aaireadify
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Coming Q3 2026 · private alpha
AI-native portal for technical products

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.

Run a free scan → See how it works
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 hover:bg-gray-50"><svg viewBox="0 0 24 24" fill="none" stroke="currentColor"><path d="M3 12h18M3 6h18M3 18h18"/></svg><span class="badge badge-new">NEW</span></div></div></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.

Start here · free

See your site the way an agent does.

We check 20 signals — robots.txt, llms.txt, MCP, structured data, content negotiation — and grade you 0–100. No signup. Public pages only.

Try one:

Behind a login wall? That's exactly what we handle. →

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.

Pricing

Free to find out. A fixed price to fix it.

Start with the score. Upgrade when the number isn't good enough.

Scan

$0
free

Find out where you stand

✓Agent-readiness score, 0–100
✓20-signal report + fix list
✓Token-waste estimate
✓No signup
Run a free scan

Transformation

Most chosen
$1,500–$5,000
one-time

From a failing grade to an A — or you don't pay

✓robots.txt, sitemap, schema.org
✓Generated llms.txt + llms-ctx.txt
✓MCP server, configured
✓Chat widget, embedded
✓We re-run the score and prove it
Book a transformation

AI-Native Portal

$300–$1,500
/ month

Keep it living

✓Customer console + YAML review
✓Datasheet → structured extraction
✓Multi-tenant chat + MCP, maintained
✓Analytics: quality, hot queries, funnel
✓Citation tracing
Talk to us

Vertical focus: semiconductors, electronics, industrial instruments.

Coming Q3 2026

Get on the list before alpha opens.

We're onboarding a handful of design partners first. Leave an email and we'll reach out when there's room.