Optimization Predictive analytics identify optimal RVM locations and incentive rates Computer Vision Sorting Deep learning models distinguish between different polymers, colors, and brand labels Process Optimization "Digital twin" of manufacturing process creates closed-loop optimization Quality Control AI-powered visual inspection detects surface flaws and dimensional inaccuracies Collection & Incentivization Waste collected from households, businesses, and public spaces through pickups and Reverse Vending Machines (RVMs). Inbound Sorting Initial manual sorting at collection hubs, then optimized transport to the Material Recovery Facility (MRF). Automated Processing AI- powered sorting with computer vision systems identifies materials with 95% accuracy. Materials undergo washing, shredding, and drying. Manufacturing & Upcycling Processed materials become feedstock for product lines: composite tiles, footwear components, stationery, and furniture. Quality Control & Finishing AI- powered visual inspection scans for defects. Products are finished and packaged using sustainable materials. Page 5 of 10 Sales & Distribution Multi- channel sales through e- commerce, B2B partnerships, and corporate gifting programs. AI forecasts demand for optimized production.

6. AI Architecture & Implementation ReNewWorks: AI- powered Waste- to- Product Startup ReNewWorks integrates a proprietary AI platform that transforms operational data into actionable insights, driving efficiency and profitability across the entire waste- to- product value chain. Collection Optimization Uses predictive analytics to identify optimal locations for RVMs and smart bins. Dynamically adjusts incentive rates to meet collection targets and manage feedstock costs based on real- time supply and demand data. Computer Vision Sorting Employs deep learning models trained on millions of images to achieve real- time, high- accuracy identification of materials. Can distinguish between different polymers (PE, PP, PET, PVC), colors, and brand labels. Process Optimization Leverages machine learning to create a "digital twin" of the manufacturing process. By analyzing sensor data from machinery, the AI optimizes parameters like temperature and pressure to maximize yield. Demand Forecasting Analyzes historical sales data, market trends, and external factors (e.g., construction cycles, festival seasons) to predict demand for different product lines, enabling optimized production planning. Quality Control Implements AI- powered visual inspection systems that automatically detect surface flaws, dimensional inaccuracies, or color inconsistencies in finished products, triggering reject or repair decisions. Dashboard & Reporting Provides partners with a SaaS dashboard offering real- time data on waste diversion rates, tonnes collected, and CO ₂ emissions avoided. Internally, it offers comprehensive dashboards for inventory management and operational efficiency. AI Integration Ecosystem Page 6 of 10

7. Go- to- Market Strategy ReNewWorks: AI- powered Waste- to- Product Startup Three-Phase Implementation Plan Phase 0: MVP & Pilot Months 0- 3 Objective: Validate collection model & initial product- market fit Finalize pilot city & secure partnerships Deploy 2- 4 Reverse Vending Machines Begin pilot production of composite tiles Phase 1: Local Scaling Months 3- 12 Objective: Achieve operational break- even & establish local brand Expand to 50 housing societies & 15 commercial establishments Launch e- commerce storefront Secure 2- 3 corporate gifting contracts Phase 2: Enterprise Expansion Months 12- 36 Objective: Become a key sustainable waste management partner Expand plant processing capacity Secure enterprise- level contracts with construction firms Engage municipalities for IWM services Marketing Channels Community Engagement Collection drives in apartment complexes & educational institutions Social Media Showcasing upcycling process through engaging content CSR Outreach Engaging corporate CSR heads with free pilot eco- hampers Content Marketing Publishing impact metrics & thought leadership content Key Performance Indicators Operational KPIs Tonnes collected/month Recovery rate (%) Product yield (%) Financial KPIs Revenue per tonne Customer acquisition cost Blended gross margin Environmental KPIs Landfill diversion CO ₂ e avoided/month Jobs created Break- even Target Based on pilot phase OPEX of ₹ 1.8 Lakh/month, blended gross margin of 50%, and average selling price of ₹ 300 per item, we need to sell approximately 1,200 items/month to cover operational costs. Page 7 of 10

8. Risk Assessment & Mitigation ReNewWorks: AI- powered Waste- to- Product Startup Feedstock Quality and Variability Inconsistent quality of post- consumer waste affects product quality and increases processing costs. Mitigation Strategies: AI-Powered Sorting: Computer vision systems to identify and segregate different polymer types with high accuracy Tiered Incentive System: Financial rewards for quality to encourage clean waste collection Supplier Education: Provide sorting guidelines and feedback to improve waste quality at source Equipment Downtime and Maintenance Specialized machinery failure can halt production, leading to revenue loss and missed delivery deadlines. Mitigation Strategies: Predictive Maintenance: IoT sensors and AI algorithms to forecast equipment failures Strategic Supplier Relationships: Strong SLAs with local OEMs for faster repair Operational Redundancy: Modular processing units to ensure continuous operation Market Price Fluctuations Volatile market prices for recycled materials and end- products can compress profit margins. Mitigation Strategies: Diversified Revenue: Multiple product lines and services to buffer against price volatility Long- Term Contracts: Fixed- price agreements with key B2B clients Value- Added Products: Focus on products with premium pricing less susceptible to market swings Regulatory and Compliance Hurdles Complex regulatory landscape including factory licenses and waste- handling permits. Mitigation Strategies: Proactive Regulatory Engagement: Early dialogue with all relevant government agencies Expert Consultation: Environmental consultants with proven experience in waste management Phased Product Certification: Align product rollout with regulatory requirements Page 8 of 10

9. Social & Environmental Impact ReNewWorks: AI- powered Waste- to- Product Startup Quantifiable Positive Outcomes Jobs Created Direct and indirect employment opportunities, with focus on: Local waste-pickers Women's self- help groups Landfill Diversion Total waste diverted from landfills: Post- consumer waste collection Processing waste into feedstock CO ₂ e Avoided / Month Greenhouse gas emissions reduction: Recycling vs. virgin production Landfill methane reduction Processing Impact 85%+ Recovery rate 5- 10 Tonnes collected/month 90%+ Product yield Measurable KPIs ReNewWorks tracks a balanced set of operational, financial, and environmental KPIs to demonstrate value to stakeholders. These metrics are crucial for quantifying our contribution to the circular economy and meeting regulatory targets. 12- Month Implementation Timeline Phase 0: MVP & Pilot (0-3 months) Month 0- 3 Month 3- 6 Month 6- 9 Month 9- 12 Month 12 Phase 0: MV P V a & l i P d i a l o t t e E c a o r l l y l e C c o t i l o l e n c t m io n o d & el a n L d o c i n a i l t S i a c l a p li n r o g du c E t n - m te r a p r r k i s e e t E f i x t p w a i n t s h i i o n n a S s c i a n l g e l R e eadiness city micro- c P a r t o c c h e m s s e i n n g t. Deploy 2- 4 Reverse Vending Machines and pilot production of composite tiles. Phase 1: Local Scaling (3-12 months) Scale collection and production capacity to serve a larger area within the initial city. Expand bulk collection services to 50 housing societies and 10- 15 commercial establishments. Phase 2: Enterprise Expansion (12-36 months) Scale through large- scale B2B and B2G contracts. Secure enterprise- level contracts with construction firms and developers for composite tiles and boards. Page 9 of 10