How Intelligent Agents Are Redefining the Role of Human-Centred Design in E-Commerce The brief was simple: “Improve the product detail page experience and reduce bounce rate by 15%.” The UX designer opened her laptop, loaded the analytics dashboard, and prepared for the usual hours of work
A Behind-the-Scenes Look at Real-World Agentic Automation in Modern E-Commerce In the age of algorithmic personalisation, one team still fought battles with spreadsheets, browser tabs, and Monday morning checklists: the merchandising department. This is the story of how one retail brand — a fashion marketplace with
For years, software was built stateless by design — every request independent, every session short-lived, every system reloaded from scratch. It was reliable, scalable, and sufficient. Then came AI agents. Suddenly, statelessness became a liability. At Vortex IQ, as we moved from simple prompt-based assistants to
AI agents that act without remembering are just autocomplete tools in disguise. At Vortex IQ, we’re building agents that don’t just respond — they observe, learn, and adapt over time. To do that, they need memory: not just short-term “context windows” but a structured, persistent memory
As AI agents shift from research novelty to real-world utility, one truth is becoming crystal clear: the future isn’t just LLM-ready — it’s agent-ready. But to fully unlock that future, we need more than intelligent models. We need a new breed of APIs. APIs that aren’t
Building AI agents that “do things” is easy. Building agents that keep working—despite API changes, timeouts, data corruption, and unforeseen user behaviour—is a completely different challenge. At Vortex IQ, we’ve built and deployed AI agents across 10,000+ real-world production tasks for BigCommerce, Shopify, and StagingPro. And
In a world where AI agents are expected to perform meaningful work—beyond chat and search—the hidden layer that determines success is infrastructure. At Vortex IQ, we’ve architected our entire platform around a single core principle: APIs first. Everything else second. Why? Because if agents are to
At Vortex IQ, we often get asked: “How does your platform turn a single natural language prompt into a fully autonomous AI agent that runs real workflows?” It’s a fair question. Because what sounds simple on the surface—“update all product prices by 10% if the stock
When people hear “multi-agent system,” they often imagine sci-fi-style AI collectives solving big problems. In reality, most AI agents today are solitary, isolated functions—smart, but siloed. At Vortex IQ, we’ve taken a different approach. We believe the real power of AI agents comes from coordination, not
AI agents are having a moment. From developer demos to VC decks, the idea of autonomous systems that can reason, act, and execute across software is everywhere. But once you leave the prototype stage, reality sets in. At Vortex IQ, we’ve built, deployed, and managed AI
When we first launched the Vortex IQ Agent Framework, our goal was simple: turn fragmented API access into intelligent, autonomous workflows. Fast-forward to today, and we’ve successfully deployed over 10,000 agent tasks across real-world e-commerce operations—automating everything from SEO enhancements and backups to product updates and
In the race toward AI-first platforms, we often hear the term “agentic AI” tossed around—usually with an image of a chatbot that can “do more” or a plugin system wrapped in prompts. But what does agentic actually mean? And more importantly, what makes an AI system