2 providers · from $0.0015 per result · $0.000 markup

Glassdoor API and Glassdoor scraper, through one key: a company's employee reviews as rows your agent can read

Give your agent a company and get its employee reviews back as rows: rating, title, pros, cons, date and whether the reviewer still works there. Glassdoor closed its partner API, so the two providers here read the reviews for you, by company website or by Glassdoor page URL, from $0.0015 at the provider's own rate with no markup. There is no Glassdoor login, no bot wall and no give-to-get review to write first. What comes back is what Glassdoor shows; nobody here vets the reviewers.

Start free See the comparison

$1.00 of free credit on every new team · no provider signup · no card

0 of 2 endpoints on this page are live-verified against the provider.

compared on this page

Try it

What’s the best way to ask ChatGPT?

1Set your agent up, once

in your agent's chat

set up treg — https://treg.to/llms.txt

2Ask for the job

the prompt

Using treg, pull the last 100 employee reviews for canva.com, show me the price first, then split them into current and former staff, give me the three complaints that recur most in the cons, and flag any month where the rating dropped sharply.

works in

Why this prompt works

Give the website, or the Glassdoor URL

Akta keys on the company's website; Bright Data on the Glassdoor page URL. Say which one you have and the agent picks the row that takes it.

Ask for a count you can afford

Akta bills per 50 reviews returned and defaults to 10. A hundred reviews is a few cents; every review a big employer has is not.

Split current from former

Each row carries the reviewer's status. The two groups tell different stories, and a mean over both hides both.

Ask for the price first

treg.to returns the rate before the call, so the agent can say what a list of fifty companies will spend.

Why treg.to

Why go through treg.to

One key, not 9 accounts

treg.to holds the provider keys. Neither you nor the agent sees them.

Price before the call

The provider's own rate, $0.000 markup, from a prepaid balance.

No subscription, no seats

Charged per call. $1.00 free per new team, no card to start.

Your own keys are free

Already pay Hunter? Register it and those calls are never metered.

Switch by changing a word

Another provider is a different word in the prompt, not a new integration.

Nothing to integrate

No SDK, no OAuth dance per vendor, no seats.

Behind the scenes

What ChatGPT sees before it calls

treg.to does not choose for you. It hands ChatGPT this comparison, with the price shown before any call, and ChatGPT picks. Or you tell it how: "cheapest", "most reliable", "the one that takes what I have", or a provider by name.

Which Glassdoor reviews provider is cheapest per review?

Cheapest per result

Akta by Wokelo at $0.0015

How do Akta and Bright Data compare?

Provider	Price	Accepts	Success rate	Verified
Akta by Wokelo	$0.0015 per result	company, limit, offset	(1 calls)	unverified
Bright Data	$0.0015 per result	dataset_id, format, input	(2 calls)	unverified

Run one

the cheapest verified call

treg call akta.companies.reviews --query company=canva.com --query limit=1

Swap the id for any provider above. All 2 endpoints behind this job, with their parameters and captured responses, are on the Company data shelf.

How these numbers are made

PricesEach provider’s own published rate, converted to US dollars for one chargeable event of the unit they bill in. treg.to adds $0.000. Where a provider bills in credits, the conversion uses the rate on their public pricing page.

Success ratetreg.to’s own served calls over the last 30 days: 2xx counts as a success, 5xx and timeouts as a failure. A 4xx is excluded, because it usually means the caller sent bad parameters and one bad query should not make a healthy endpoint look broken.

What this is notA controlled benchmark. These are real calls with real inputs, so sample sizes and the difficulty of what was asked differ by provider. Treat the rates as live reliability, not a like-for-like test.

VerifiedThe date treg.to last called the endpoint end to end and confirmed the shape of its response and the price it charged.

From the field

What people actually struggle with

Glassdoor threads split in two: people who want the data and people who hate the sign-up wall. Of the ~165 Reddit and X posts read in August 2026, about 25 were organic and on the job; the vendor share was scraper launches, one identical cross-post in two subreddits, and a review-removal service. These five are the people doing the work.

The API everyone reaches for first is closed

“I was planning to use Glassdoor’s API to gather this data, but unfortunately, they’ve stopped API partnerships for now.” r/learnprogramming

What this page can do about it: Still closed, and the page does not know a way in. What it does have is two providers that return the reviews as rows without a Glassdoor app, priced per review or per record, with the rate shown before the call.

A company name is not a Glassdoor URL

“For Glassdoor it is more complicated. I cannot just add the company website to the Glassdoor url to locate and scrape the correct page” r/learnpython

What this page can do about it: That is the exact input Akta takes: the company website, no Glassdoor URL needed. A dataframe of names and domains is the whole job, one call per company.

Is it even worth trying to scrape it for free?

“is it possible to scrape Glassdoor reviews (completely free). I don’t want to waste my time if I can’t.” r/webscraping

What this page can do about it: The honest answer from the same thread is that plain requests get a bot page. Through treg.to it is not free, it is a fraction of a cent per review at the provider's rate, and the first dollar is on the house for a new team.

Nobody knows how many of the reviews are real

“there is not much transparency about how many reviews on the website are made by nefarious actors (e.g. bots).” r/RKLB, 13 points

What this page can do about it: No comparison table can answer that, and neither provider vets a reviewer. What an agent can do is what that investor did by hand: pull the rows, weight by date and status, and compare the shape against peers.

The rating is a hiring signal, whether or not it is fair

“developers are keen to weed out companies with ratings like this.” r/cscareerquestions, 1,108 points

What this page can do about it: Which is why a list of target companies with their recent reviews is worth a few cents a row to a recruiter, a seller or a candidate. The agent reads the cons; the page only gets it the rows.

The detail

What actually differs

The input decides the provider.

Akta takes a company website, which is what a spreadsheet of targets usually has, and returns reviews in pages of up to 100. Bright Data wants the Glassdoor page URL itself, and finding that URL from a company name is the step the forum's scrapers kept failing at. If you have websites, start at Akta; if you have Glassdoor URLs, either row works.

Neither endpoint has been called live through treg.

to yet, and the page says so rather than hiding it. Akta's rate is documented as 1.5 credits per 50 reviews, Bright Data's as $1.50 per 1,000 records on a pay-per-success basis, and both are the provider's own rate with $0.000 added. Bright Data's scraper answers within a minute for a handful of URLs and falls back to a snapshot id past that, so a long list is a job to poll, not a single call.

Rows are what Glassdoor shows, not what is true.

The research has retail investors using review scrapes for due diligence and hiring managers reading the cons before an offer, and it also has the same people asking how many reviews are bots or bought. No provider here answers that. What the rows do carry is date, status and sub-ratings, which is enough for an agent to weight recent reviews, separate current staff from former, and show its working.

Background

Is there a Glassdoor API?

Not one you can sign up for. Glassdoor ran a partner API and stopped taking new partners, so the phrase on the forums, Glassdoor API, now means one of two things: a scraper you run yourself against pages that block plain requests and render reviews through GraphQL, or a data provider that does the reading and returns rows. The two providers here are the second kind. Akta returns employee reviews and ratings for a company by its website, so a list of company names and domains is enough; Bright Data's Glassdoor reviews dataset takes the Glassdoor company page URL and returns the records, pay per record delivered.

Questions

Before you start

Does Glassdoor have a public API?

No. The partner programme stopped accepting new partners, which is why the people who asked for access on the forums were turned away. The providers here read the public review pages for you and return rows; you never fetch glassdoor.com yourself.

Do I need a Glassdoor account?

No. Both calls run on treg.to's own key and return review text without a login, so the sign-up wall that asks you to review your own employer first does not apply to the agent. Register your own Akta or Bright Data key and the calls are never metered.

Can it tell me which reviews are fake?

No, and this page will not pretend otherwise. The rows are Glassdoor's, unvetted. Use the date and the current-or-former flag to weight them, and treat a cluster of five-star reviews in one week as a question, not an answer.

Which provider should my agent use?

The one whose input you hold: website for Akta, Glassdoor URL for Bright Data. treg.to shows both with the rate side by side; it compares, it does not route or fail over for you.