Data extraction, with intelligence on top

Web Scraping & Data Extraction Company in India

We extract the public web data you cannot get cleanly anywhere else, from marketplaces, listings, directories, and review sites, then put an intelligence layer on top so you get decisions, not just a CSV.

Galific is a data intelligence company. We handle the hard scraping at scale and turn it into prices to act on, demand signals, and reconciled records. Every engagement starts with a free feasibility and legality check on your target sources.

Get a free source and legality check →

Scraping is step one. Intelligence is the point.

Most providers hand you a raw dump and walk away, which leaves your team to clean, match, and interpret it. That is where the real work is. We do the extraction and the intelligence, so the output is something you act on, delivered where your team already works.

Extraction at scale

We collect public web data reliably across thousands of pages and many sources, not a one-off scrape that breaks next week.

Entity matching and normalization

We deduplicate, match records across sources, and normalize units, currencies, and formats so the data is actually comparable.

Change monitoring and alerts

We track changes over time and alert you when a price, listing, or signal moves, instead of handing you a static snapshot.

The intelligence layer on top

We turn the data into decisions: competitor repricing, demand forecasts, and reconciled records, delivered where your team already works.

What we extract

Product catalogs and prices across Amazon, Flipkart, Myntra, Meesho, and quick-commerce apps; real estate listings and transaction records; business directories and leads; travel and pricing data; reviews and sentiment. If the data is public and you can see it in a browser, we can usually collect it, structure it, and keep it fresh.

Built for the sites that fight back

Public data is rarely served cleanly. We handle JavaScript-rendered and infinite-scroll pages, rotating proxies and IP management, CAPTCHA and anti-bot defenses, rate limits, and layout changes that break naive scrapers, with quality checks so the data is accurate, not just collected.

Is web scraping legal in India?

Short version: scraping publicly available data is generally permissible, but the details matter, and we scope them with you before we start. India has no statute that specifically bans scraping. The Digital Personal Data Protection Act 2023 does not apply to personal data that has been made publicly available (Section 3(c)(ii)), which covers most public web data.

Accessing a system without authorization can fall under Section 43 of the IT Act 2000, and a site's terms of service can create contractual limits. So we focus on public, permitted data, respect robots and rate limits, avoid personal or sensitive data unless you have a lawful basis, and flag anything that needs your legal sign-off.

This is general information, not legal advice.

How we work

01

Feasibility and legality check

We review your target sources, confirm what is collectable and compliant, and send a sample. Free, before you commit.

02

Build and validate

We build the extractors and the intelligence layer, then validate accuracy and completeness against your needs.

03

Deliver and monitor

We deliver in your format (CSV, JSON, API, or your database) and keep it fresh with monitoring and change alerts.

Where extracted data turns into decisions

Retail and e-commerce

Competitor prices, catalog gaps, and stock signals across marketplaces.

Finance and fintech

Public filings, market data, and counterparty signals, cleaned and matched.

Supply chain

Supplier, logistics, and commodity data feeding demand and inventory models.

Real estate

Listings and transaction records turned into verified, searchable intelligence.

Our trusted clients

TechMax IT Consultancy TechMax IT Consultancy
Virtuous Group
Golden Abodes
Questera
Fluid Labs
Anxzone
Kroo
RSE Labs
Clariti
Naskay Technologies
Bellurbis
Praic
Doctat
Persana AI
Propviewz

Web scraping FAQs

General FAQs

Everything you need to know about the service and how it works. Can’t find an answer? Mail us at info@galific.com

  • Is web scraping legal in India? ⌄
    Scraping publicly available data is generally permissible, but the details matter and we scope them with you before starting. India has no statute that specifically bans scraping. The Digital Personal Data Protection Act 2023 does not apply to personal data that has been made publicly available (Section 3(c)(ii)), which covers most public web data. Accessing a system without authorization can fall under Section 43 of the IT Act 2000, and a site's terms of service can add contractual limits. So we focus on public, permitted data, respect robots and rate limits, and flag anything that needs your legal sign-off. This is general information, not legal advice.
  • What makes you different from a regular scraping provider? ⌄
    Most providers hand you a raw dump and leave the hard part, cleaning and interpreting it, to you. We do the extraction and the intelligence on top: deduplication, entity matching, normalization, change detection, and models that turn the data into a decision. Galific is a data intelligence company, so a scrape is the input, not the deliverable. The deliverable is something you act on, like a repricing signal or a forecast. See our custom machine learning solutions.
  • Which sites and marketplaces can you extract data from? ⌄
    Product catalogs and prices across Amazon, Flipkart, Myntra, Meesho, and quick-commerce apps, plus real estate listings, business directories, travel and pricing data, and reviews. If the data is public and visible in a browser, we can usually collect it, structure it, and keep it fresh.
  • How do you handle dynamic sites, CAPTCHAs, and blocking? ⌄
    Public data is rarely served cleanly. We handle JavaScript-rendered and infinite-scroll pages, rotating proxies and IP management, CAPTCHA and anti-bot defenses, rate limits, and layout changes that break naive scrapers. We monitor the extractors so they keep working as sites change.
  • How do you keep the data accurate and complete? ⌄
    We run schema validation, completeness checks, and change detection on every run, and match records across sources so you are not comparing duplicates or mismatched items. Accuracy is a method we apply, not a number we promise.
  • In what formats do you deliver the data? ⌄
    CSV, JSON, a direct API, or written straight into your database or BI tool. The point is to put the data where your team already makes decisions, not in a separate file nobody opens.
  • How often can you refresh the data? ⌄
    From a one-time pull to continuous monitoring with hourly or daily refreshes, depending on how fast your decisions need to move. Price and stock data often needs frequent refreshes; reference data can be slower.
  • What can we do with the data once we have it? ⌄
    That is where the intelligence layer comes in. Common uses are demand forecasting, competitor price monitoring and repricing, ML-powered reconciliation, and live signals served through real-time inference engines.
  • Do you handle personal or sensitive data? ⌄
    We focus on public, non-personal data by default. If a use case involves personal data, we only proceed where there is a lawful basis, minimize what we collect, and put the compliance terms in writing first.
  • How does an engagement start, and what does it cost? ⌄
    It starts with a free feasibility and legality check on your target sources, plus a sample, so you see the data quality before committing. Cost depends on the number of sources, refresh frequency, and the intelligence layer, and we scope it after the check rather than quote a vague range.