$600 Fullstack Live Event Free With a Membership!
AI creates value only when it moves beyond experimentation and becomes part of real operational workflows. This Fullstack Live Event shows how to transform messy enterprise data into measurable decisions, evaluate agentic AI systems with confidence, and deploy production-ready models across cloud and browser environments.
Learn how to operationalize AI with practical architectures, rigorous evaluation strategies, and modern deployment techniques that turn intelligent systems into scalable business assets.
Moving AI into production requires more than model access. It demands structured pipelines, trustworthy evaluation, and efficient delivery architectures that perform reliably in real-world environments.
In this event, leading practitioners share actionable strategies for structuring unstructured data, testing complex agentic applications, and running advanced AI models directly in the browser without cloud dependencies. You will gain practical insights for building secure, efficient, and measurable AI systems that scale.
Learn how to transform unstructured enterprise data into measurable business outcomes. Discover practical patterns for data ingestion, retrieval pipelines, summarization, workflow automation, and human-in-the-loop systems that turn AI into a reliable operational asset.
Move beyond guesswork and learn how to evaluate agentic AI systems with rigor. Explore strategies for benchmark creation, regression detection, LLM-as-judge pipelines, and human validation workflows to ensure trust, reliability, and production readiness.
Discover how to run LLMs, image models, and speech AI locally in the browser using WebGPU, WebNN, WebAssembly, and Gemini Nano. Learn how to build fast, private, and cost-efficient AI-powered applications without relying on cloud infrastructure.
AI Engineers who want to build scalable production pipelines for intelligent systems
Software Developers who want to deploy browser-based AI applications without cloud overhead
ML Practitioners who want to improve LLM evaluation, testing, and reliability
Technology Leaders who want to turn AI initiatives into measurable business outcomes
turn unstructured business data into production-ready AI workflows
evaluate agentic LLM applications beyond intuition and manual testing
deploy LLMs, vision, and speech models directly in the browser
build secure, scalable AI systems with measurable performance
Apurva Misra
Expert in: AI automation, enterprise ML systems, operational AI strategy
Rushabh Mehta
Expert in: LLM evaluation, AI infrastructure, privacy-preserving ML systems
Maximiliano Firtman
Expert in: browser-based AI, web performance, modern web application architecture