Mayank Aggarwal is the Co-founder & CEO of evolvue AI, and also leads strategic AI consulting initiatives at CreateHQ Consulting, where he helps organizations harness the transformative power of AI across verticals. With over 7 years of experience spanning industry, research, and academia, Mayank has established himself as a voice in applied machine learning, data engineering, and large-scale AI system design.
Previously, Mayank has held impactful roles at companies like Goldman Sachs, OYO Rooms, MindTickle, and iNeuron Intelligence, where he contributed to building production-grade ML pipelines, scalable data platforms, and intelligent automation systems. His work ranges from deep learning and big data infrastructure to LLMOps and generative AI applications.
As a passionate educator with over 5 years of teaching experience, Mayank has taught 100K+ students globally through platforms like YouTube, Udemy, and live bootcamps. His teaching spans Python, Data Science, Generative AI, and Full Stack Machine Learning, with a focus on simplifying complex concepts for real-world adoption.
In addition to his industry and teaching experience, Mayank also has a strong research background at IIIT-Delhi, having worked on projects in natural language processing, deep learning, and responsible AI. He frequently mentors professionals and startups on topics like AI system architecture, MLOps, and product-oriented AI development.
Get ready for a high-stakes AI face-off as three leading multi-agent frameworks - AutoGen, CrewAI, and LangGraph, go head-to-head solving the same real-world AI problem: Building a Multi-Agent Helpdesk AI Assistant.
Watch top Agentic AI practitioners demonstrate how each framework tackles this challenge: from structuring agent teams to orchestrating decisions across multiple steps. This unique session combines live hands-on demos and a panel discussion. You’ll walk away with a clear view of what each framework does best, where they struggle, and how to pick the right one for your next Agentic AI project.
Read MoreIn this hands-on session, we’ll explore how no-code automation platforms—especially the open-source tool n8n—can be combined with powerful AI agents to build intelligent, production-ready workflows.
Whether you’re a data professional, developer, or automation enthusiast, this session will demystify how you can go from a manual task to a fully orchestrated AI-powered agent-all without writing full applications.
With a blend of humor, visual storytelling, and real-world case studies, we’ll walk through building an AI Literature Review Assistant using AI agents and no-code automation.
We’ll dive deep into: - The automation landscape (Zapier, Make, Bubble, n8n) - What agentic AI means, from basic bots to AutoGPT-style workflows - How n8n enables flexible AI orchestration - How to design and run autonomous AI workflows using visual tools
By the end of this session, you’ll understand how to design agentic AI workflows that use LLMs, APIs, and no-code builders to automate even research and decision-heavy processes.
Read MoreManaging and scaling ML workloads have never been a bigger challenge in the past. Data scientists are looking for collaboration, building, training, and re-iterating thousands of AI experiments. On the flip side ML engineers are looking for distributed training, artifact management, and automated deployment for high performance
Read MoreManaging and scaling ML workloads have never been a bigger challenge in the past. Data scientists are looking for collaboration, building, training, and re-iterating thousands of AI experiments. On the flip side ML engineers are looking for distributed training, artifact management, and automated deployment for high performance
Read More