The same product intelligence that answers the question also brings people to it
We normalize your catalog into a product intelligence layer. That one layer gets you found, converts what arrives, routes each conversation to the right outcome, and tells you what your content is missing.
Get found, convert what arrives, route it, learn from it
Four stages, one product intelligence layer underneath all of them. The order matters, because each stage depends on the one before it.
Bring more people to the website
Two things move here: AI visibility and search visibility. Both are downstream of having accurate, structured product content for engines to find and cite.
Give us the set of prompts you need to be optimized for, and we generate the right content from the product information we already hold, grounded in your real specifications rather than written around them.
This is the part most content programs get backwards. The reason a competitor gets cited is not that they wrote more; it is that what they published was structured for a machine to use.
Give them a real experience when they land
Deployed on your marketing site, the agent takes a customer’s high-level requirement, breaks it down and points them to the right solution.
Behind a single conversation it may call ten different tools, working against a normalized product catalog, which is why the recommendation comes back accurate rather than merely plausible. We have done this repeatedly across customers, and it produces both a good experience and real conversion.
Deal velocity improves too, because the buyer arrives at your sales team already narrowed down.
Route the conversation to an outcome
Dynamic routing decides what each conversation becomes. It can escalate as a customer success ticket, or create a lead with the customer’s intent clearly identified.
That second one is the difference between a form fill and a qualified opportunity. The lead arrives with the requirement already articulated: what they are building, what they need, and what the agent recommended.
Learn from all of it
The analytics dashboard is extremely customizable, and it surfaces product gaps and content gaps based on what people asked.
We use it to continuously improve the platform, and you use it to decide what to write next. The site gets better every month instead of decaying between redesigns.
Why it all runs on one layer
Content, on-site experience and lead quality are usually three separate vendors that know nothing about your products. Here they are three outputs of the same thing.
Your technical documentation
Datasheets, catalogs, application notes, support history and schematics, including the diagrams most systems discard at ingestion.
Into a product catalog
Structured, queryable and consistent across product families, which is what makes an accurate recommendation possible.
Content, conversation and routing
The same layer generates the content that gets you found, powers the conversation that converts, and classifies the intent that routes.
Taoglas runs a public AI product recommendation experience. Qorvo runs the agent on their main site. Critical Link runs it in the site search bar. Bay Supply runs a full selection-to-quote experience on their storefront.
Common questions from marketing leaders
Is this a chatbot?
No, and the difference is worth being precise about. A chatbot retrieves from a help center. This reasons over a normalized product catalog, calls tools during a single conversation, and returns a recommendation with the reasoning shown. The output is a decision, not a link.
How does the content generation work?
You tell us the prompts and queries you want to be found for. We generate content grounded in the product information we already hold, real specifications, real part data, rather than writing around the topic. That is what gives an answer engine something worth citing.
What does the lead look like?
It arrives with the intent identified: what the buyer described, what was clarified, and what was recommended. Your sales team opens it already knowing the application, which is the difference between a form fill and a qualified opportunity.
Who owns this internally, marketing or IT?
Marketing owns the outcome and usually buys it. IT is generally involved on deployment and data access, and on manufacturer sites they are sometimes the buyer instead. Both paths are normal.
What happens to the analytics we get back?
It is yours to act on and we work through it with you. Document gaps become a content backlog, and query themes tell you what your buyers are trying to do, which is usually more useful than any keyword report.
Related
Start with your product pages
We’ll ingest your public documentation, put a selection agent on a section of your site, and show you what visitors ask when they can finally ask properly.
SOC 2 Type II · Every answer traceable to its source