2 tools do this job
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 tools here read the reviews for you, by company website or by Glassdoor page URL, from 1.05 credits/result, each at its own rate. 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.
Billed per call, for what you use. No card required.
0 of the 2 tools that answer this job are live-verified against their upstream.
Try it
1 · Set your agent up, once
set up 鹦鹉AI — https://parrot.amorist.cn/llms.txt
2 · Then ask for the job
Using 鹦鹉AI, 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.
Akta keys on the company's website; Bright Data on the Glassdoor page URL. Say which one you have and the agent picks the tool that takes it.
Ask for the reviews you need; every review a big employer has is not worth pulling.
Each row carries the reviewer's status. The two groups tell different stories, and a mean over both hides both.
鹦鹉AI returns the rate before the call, so the agent can say what a list of fifty companies will spend.
Why 鹦鹉AI
Charged per call. No card, no minimum; top up the prepaid balance.
Another tool is a different word in the prompt, not a new integration.
From the field
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 promotional share was scraper launches, one identical cross-post in two subreddits, and a review-removal service. These five are the people doing the work.
“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 tools that return the reviews as rows without a Glassdoor app, priced per review or per record, with the rate shown before the call.
“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 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 鹦鹉AI it is not free, it is under one credit per review at its own rate.
“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 one can answer that, and neither tool 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.
“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 credits a row to a recruiter, a seller or a candidate. The agent reads the cons; the page only gets it the rows.
The detail
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 tool works.
Bright Data's scraper answers small batches directly and falls back to a snapshot id past that, so a long list is a job to poll, not a single call.
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 tool 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
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 tool that does the reading and returns rows. The two tools 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
No. The partner programme stopped accepting new partners, which is why the people who asked for access on the forums were turned away. The tools here read the public review pages for you and return rows; you never fetch glassdoor.com yourself.
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.
The one whose input you hold: website for Akta, Glassdoor URL for Bright Data. 鹦鹉AI does not route or fail over for you.
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