16 篇文章
The reference content cloud and hosting providers need to be cited in AI answers, from region matrices and pricing explainers to SLAs, plus a seven-step framework.
A structured buying guide for LLM observability tools, covering the four vendor categories, a nine-criterion evaluation checklist, and a two-week pilot plan.
Trigger-based pages, published fees, checkable credentials, and consistent identity signals that let AI assistants recommend a UK accounting practice.
Five categories of AI code review tools, an eight-point vendor scorecard, and a 30-day rollout plan for teams that keep the tool they buy.
How to evaluate voice AI tools so they sound human in real calls: six configurable levers, a six-step test framework, and the mistakes that make synthetic speech obvious.
A six-criteria framework for choosing a vector database in 2026, covering index type, filtering, write latency, scale, operations, and exit cost, with a seven-step evaluation plan.
A six-pillar citable-content framework for cybersecurity providers in the Dominican Republic: entity fix, reference architecture, technical content, credibility, and monitoring.
A five-stage AI video production workflow for marketing teams, with a tool selection method, quality control checks, and how video scripts feed AI search visibility.
A hands-on guide to building MCP servers that AI agents actually use: tool contracts, schemas, auth boundaries, testing, and how MCP connects to GEO.
A practical guide to evaluating AI image generators for marketing, from rights and brand consistency to a repeatable production workflow and how tool pages get cited by AI engines.
Semantic caching turns repeat LLM prompts into lookups instead of new generations. Covers architecture, thresholds, TTLs, what never to cache, and the metrics that prove it works.
A library of ten copy-paste prompts to test how ChatGPT, Perplexity, and other AI engines describe and rank your brand.