Presented by Rezolve AiWhen an AI assistant recommends a product or brand, it generates something valuable: a purchase-ready consumer with high intent and low friction in their decision. That consumer has already compared options, asked follow-up questions, and arrived at a conclusion. They want to buy.What they encounter next is a commerce infrastructure that was not designed for them.The gap between recommendation and purchaseThe typical enterprise commerce stack was built for a specific model: a consumer who arrives at a brand's website through search or a direct link, navigates product pages, adds to cart, and completes checkout through a multi-step form flow. That model assumed the consumer would do the work of bridging their intent to the transaction. Most commerce systems still [...]
The modern customer has just one need that matters: Getting the thing they want when they want it. The old standard RAG model embed+retrieve+LLM misunderstands intent, overloads context and misses fre [...]
Here is a scenario that should concern every enterprise architect shipping autonomous AI systems right now: An observability agent is running in production. Its job is to detect infrastructure anomali [...]
For more than two decades, digital businesses have relied on a simple assumption: When someone interacts with a website, that activity reflects a human making a conscious choice. Clicks are treated as [...]
American Express (Amex) is building a system that lets AI agents shop and pay on behalf of users — but right now it’s only within its own payment network, and still involves a black box that could [...]
Microsoft assigned CVE-2026-21520, a CVSS 7.5 indirect prompt injection vulnerability, to Copilot Studio. Capsule Security discovered the flaw, coordinated disclosure with Microsoft, and the patch was [...]
When Cisco ran 6,986 multi-turn attacks against 15 flagship models, attackers who adapted across the conversation broke through as often as 88.3% of the time. Amy Chang, Cisco's head of AI threat [...]
AI coding agents are rapidly accelerating data engineering by generating transformations, pipelines, orchestration workflows, validation tests, and infrastructure configurations from prompts. However, [...]
Gen AI in software engineering has moved well beyond autocomplete. The emerging frontier is agentic coding: AI systems capable of planning changes, executing them across multiple steps and iterating b [...]