From being named
to being chosen.
Sales and marketing support aimed at your customers' AI agents. We fix the prompts buyers use, measure your mention share every month, and keep correcting your company information and product data.
Run a free audit of your siteThe product information required
is growing dramatically.
An AI agent needs all the context a human buyer carries as tacit knowledge, too.
EC
AGENTIC
From competing for a ranking
to making the shortlist.
To process a request in the time it has, an AI needs structured product information.
How an AI knows your company,
and how it knows your products.
The two tracks can be run independently.
Corporate site · Brand
Business segments, technologies, certifications, plants and markets, put in a form an AI can read. If they exist only as prose on a page, the AI fills the gaps from pages outside your site.
- Structured data for the company and organisationNo visible change
- Rewriting the body of company information pagesVisible change
- Identifying and correcting external sourcesWe identify who is being cited
Product pages · Model numbers
Every specification held as attribute name, value and unit. Once a value can be read as a number, an AI can compare it directly against a condition like “4K 60p”.
- Embedding JSON-LDExisting pages stay as they are
- Attribute enrichment and vocabulary normalisationSplitting 4K/59.94p apart
- Compatibility tables and application guidesReplacing a competitor's model number
Catalogues for 6 brands across 36 files, converted into the formats specified by 4 consumer-electronics retailers. Output simultaneously to a different schema for every recipient.
More than 20,000 SKUs extracted from several catalogues spread across PDF and Excel files of over 200 pages, and converted into the specified format. Two months of work for six people, cut to two weeks.
Product catalogues of more than 10,000 items from 26 suppliers, extracted, merged and converted into each customer's own listing format.
The trial covers
one representative product line.
We structure the specification sheets of one representative product line, as they are.
Measure and correct
until you are mentioned.
Every month we run a fixed set of prompts and line up the share of answers that name you, against the same denominator as the competitors you specify. We identify the weak prompts and choose the remedy by cause.
- When your own data is insufficient
- Extend the data embedded in JSON-LD
- When other domains are cited heavily
- Propose outreach to the sources being cited
A value with no source
is never entered.
Every piece of source data is accounted for
All data is sorted into “captured” or “needs review”. The silent loss of data that a general-purpose AI can produce is ruled out structurally.
Every cell traces back to the original
Extracted data is tied to the exact place it came from, such as the page of a PDF. A cell whose source cannot be proven is refused.
The same input gives the same output
Conversion runs LLM-generated rules as deterministic code, behind three approval gates: schema approval, sample approval and final review.
How do your site and products look
to your customers' AI?
Send us a URL and we show you an instant report on the spot, scoring what can be verified from public information. A full report, including a comparison with competitors, can be requested free of charge.
