Tabstack Structured Extraction - Extract web data into structured JSON, no scraper required.
Define a schema, pass a URL, get back JSON that matches. Tabstack's extract endpoint turns any web page into structured output, no parsing code and no LLM call to maintain. generate endpoint adds AI instructions for reasoned answers, not raw fields. Both enforce your schema on every call, even when the page changes. Tune speed with effort levels, target any country with geo_target. Mozilla-backed: your data is never sold or used to train models. 10,000 free credits to start.
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Tabstack by Mozilla
There's one piece of code that gets rebuilt at almost every company: the layer that turns a web page into data you can actually use. Fetch, parse, clean, pipe it through an LLM, force it into the shape you wanted. Nobody wants to own it, and it breaks the second a page changes.
That's the thing we deleted.
With Structured Extraction you define the schema, pass a URL, and get JSON back that matches. The reasoning happens inside the call, so there's no parsing code and no second LLM step bolted on after. `extract` pulls the fields you define. `generate` adds instructions on top when you want a reasoned answer, not just raw values.
It's built inside Mozilla, which matters here: the pages we fetch and the data you send are never sold or used to train models.
Get started for free with 10,000 credits →
I'd love to know what you're stuck extracting right now: the messy site, the SPA that fights you, the schema that never holds. Drop your extraction struggle below.
The structured output part is what stood out to me. Getting data is usually easy, keeping it reliable when websites change is the hard part. How often schemas need to be adjusted in real world use?
Tabstack by Mozilla
@busra_seker1 exactly. Reliability is where Tabstack shines in that regard.
Stripo.email
Congrats on the launch! 🚀 Defining a schema and getting structured JSON back without maintaining scrapers sounds like a huge time saver for developers.
Tabstack by Mozilla
Thanks for the support, Alina! Help us spread the word on LinkedIn, repost this
Tabstack by Mozilla
ZapDigits
This is amazing. I wanna build something around this. The browser automation part seems like a game changer. One question: I see there is 10k credits on the free trial . Is there a time limit?
Tabstack by Mozilla
ZapDigits
@tessak22 Amazing, will be working on it coming days. let's keep in touch.
Tabstack by Mozilla
@tessak22 @malithmcrdev looking forward to it!
Tabstack by Mozilla
@malithmcrdev absolutely! Let me know what you end up building, I'd love to hear about it.
Tabstack by Mozilla
@malithmcrdev thanks for the continuous support, Malith! let's spread the word on LinkedIn, repost this
I have been using Tabstack for quite some time and loving it :)
Tabstack by Mozilla
@natwar86 that's amazing! Feel free to provide us a review if you ship anything on Product Hunt! I would love to support your efforts across the board so reach out if I can help in any way.
A private-forward solution to a technical headache? I'm listening...;)
Tabstack by Mozilla
@mark_toubman2 exactly what I said when I was interviewing to join the team! Such an awesome win.
jared.so
Solid launch for Tabstack by Mozilla: Extract web data and automate browsers, no scraper required.. What was the hardest part to get right so far?
Tabstack by Mozilla
@borrellbr for sure the marketing! hahah. Nah, I'm just biased. We have had a lot of challenges from getting agents to navigate the web to ensuring we're great stewards of Mozilla's manifesto for data privacy and transparency. It's been a really fun adventure, though.
@srbiv might have something else to share here that could be fun to hear.
Tabstack by Mozilla
@borrellbr Great question, two things come to mind:
- Building a product that puts privacy first means we're often making decisions with incomplete data. We have to get creative with the few signals we do have to understand our users' needs.
- In the same vein, we're tuning the system to use the most efficient fetching strategy for any given URL. Even with continuous learning and tuning, we don't always get it right, so we give the caller the ability to control the effort of the fetch. If they aren't happy with the results, they can increase the effort and we'll spend more time and resources to get back as much content as we can.
Snyk
This reminds me of the Faker lib. Cool stuff Tessa! 🎉
Tabstack by Mozilla
The schema first approach is what caught my eye. Scrapers usually work great until a site changes one small thing
Tabstack by Mozilla
@furkan_topcuoglu exactly. Tabstack takes a different approach, helping avoiding the constant scraper management fixes. I had an audit tool reviewing developer documentation and the pricing page was a constant pain point, so many varying needs and ways to get pricing across different brands. I implemented Tabstack (when I was interviewing) and realized how much more effective it is. I haven't had to adjust my app in this area since.
I've built a few scraping workflows before and maintenance was always the painful part. How it handles sites that change their structure frequently
Tabstack by Mozilla
@erkan this is the main reason Tabstack exists. The maintenance pain you are describing comes from selector-based extraction: you pin to CSS paths or DOM structure, and the moment a site reships its markup, those break.
Tabstack is schema-driven, not selector-driven. You define the JSON shape you want, the meaning of the data, not where it lives in the DOM. A model reads the rendered page and maps content to your schema. So when a site redesigns its layout, there is no selector pinned to the old structure to break. The same schema keeps returning the same shape against the new markup.
Honest boundary: this insulates you from layout and markup churn, not from the content itself changing. If a field genuinely disappears from the page, changes in meaning, or moves behind a new interaction, you may still need to adjust. But the day-to-day "they shipped a redesign and my extractor broke" maintenance mostly goes away.