Upgrade service · for technical product companies

Your catalog is invisible to AI agents.

Technical buyers now do most of their research inside ChatGPT, Claude, and Perplexity — not Google. Your products, buried in PDFs and behind login walls, can't be found or cited. We make them legible. Measured, not promised.

Your page today
<div class="wrapper"><div class="row"><span style="font:14px/1.5 -apple-system"><a href="/p?id=ct8000&ref=nav&utm=hdr"><b>Hall</b> Sensor</a></span><div class="px-4 py-2 flex items-center gap-2"><svg viewBox="0 0 24 24"><path d="M3 12h18M3 6h18M3 18h18"/></svg><span class="badge">NEW</span></div>…
~64,699 tokens
After aireadify
# CT8000 3D Hall sensor
range: ±40 mT
interface: I²C / SPI
replaces: TLE493D
~1,093 tokens · citable

Cloudflare tells you you're not agent-ready. We make you agent-ready in 2 weeks.

The shift

The buyer moved inside the model. Your site didn't follow.

This isn't a fad cycle like crypto or the metaverse. Buyer behavior already changed — the demand is real, and your catalog is on the wrong side of it.

60%

of B2B research now happens inside an LLM before a vendor is ever contacted.

−30%

Google click-through on technical queries since AI Overviews shipped.

39/100

what a major chipmaker's public site scores on agent-readiness today.

42

average score across the 106 chip companies we scanned.

Three things, on your site

One transformation. Built for humans and agents at once.

Competitors ship a chatbot and stop. The chatbot is the easy third. The hard part is being machine-readable and citable.

01for humans

Chat widget

Embeddable chat for visitors. Natural-language part search across your whole catalog — and every spec it returns cites the datasheet line it came from.

02for agents

MCP server

One MCP endpoint per tenant. ChatGPT, Claude, and Cursor pull structured specs directly — search_parts, get_datasheet — no scraping, no guessing.

03for crawlers

llms.txt + schema.org

Generated llms.txt, llms-ctx.txt, and schema.org Product markup. So Perplexity and the rest recognise your catalog when they crawl it.

How it works

Audit, transform, measure — done for you.

01

Audit

We scan your site for crawlability, schema, llms.txt, and MCP. You get a graded report and a fix list, ranked by weight.

02

Transform

We extract your datasheets, generate llms.txt, deploy the MCP server, and embed the chat widget. All of it, done for you — in about two weeks.

03

Measure

Real-time analytics on what agents and customers actually ask. Wrong answers become test cases. The portal improves from data, not guesswork.

Case

CONNTEK: a 60-product magnetic sensor catalog, from 39 to 78 in six weeks.

Design partner #0. Datasheet extraction, cross-category use-case retrieval, a 92% citation rate and 94% token savings. Full case study coming soon.

Pricing

A fixed price. No A, no fee.

Three packages on the pricing page. Ongoing maintenance continues as the AI-Native Portal at $300–1,500 / month.

See upgrade pricing →

Start

Send us your product catalog URL.

We only scan websites you own or explicitly authorize. For a first look, run Cloudflare's public scanner yourself and send us the result.

Email us