Episode 18: Nishit Agrawal on AI, Innovation, and Food Supply Chain Challenges скачать в хорошем качестве

Episode 18: Nishit Agrawal on AI, Innovation, and Food Supply Chain Challenges

In this episode: Mo Echout and Steve Johnston sat down with Nishit Agrawal, Co-founder of SkoneLabs and Forbes 30 Under 30 honoree, to explore the intersection of AI, food tech, and sustainability. Nishit shares his journey in the AI space since 2015, his motivation behind founding SkoneLabs, and how the company is tackling one of the world's most pressing issues: food loss in the supply chain. We dive into the technical aspects of monitoring food quality, the importance of trust in the food industry, and the business models that support scalability. Nishit also reveals how data collection fuels AI innovation and how his solutions are shaping the future of sustainable food technology. 🌟 What You'll Learn: Nishit's journey into AI and food technology How SkoneLabs is addressing food loss through innovation Why trust is fundamental in the food supply chain How AI predicts spoilage by analyzing environmental factors The role of data collection in improving AI models Different business models for different customer needs The challenges of scaling food tech solutions Opportunities for AI across industries beyond food tech The impact of sustainability and future regulations 💡 Key Takeaways: Nishit has been working with AI since 2015 SkoneLabs focuses on minimizing food loss through AI and innovation Trust is the foundation of successful food industry solutions Data is the lifeblood of accurate and scalable AI models AI applications go far beyond food tech Building strong customer relationships is key to adoption Scaling food tech requires creativity and persistence Sustainability demands innovation in food technology 🔊 Sound Bites: "It's a beautiful day to be alive." "AI can do a lot of things." "Keep it short and simple." ⏱️ CHAPTERS: 00:00 – Introduction to AI and Innovation 03:30 – Nishit's Journey in AI and Food Tech 06:16 – Understanding Food Loss and Supply Chain Challenges 09:10 – Building Trust in Traditional Markets 12:04 – Technical Insights: Detection and Monitoring Solutions 14:49 – Business Model and Customer Engagement 17:36 – AI Tools and Data Utilization 20:29 – Differentiation in the Market 27:11 – Innovative Approaches in Development and Marketing 28:40 – Understanding Competitors and Market Needs 29:57 – Company Mindset and Unique DNA 31:23 – Challenges in Scaling and Growth 33:26 – Building a Strong Brand and Vertical Integration 35:10 – Establishing Industry Standards and Quality Monitoring 36:40 – Influencing Future Standards and Regulations 38:57 – Autonomous Solutions in Environmental Monitoring 40:22 – Future of AI in Business and Practical Applications 45:37 – Challenges in the Food Industry and Scalability 48:40 – Building Personal Networks and Trade Show Participation 🔑 Keywords: AI, innovation, food tech, supply chain, sustainability, machine learning, food loss, business model, data analysis, technology, Nishit Agrawal, SkoneLabs 👇 CONNECT WITH US & OUR GUEST: Mo Echout – Podcast Co-Host linktr.ee: [https://linktr.ee/Mohamed.Echout] LinkedIn: [  / mohamed-echout  ] X: [https://x.com/MEchout] Steve Johnston – Podcast Co-Host LinkedIn: [  / steve-johnston  ] YouTube: [   / @steveondigital  ] Website: [https://steveondigital.com/] Instagram: [  / steveondigital  ] Facebook: [  / steveondigital  ] Twitter: [  / steveondigital1  ] StemJee – Strategy & Digital Solutions: [https://stemjee.com/] Loreeya – Online Education Platform for Entrepreneurs: [https://loreeya.com/] Guest: Nishit Agrawal LinkedIn: [  / nishit-agrawal20  ] Website: [https://www.skonelabs.com/] 👍 If you enjoyed this episode, please LIKE, COMMENT, and SUBSCRIBE for more real stories and expert insights! Don't forget to hit the 🔔 bell so you never miss an episode! #AI #FoodTech #Innovation #SupplyChain #Sustainability #MachineLearning #Entrepreneurship #SkoneLabs #NishitAgrawal Thank you for watching! Share your questions and feedback in the comments section below.