AmbitionBox Reviews Scraper

Export public AmbitionBox employee reviews as structured JSON, CSV, Excel, XML, or RSS.

Give the Actor a company slug such as tcs or an AmbitionBox company review URL. It returns individual reviews with ratings, pros, cons, designations, departments, locations, work policies, verification signals, and denormalized company culture context.

No AmbitionBox login or API key is required.

What does AmbitionBox Reviews Scraper do?

AmbitionBox Reviews Scraper turns public company review pages into analysis-ready records.

It can:

• 📝 Export one row per employee review.
• ⭐ Capture overall and seven category ratings.
• 💬 Collect pros, cons, and review titles.
• 🧑‍💻 Extract designation, department, location, and employment type.
• 🏠 Identify WFO, WFH, and Hybrid work-policy reviews.
• ✅ Preserve AmbitionBox verification and helpfulness signals.
• 📊 Add company-wide ratings, rating distribution, culture themes, and work-policy mix to every row.
• 🔎 Filter by rating, designation, location, work policy, or verified status.
• 🔁 Process several companies in one scheduled run.

The scraper uses AmbitionBox's current server-rendered data and public structured review endpoints rather than brittle visual selectors.

Who is AmbitionBox Reviews Scraper for?

Employer-brand and people teams

• Monitor recent employee feedback about your company.
• Track repeated culture, compensation, and management themes.
• Compare review velocity and ratings with peer employers.

Recruiters and talent-intelligence teams

• Research how candidates may perceive a target employer.
• Compare work-policy and role-specific experiences.
• Build repeatable company research before outreach campaigns.

Candidates and career researchers

• Export reviews for offline comparison.
• Focus on a city, designation, rating range, or work policy.
• Review both individual comments and company-level context.

Analysts and data teams

• Build employer sentiment dashboards.
• Schedule recurring snapshots for trend analysis.
• Feed structured records into warehouses, notebooks, or AI workflows.

Why use this AmbitionBox review extractor?

• Focused reviews-only contract — no mixed salary, interview, or job rows.
• Analysis-ready output — every row includes company aggregate context.
• Source IDs included — deduplicate recurring snapshots by reviewId.
• Strict input validation — unrelated websites and non-review AmbitionBox paths fail closed.
• Useful filters — reduce downstream cleaning for role, city, rating, policy, or verified reviews.
• Reliable delivery — conservative concurrency, India routing, cookie-preserving sessions, and bounded retries.
• Apify-native automation — API access, schedules, webhooks, datasets, exports, and integrations.
• No target login — the Actor reads only anonymously visible public review data.

What AmbitionBox review data can you extract?

Category	Fields
Identity	reviewId, companyId, companyName, companySlug
Review	rating, reviewTitle, pros, cons, reviewedOn, reviewUrl
Reviewer context	designation, department, location, employmentType, workPolicy
Signals	verified, helpfulCount, notHelpfulCount, employerResponded
Category ratings	salary, skill development, job security, promotions, work satisfaction, company culture, work-life balance
Company ratings	overall, job security, work life, culture, skills, satisfaction, compensation, career growth
Company aggregates	total reviews, rating distribution, work-policy distribution, top mentions, positive and critical themes
Run metadata	scrapedAt

Optional values are omitted when AmbitionBox does not publish them for a specific review. The Actor does not invent missing values.

How much does it cost to scrape AmbitionBox reviews?

The Actor uses pay-per-event pricing:

• $0.005 start fee per run.
• $0.00077011 per review on the Bronze tier before volume discounts.

Example estimates:

Reviews	Estimated Bronze charge
20	$0.0204
100	$0.0820
1,000	$0.7751

Apify plan tiers can receive lower per-review prices. Residential proxy bandwidth and compute are handled by the Actor; users pay the displayed Actor charge.

With the Apify Free plan's monthly platform credit, small review exports can usually be tested before scaling. Check the live Pricing tab because platform prices can change.

How to scrape AmbitionBox employee reviews

1. Open AmbitionBox Reviews Scraper on Apify.
2. Add one or more company slugs, such as tcs or infosys.
3. Alternatively, paste a URL such as https://www.ambitionbox.com/reviews/tcs-reviews.
4. Choose the maximum reviews per company and total review limit.
5. Optionally add rating, designation, location, work-policy, or verified-only filters.
6. Click Start.
7. Preview the dataset or export it as JSON, CSV, Excel, XML, or RSS.
8. Save the input as a Task or schedule it for recurring monitoring.

A low-cost first input:

{
  "companies": ["tcs"],
  "maxReviewsPerCompany": 5,
  "totalMaxReviews": 5,
  "maxPagesPerCompany": 2,
  "maxConcurrency": 1
}

A multi-company monitoring input:

{
  "companies": ["tcs", "infosys", "wipro", "hcl-technologies"],
  "maxReviewsPerCompany": 50,
  "totalMaxReviews": 200,
  "maxConcurrency": 3
}

A filtered research input:

{
  "companies": ["https://www.ambitionbox.com/reviews/infosys-reviews"],
  "minRating": 1,
  "maxRating": 3,
  "location": "Pune",
  "workPolicy": "Hybrid",
  "verifiedOnly": true,
  "maxReviewsPerCompany": 25
}

Input parameters

Parameter	Type	Default	Description
companies	array	required	Bare company slugs or AmbitionBox /reviews/ URLs
maxReviewsPerCompany	integer	20	Maximum matching reviews saved per company
totalMaxReviews	integer	100	Maximum reviews saved across all companies
minRating	integer	—	Minimum overall review rating, 1–5
maxRating	integer	—	Maximum overall review rating, 1–5
designation	string	—	Case-insensitive job-profile text filter
location	string	—	Case-insensitive job-location text filter
workPolicy	string	any	any, WFO, WFH, or Hybrid
verifiedOnly	boolean	false	Keep only reviews marked verified
maxPagesPerCompany	integer	20	Safety limit on pages scanned to find filter matches
maxConcurrency	integer	3	Companies fetched in parallel; maximum 5
maxRequestRetries	integer	5	Session rotations after a network or anti-bot response
proxyConfiguration	object	Residential IN	Advanced proxy configuration

maxReviewsPerCompany limits saved rows. When filters are active, the Actor may scan several source pages to find that many matches, bounded by maxPagesPerCompany.

Output example

{
  "reviewId": 80482915,
  "companyId": 42,
  "companyName": "TCS",
  "companySlug": "tcs",
  "rating": 1,
  "ratingSalary": 1,
  "ratingSkillDevelopment": 2,
  "ratingJobSecurity": 1,
  "designation": "Transformation Manager",
  "department": "Compensation & Benefits",
  "location": "Bengaluru",
  "employmentType": "permanent",
  "workPolicy": "WFO",
  "pros": "Public review text from AmbitionBox",
  "cons": "Public review text from AmbitionBox",
  "verified": false,
  "employerResponded": false,
  "reviewedOn": "2026-07-22",
  "reviewUrl": "https://www.ambitionbox.com/reviews/tcs-reviews?rid=80482915",
  "companyOverallRating": 3.3,
  "companyTotalReviews": 117292,
  "companyWorkPolicyDistribution": "Work from office: 81%; Hybrid: 15%; Permanent work from home: 4%",
  "scrapedAt": "2026-07-23T00:00:00.000Z"
}

The example illustrates field shape. Review text and aggregate values change as AmbitionBox publishes new data.

Filter AmbitionBox reviews

Filters are evaluated against the source values in each review:

• Rating bounds require a parseable numeric rating and fail closed when absent.
• Designation and location use case-insensitive substring matching.
• Work policy requires the exact AmbitionBox policy code.
• verifiedOnly requires AmbitionBox's boolean verified flag.

A valid source request with no matching reviews finishes successfully with an empty dataset and a warning. A source extraction failure exits non-zero instead of silently returning success.

Tips for best results

• Start with 5–20 reviews before increasing limits.
• Use company slugs when you already know the AmbitionBox URL name.
• Use full review URLs when copying a company from your browser.
• Keep concurrency at 3 or lower for stable recurring runs.
• Raise maxPagesPerCompany only for selective filters.
• Use reviewId to deduplicate scheduled snapshots.
• Store scrapedAt and reviewedOn separately for trend analysis.
• Keep the default Residential India routing unless you have tested another route.

Schedule employer-review monitoring

Create an Apify Task with your company list and review limit. Then add a daily, weekly, or monthly schedule.

For incremental workflows:

1. Run the Actor on a schedule.
2. Read the default dataset through the API.
3. Compare reviewId with your stored IDs.
4. Send only unseen reviews to your dashboard, warehouse, or alert channel.

The Actor currently exports snapshots. It does not maintain cross-run state or suppress previously seen reviews automatically.

Integrations

AmbitionBox Reviews Scraper → Google Sheets

Append recent reviews to a shared employer-brand tracker and build rating pivots by company, role, or location.

AmbitionBox Reviews Scraper → Slack or Microsoft Teams

Use an Apify webhook with Make or Zapier to alert a people team when a scheduled run finds new low-rating reviews.

AmbitionBox Reviews Scraper → BigQuery or Snowflake

Load scheduled datasets into a warehouse, deduplicate by reviewId, and model rating or culture trends over time.

AmbitionBox Reviews Scraper → AI sentiment workflow

Send pros and cons to an approved language model to classify themes while retaining source IDs and URLs for auditability.

AmbitionBox Reviews Scraper → Looker Studio or Power BI

Build employer-comparison dashboards from review-level ratings and denormalized company aggregates.

Use the Apify API with JavaScript

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('automation-lab/ambitionbox-reviews-scraper').call({
  companies: ['tcs', 'infosys'],
  maxReviewsPerCompany: 20,
  totalMaxReviews: 40,
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

Use the Apify API with Python

import os
from apify_client import ApifyClient

client = ApifyClient(os.environ['APIFY_TOKEN'])
run = client.actor('automation-lab/ambitionbox-reviews-scraper').call(run_input={
    'companies': ['tcs'],
    'maxReviewsPerCompany': 20,
    'totalMaxReviews': 20,
})

for item in client.dataset(run['defaultDatasetId']).iterate_items():
    print(item)

Use the Apify API with cURL

curl -X POST \
  "https://api.apify.com/v2/acts/automation-lab~ambitionbox-reviews-scraper/runs?token=$APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "companies": ["tcs"],
    "maxReviewsPerCompany": 20,
    "totalMaxReviews": 20
  }'

After the run finishes, fetch items from the run's defaultDatasetId.

Use AmbitionBox Reviews Scraper with AI agents via MCP

The Actor can be used by AI assistants through Apify's hosted Model Context Protocol integration.

For Claude Code:

$claude mcp add --transport http apify "https://mcp.apify.com?tools=automation-lab/ambitionbox-reviews-scraper"

For Claude Desktop, Cursor, or VS Code, add:

{
  "mcpServers": {
    "apify": {
      "url": "https://mcp.apify.com?tools=automation-lab/ambitionbox-reviews-scraper"
    }
  }
}

Example prompts:

• "Use automation-lab/ambitionbox-reviews-scraper to export the 20 latest TCS employee reviews."
• "Collect verified Infosys reviews from Pune and summarize recurring pros and cons."
• "Compare work-policy and company-culture ratings for TCS, Infosys, Wipro, and HCL Technologies."

Your AI client authenticates with your Apify account and can start the Actor as a tool.

Is it legal to scrape AmbitionBox reviews?

This Actor accesses anonymously visible public review content. It does not log in, bypass private employer analytics, solve CAPTCHAs, or collect reviewer contact details.

Scraping public information is generally permitted in many jurisdictions, but rules depend on your location and use case. Users are responsible for complying with AmbitionBox's terms, applicable privacy and database laws, employment regulations, and contractual obligations.

Use the data ethically:

• Collect only what you need.
• Avoid attempts to identify anonymous reviewers.
• Do not use review data for harassment or unlawful employment discrimination.
• Honor deletion, correction, retention, and access obligations that apply to your organization.
• Seek legal advice for high-risk or large-scale uses.

Limitations

• AmbitionBox uses Akamai protection, so Residential India proxy routing is normally required.
• The Actor supports public company review pages only.
• Jobs, salaries, interviews, employer dashboards, and private analytics are outside V1.
• AmbitionBox may omit helpfulness, role, location, or optional text on individual reviews.
• Rating and aggregate values change as the source receives new reviews.
• Selective filters may return fewer rows before maxPagesPerCompany is reached.
• Source layout or endpoint changes can temporarily require an Actor update.
• Reviewer identity is intentionally not inferred from anonymous content.

Troubleshooting

Why did my run return no reviews?

Check that the slug exists and that your filters are not too narrow. Remove filters or raise maxPagesPerCompany. Logs distinguish zero filter matches from extraction failures.

Why does an AmbitionBox URL fail validation?

Use a company review URL shaped like https://www.ambitionbox.com/reviews/tcs-reviews. Overview, salary, interview, job, search, and third-party URLs are rejected by the reviews-only contract.

Why do some fields not appear?

Optional fields are omitted when AmbitionBox does not publish them for a review. This is preferable to empty placeholders or guessed data.

Why can runs take longer with filters?

The Actor scans source pages until it finds enough matching reviews or reaches the page safety limit. Narrow filters require more source requests.

FAQ

How fast is the AmbitionBox scraper?

A small single-company run normally finishes in under two minutes. Larger multi-company or selective-filter runs take longer because requests use conservative concurrency and protected-source retries.

Does it require an AmbitionBox account?

No. It accesses only public company review data that is visible without logging in.

Can I scrape several companies at once?

Yes. Add multiple slugs or review URLs to companies and set per-company and total limits.

Can I scrape only one-star reviews?

Yes. Set both minRating and maxRating to 1.

Can I filter by job title or city?

Yes. Use designation and location; both are case-insensitive substring filters.

Does this replace an official AmbitionBox API?

It provides an Apify API for public review exports. It is not affiliated with AmbitionBox and is not an official AmbitionBox API.

How should I track new reviews?

Schedule snapshots and deduplicate by the stable numeric reviewId. Keep scrapedAt to identify when each snapshot was collected.

What happens when AmbitionBox blocks a request?

The Actor rotates the full proxy session and retries with bounded exponential backoff. Persistent extraction failure returns a failed run rather than an empty successful dataset.

Other employer-review and labor-market scrapers

Explore related Automation Labs actors:

• Glassdoor Reviews Scraper
• Indeed Reviews Scraper
• Trustpilot Scraper
• LinkedIn Jobs Scraper
• Naukri Jobs Scraper
• Google Jobs Scraper

Use related actors only when you need another source or workflow. AmbitionBox Reviews Scraper remains focused on public AmbitionBox employee reviews.

Support

If a valid public review URL stops working, open an issue from the Actor's Issues tab.

Include:

• The input with secrets removed.
• The failed run URL.
• The company slug or public review URL.
• The expected and actual behavior.

Do not include Apify tokens, private proxy credentials, or personal employee information.