Vikas Agarwal

Smarter Journeys Begin With AI in Retail Bots AI is everywhere in retail - but is it truly working for your brand, or just checking a box? At CrossML Pvt Ltd, we built a next‑gen AI Customer Support Bot that does more than talk: it thinks, learns, and sells - all while staying budget- and system-efficient. It’s turning support into sales, automation into loyalty, and casual chat into genuine growth. Why retailers - fast-growing and established - are betting on AI bots: -91% of retail IT leaders aim to make AI their top tech investment by 2026. -GenAI chatbots drove a 15% boost in Black Friday conversions . -60% of shoppers noticed better forecasting and inventory with AI retail tools . -By 2025, 85% of retail interactions will be fully automated. AI-powered support yields a 25% increase in customer satisfaction . 🛠️ How Our Bot Drives Smarter Journeys 1. Conversational AI that Feels Human & Converts Built with GPT‑4, Gemini & LLaMA - understands tone, intent, context, and nudges cart abandoners seamlessly. Impact: 63%+ retailers saw conversion gains, 55% saw higher average order value . 2. Seamless Backend Integration Connects Shopify, WooCommerce, CRMs, POS, loyalty & delivery APIs - provides real-time, personalized support. 3. RAG-Powered Real-Time Accuracy Fetches live data to answer so there’s never outdated or inaccurate info - drastically reduces hallucinations. 4. Empathy at Scale with Sentiment Analytics Our dashboard tracks neutral-to-negative sentiment and flags chats needing human attention - balancing speed with emotional intelligence. 🚀 Real-World Results ✅ 50% faster first responses during peak events ✅ 18% lift in daily sales through personalized recommendations ✅ 20% lower support operating costs ✅ 30% drop in repetitive queries ✅ 25% higher CSAT scores 🔮 What’s Next for Retail Bots - Voice & Visual Interactions - think kiosks, in-store voice support, and image-based assistance. True Omnichannel Presence - across live chat, email, WhatsApp, and more. Industry-Specific AI Modules - tailored to fashion, electronics, beauty, grocery - with domain logic built-in. Predictive Support - anticipating issues, identifying churn, and initiating outreach before customers even ask. At CrossML, our AI bots aren’t just hype - they’re built for real-world impact. If you’re a CTO, Founder, or AI Lead ready to elevate your retail strategy, let’s connect. Let’s make AI work smarter - for you and your customers. #RetailAI #CustomerExperience #ConversationalAI #GenAI #RAG #Omnichannel #CloudNative #CrossML

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When we started Fynd in 2012, retail was deeply fragmented. Inventory, orders, and customer data lived in separate systems, and brands were forced to operate without a unified view of their business. We began by solving this challenge. Over time, integration became the baseline. The real opportunity was building a single operating layer across catalogue, inventory, logistics, and customer experience. Not just systems that connect, but systems that coordinate. Today, AI is accelerating that shift. For me, its value is not in dashboards or surface features. It lies in intelligent execution, predicting demand, automating workflows, personalising journeys, and reducing operational issues at scale. As we expand into markets like Middle East and UK, I am reminded that these challenges are universal. Brands everywhere are navigating complexity and disconnected systems. What they need are coherent platforms with intelligence embedded at the core, not layered on later. I recently spoke with Neil Ainger at Retail Technology Innovation Hub about this journey, our global expansion, and how I think about AI-powered unified commerce. Scott Fynd Farooq Ronak Ragini Salman Jigar Kushan Aditi Nanditha Rixon Pinto Vipul

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Titles don’t define progress. Responsibilities do. I’ve taken on the role of AI-Powered Chief Learning Architect at SarlaYash Learning Solutions LLP — not as a milestone, but as a responsibility to build, learn, and refine learning systems in real conditions. The work ahead is centered on: •Designing learning as an engineered system, not content delivery •Building AI-enabled frameworks that scale thinking and judgment •Creating future-ready skill pathways grounded in execution •Learning continuously by designing, testing, and improving systems in motion This role isn’t about having all the answers. It’s about asking better questions, structuring decisions, and learning by doing — at scale. The focus remains on translating intelligence into capability, and capability into long-term impact. Kapil Narula EVANS KOSGEI KisoByte Solutions #LearningArchitecture #AISystems #SystemsThinking #FutureReadySkills #Leadership

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🤝 Mentorship in Action After my last post on unlearning old skills to grow as a leader, a few people asked what I did keep through those transitions. For me, the answer is simple — mentorship. It’s been the constant across every stage — and honestly, as much about learning as teaching. It reminds me of sports: even the best athletes have coaches, not because they lack skill, but because great coaching builds perspective and resilience. Mentorship does the same for teams — it brings out their best. Early on, I thought mentorship was about giving answers. Over time, I learned it’s about creating space for others to find their own. Now, seeing someone I’ve coached step into leadership is the most rewarding part of the journey. As my org grew, mentorship evolved into a different kind of conversation — connecting with people several layers away. That’s where skip-levels started changing how I lead. More on that soon. ⸻ #Leadership #Mentorship #Growth #CareerJourney

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This was an awesome chat with Deepak Chhugani where we did a deep dive into how Nuvocargo is leveraging AI. We also discussed lots of topics like how B2B marketplaces often start off looking more like brokerages, how operationally complex marketplaces can leverage AI, taking the "full-stack AI" vs. vertical agent approach, early GTM strategies for B2B marketplaces, and more. This is a must-watch (or listen) for B2B marketplace founders and get ready to take some notes!

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AI Success Starts with Data Quality and Governance A recent TechCrunch article reinforces something many of us driving digital transformation in large organizations have learned firsthand: better-quality data, not just more data, is the real driver of successful AI initiatives (https://lnkd.in/eHR9kcXH). Companies like iMerit are showing that domain-specific, expert-labeled data consistently outperforms massive, loosely curated datasets. But that precision doesn’t happen on its own. To build trusted, explainable, and scalable AI systems, enterprises must pair high-quality data with strong data governance practices: 🛡️ Ensure compliance and auditability 🔍 Maintain data lineage and integrity 🔄 Support continuous validation and improvement 🔗 Align data with business context and use case From my experience leading digital transformation, I’ve seen how data governance transforms AI from a prototype into a platform, one that can be measured, trusted, and scaled. As organizations race to adopt AI, success won’t be determined by model complexity, but by how well you manage the data that feeds it. #AI #DataQuality #DataGovernance #DigitalTransformation #EnterpriseAI #ResponsibleAI #TechLeadership

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Glad to have had the opportunity to speak on “The Deterministic AI Era – Re-Architecting Enterprise Infrastructure for LLM Workloads.” The conversations at the summit reinforced a strong belief — enterprise AI success will increasingly be defined by deterministic, production-grade infrastructure, not experimentation alone. As AI moves from pilots to production, engineering discipline, cost control, and architectural clarity become the true differentiators. Thank you Accion Labs for organizing a thoughtful and well-executed summit, and for curating a platform where current AI advancements were explored in depth. Truly appreciate the engaging discussions and diverse perspectives shared throughout the event. Looking forward to continuing the dialogue. #AccionLabs #InnovationSummit2026 #EnterpriseAI #LLMInfrastructure #AIEngineering

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We have build some crazy ML/AI/Voice/Non-Voice automation stack in last 1 year. We are working some of the biggest names in industry and able to handle more than 15M voicebot calls in a day. 🚀 🚀

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Is there a point to these posts on Hawa Mahal and “ancient climate solutions”? I’m struggling to see it. If the point is “go back to our roots”, that idea has been repeated endlessly — and ignored just as consistently. At some stage, it’s worth asking: Is the idea incomplete, or is it simply impractical at scale? Also, there’s nothing uniquely Indian about this. People across geographies have always adapted to their environments: - Desert regions developed passive cooling - Arctic communities built for extreme cold - Tropical regions designed for heavy rainfall Humans solve for time and place. But times have changed. We now have: - Urban density at an unprecedented scale - Resource constraints very different from the past - Expectations of comfort that didn’t exist earlier - And importantly, structures like Hawa Mahal were built for a tiny, privileged section of society — not something that can be generalized for millions. If the goal is to drive change today, the conversation needs to move from “look at what royalty built centuries ago” to “what scalable, modern solutions can work for today’s realities.” Otherwise, it remains an interesting history lesson — not a practical direction.

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