Web Scraping & Data Extraction

Custom web scraping & data extraction, built to run on its own

We engineer scrapers and crawlers that pull public data on a schedule — leads, prices, listings, reviews — handle anti-bot protection, and deliver clean, structured records straight to your sheets, database or CRM. Ethical, compliant scraping, built in Kuala Lumpur for Malaysia and worldwide.

Scheduled · anti-bot ready · structured output you own.

Handling
Anti-bot
Output
Structured
What we build

Scrapers engineered for reliable, structured data

We don’t sell one-off data dumps. We build maintained extraction systems — and hand you the code, the schedule and the output. A typical build includes:

Custom scrapers & crawlers

Purpose-built extractors that paginate, follow links and render JavaScript-heavy pages to pull exactly the fields you need.

Scheduled extraction

Runs on a cron schedule — hourly, daily or weekly — so fresh data lands without anyone touching a browser.

Anti-bot handling

Headless browsers, rotating proxies, realistic request patterns and retry logic to get through rate limits and blocks cleanly.

Structured output

Clean, validated, de-duplicated records written to Google Sheets, Airtable, Notion, a SQL warehouse or your CRM — not messy CSVs.

Monitoring & change detection

Diffing between runs to catch new listings, price moves and stock changes — with alerts when a scraper returns nothing.

Enrichment & de-duplication

Merge, normalise and enrich records — matching emails, phones and domains — so what you receive is ready to use.

Built with

We render dynamic pages with headless browsers — Playwright and Puppeteer — behind rotating proxies, schedulers and cron, then land clean, structured data in whichever store fits your stack:

Google SheetsAirtableNotionPostgreSQLMySQLGoogle BigQuerySnowflakeHubSpot
The build process

How a scraper goes from target list to running pipeline

A repeatable engineering process that keeps extraction reliable, compliant and low-maintenance.

01
Scope
Sources, fields & volume.
02
Design schema
Data model & targets.
03
Build scraper
Crawl, render, extract.
04
Integrate
Load to sheet or DB.
05
Test & validate
Accuracy & dedupe.
06
Deploy & schedule
Cron, proxies, runs.
07
Monitor & support
Alerts & upkeep.
Example builds

The extraction jobs we’re asked for most

Google Maps scraping

Pull business names, categories, addresses, phones, websites and ratings across a location or niche into a clean list.

PlacesLeads

Lead generation lists

Scrape directories, marketplaces and company sites, then de-duplicate and enrich contacts straight into your CRM.

DirectoriesCRM

Competitor & price monitoring

Track competitor prices, promos and listings on a schedule, detect changes and alert your team when they move.

PricesAlerts

Product & stock monitoring

Watch catalogues and marketplaces for new products, stock and reviews, feeding a live sheet or dashboard.

CatalogueDashboard
What shapes the investment

Transparent scoping, a fixed quote

Every scraper is different, so we don’t publish a flat rate. After a free scoping call we quote a fixed price before any work starts. A few factors drive that scope:

Number & complexity of sources
One directory versus dozens of sites, each with its own structure, pagination and login.
Anti-bot protection
Open pages are quick; sites with CAPTCHAs, aggressive rate limits or heavy JavaScript need more engineering and proxy budget.
Volume & run frequency
A one-off pull differs from near-real-time monitoring that runs hourly at scale and needs more infrastructure.
Output & integration
A single sheet is simple; writing into a data warehouse or CRM with enrichment and de-duplication adds work.
Maintenance & monitoring
A delivered dataset is one-off; a maintained pipeline with alerting and fixes when sites change is an ongoing arrangement.
Why Framworq

Scrapers built to keep running, not just to demo

Ethical & compliant by default

Public data only, robots and terms respected, request rates throttled — we flag risky use cases before building.

Engineered for reliability

Resilient selectors, retries and monitoring so a site change is caught and fixed — not a silent gap in your data.

Clean data, not raw dumps

Validation, normalisation and de-duplication mean what lands in your stack is ready to use straight away.

You own everything

Scrapers, data and documentation are yours — hosted on your infrastructure or ours, no lock-in.

Part of a wider automation team

100+ workflows launched and 3,000+ hours saved — scraping plugs straight into your automations and dashboards.

KL-based, globally minded

On the ground in Kuala Lumpur, delivering for clients across Malaysia and worldwide.

Explore related

Where scraped data goes next

FAQ

Web scraping questions

What kinds of websites and data can you scrape?

Almost any publicly accessible source: business directories and Google Maps listings, e-commerce catalogues and prices, marketplaces, real-estate portals, review sites, job boards and company websites. We extract structured fields — names, contacts, prices, stock, ratings, addresses, coordinates — and can render JavaScript-heavy pages, paginate, follow links and log into permissioned areas where you have the right to access them.

Is web scraping legal, and do you scrape ethically?

We build for compliant, ethical scraping. We focus on publicly available data, respect robots.txt and each site’s terms of service, avoid personal data you have no lawful basis to collect, and throttle requests so we don’t overload a target site. Where an official API exists we prefer it. If a use case looks legally risky we will tell you before building it.

How do you handle anti-bot protection, CAPTCHAs and rate limits?

We use headless browsers such as Playwright and Puppeteer to render pages like a real user, rotating proxies and realistic request patterns to stay within rate limits, and retry-and-backoff logic so a temporary block doesn’t lose data. For heavily protected sites we integrate CAPTCHA-solving or official APIs, and we always tune request rates to avoid stressing the source.

Where does the extracted data land — sheets, a database or our CRM?

Wherever it’s most useful to you. We can write clean, de-duplicated records straight to Google Sheets, Airtable or Notion, load them into PostgreSQL, MySQL, BigQuery or Snowflake for analytics, or push them into a CRM like HubSpot. Output is structured and normalised, and we can deliver JSON or CSV exports as well.

What technology do you build the scrapers with?

Custom crawlers built on Playwright or Puppeteer for dynamic sites, with rotating proxies, schedulers and cron for recurring runs, plus a data layer in Google Sheets, Airtable, Notion, PostgreSQL, MySQL, BigQuery or Snowflake. We add validation, de-duplication and change-detection so the data stays clean, and we choose the lightest tool that does the job reliably.

How do you keep scrapers running when a website changes its layout?

Sites change, and scrapers break — so we build in monitoring and alerting that flags when a run returns no data or unexpected fields, plus resilient selectors that don’t rely on brittle markup. When a target site is redesigned we update the scraper as part of maintenance, so you’re not left with silent gaps in your data.

Can you scrape Google Maps, directories and lead sources at scale?

Yes. Google Maps and directory scraping for lead generation is one of the most common builds we do — extracting business names, categories, addresses, phone numbers, websites and ratings across a location or niche, then de-duplicating and enriching them into a ready-to-use lead list in your sheet, database or CRM.

How often can scrapers run, and can they monitor prices in near real time?

As often as the use case needs — on a schedule via cron, from hourly price and stock checks to daily or weekly competitor and directory sweeps. For price and product monitoring we detect changes between runs and can trigger alerts or feed a dashboard, so you see competitor moves without checking sites by hand.

Do we own the scrapers and data, and do you work with businesses outside Malaysia?

You own both. We hand over the scrapers, the extracted data and documentation, and can host them on your infrastructure or ours. We’re based in Kuala Lumpur and build web-scraping and data-extraction systems for clients across Malaysia and worldwide, remotely.

Turn the web into your dataset

Stop copy-pasting data. Let a scraper do it on schedule.

Tell us the sources and the fields you need. We’ll scope a compliant, maintained scraper and quote a fixed price — then deliver clean data straight into your stack.

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