What you get
A clear picture of how AI shopping agents and crawlers see your catalogue right now -- what they find, what they miss, and what they get wrong -- plus a prioritised path to fix it. Then a site agents can navigate, parse, and act on, instead of skipping you because content is locked inside JavaScript, ambiguous markup, or incomplete product and pricing data.
When an AI agent compares options for a user, it picks the source that gives it clean, structured, unambiguous answers. If your competitor's site does that and yours doesn't, the agent recommends them. This is already happening.
When a customer asks ChatGPT, Perplexity, or a shopping agent for the best option under a budget or with specific constraints, the agent pulls from structured data, product descriptions, and schema markup. If your feed is messy or key attributes are missing, the recommendation goes elsewhere. There is no ranking report or click to inspect. The loss just happens upstream.
Most sites are built for humans clicking links. Agents need a different map: machine-readable structure, stable entry points, and clear answers instead of buried content. We wrote a step-by-step guide if you want to tackle this yourself.
How it works
- Crawl simulation -- we run your site and catalogue through the same pipelines AI agents use: structured data extraction, embedding-based retrieval, and tool-augmented search.
- Gap analysis -- we flag missing attributes, weak descriptions, broken structured data, and schema issues that make your products or pages invisible or misrepresented to AI buyers.
- Optimisation playbook -- prioritised fixes for product feeds, schema markup, and content, ranked by how many SKUs or pages they affect and how much visibility they recover.
- Agent entry point -- we add llms.txt at your root so agents know where to start: product, pricing, docs, policies, contact. One file, short and navigational.
- Machine-readable content -- Schema.org JSON-LD for products, offers, FAQ, and org info, plus clean catalogue attributes and product descriptions where needed. Agents stop guessing what a page is, what it costs, and which option fits the user's request.
- Callable interface -- if you want agents to book, quote, or check eligibility, we expose those actions via OpenAPI or MCP so agents can invoke them instead of scraping.
- Browser-agent readiness -- we fix the things that break headless browsing: heavy JS rendering, content behind client-side routing, modal popups, fragile selectors. Key pages get server-rendered; critical data lives in the initial HTML.
- Agent conversion assets -- comparison pages, decision aids, procurement pack (security, compliance, DPA links), plain-language pricing, FAQ with citable answers, and product pages that expose the details shopping agents look for. Agents prefer sources with unambiguous facts.
- Traffic policy -- rate limits that don't blanket-block automation, a documented way for tools to identify themselves, and monitoring that separates abuse from legitimate agent traffic.
Who it's for
SaaS, e-commerce, and marketplace teams that want agents to find them, understand them, compare them accurately, and complete actions (buy, book, get a quote, compare) without falling back to generic or wrong answers. Especially e-commerce teams that want to stay visible as discovery shifts from keyword search to AI-mediated search -- the window to get this right is still open, but it is narrowing.
Get started
Book a call and we'll audit how agents currently see your site -- then implement what they're missing.