A tech stack detector for technographic prospecting
Identify technologies behind any website.
The Kavex tech stack detector tells you what a website is actually built on, its CMS, frameworks, analytics, marketing tools, hosting and payment integrations. For sales teams that sell into a specific stack, that is the difference between a relevant pitch and a cold guess. Hand it one URL or a whole list and it returns a clear technology profile per site. You pay per URL checked, so qualifying a list stays cheap.
A RUN OF 1,000 URLS ON THIS SOURCE, AT 1 PER URL
Six columns on every row.
These come with the run and cost nothing extra. Add-ons widen the same sheet, and you pay only for the ones you switched on.
| URL | CMS / builder | Framework | Analytics | Ecommerce | Hosting |
|---|---|---|---|---|---|
| northstudio.nl | Webflow | · | GA4 | · | AWS |
| brightlabs.co | WordPress | · | GA4, Hotjar | WooCommerce | Cloudflare |
| varzace.de | Next.js | React | Plausible | · | Vercel |
| pixelforge.io | Shopify | · | GA4 | Shopify | Shopify |
Say what you want. Read the price first.
Everything else is a ceiling or a filter. The estimate moves with the numbers you type, so the run never surprises you at the end.
The tech stack detector fingerprints a website by reading the signals every site leaves behind, response headers, script sources, markup patterns, cookies and meta tags. From those it identifies the technologies the site runs and groups them into categories you can filter on.
It covers the stack that matters for prospecting: the CMS or website builder, the JavaScript framework, analytics and tag managers, marketing and chat tools, ecommerce and payment providers, the CDN and the hosting platform. Each detected technology is returned in its category so a row is easy to scan.
Run it across a list and it becomes a qualifying tool. Instead of researching sites one by one, you get a spreadsheet that tells you at a glance which prospects are on the platform you integrate with and which are not worth a call.
Detection is most valuable as a filter. On its own a single technology profile is a curiosity; across a list it becomes a scoring column. Sort a raw lead list by CMS to find every Shopify store, or filter to the accounts running a marketing tool you integrate with, and a vague territory turns into a ranked set of real fits. The detector also flags the absence of a technology, which is its own signal, a company with no analytics or no modern framework is often the one most open to a pitch. Run it early in qualification and the rest of your outreach effort lands on accounts that were worth contacting in the first place.
The tech stack detector fetches each page live and inspects what the browser would see, the HTTP headers, the scripts the page loads, inline markup, cookies and DOM patterns. Each technology has a signature, and the detector matches those signatures against the page to build the profile.
Because every check is live, the tech stack detector reflects what a site runs today, including a platform a company migrated to last week. Sites that block plain data-centre requests are reached through rotating residential proxies, so a list of real prospects comes back complete rather than half empty.
Charged per delivered row. If the source holds fewer than you asked for, the rest of the credits go back to your balance the second the run ends.
One thousand urls, itemised.
One line, because this source has nothing bundled on top. You pay the rate times the rows the run actually delivered.
| Line | Rate | Units | Credits |
|---|---|---|---|
| Tech Stack | 1 / url | 1,000 urls | 1,000 |
| 1,000 urls | 1 / url | 1,000 credits | $1.00 |
$0.001 PER FINISHED URL · ONLY DELIVERED ROWS ARE BILLED
What people point it at.
Four ways this source is used today. Every one of them is the same run, the same export and the same credit pool.
- SaaS sales teams finding every site running a specific platform, for example anyone on Webflow, Shopify or HubSpot.
- Agencies auditing a list of prospect or competitor sites to spot outdated or mismatched stacks.
- Partnerships teams identifying companies already using a complementary tool worth integrating with.
- SDRs filtering a raw lead list down to the accounts whose stack makes them a real fit.
The rest of the web, contact & ai stack.
Same credit pool, same export. Chain the output of one run into the next without paying for the list twice.
Asked before the first run.
Short answers, no accordion to click through. If something is still missing, the help pages go deeper.
What categories of technology does it detect?
It covers the CMS or site builder, JavaScript frameworks, analytics and tag managers, marketing and chat widgets, ecommerce and payment tools, the CDN and the hosting platform, the layers that matter most for qualifying a prospect.
How accurate is the detection?
Detection is based on signatures a technology genuinely leaves in the page, so confirmed tools are reliable. A site can still hide a server-side tool that leaves no client-side trace, so treat the profile as what is observable from the page.
Can I check a whole list at once?
Yes. Upload a list of URLs and the detector profiles each one, returning a single CSV you can filter by any technology column.
How do results export?
Results download as a CSV with one URL per row and a column per technology category, so you can sort or filter your list down to the stack you care about.