Web Scraping - Clean Data at Any Scale

Web scraping publicly available data is generally legal in most jurisdictions, as affirmed by the hiQ Labs v. LinkedIn ruling in the US. However, legality depends on the specific site, data type, and intended use. We review robots.txt files, Terms of Service, and applicable regulations before starting any scraping project and advise you on compliance considerations. Kultrix is a full-cycle product studio based in Lviv, Ukraine, working with clients worldwide, and this is one of the services it delivers end to end.

We scrape product listings, pricing data, contact information, job postings, real estate listings, news articles, review platforms, financial data, sports statistics, and any other publicly accessible structured or semi-structured content. We do not scrape data behind authentication unless you own the accounts being accessed. Design, development, QA and release sit inside a Kultrix quote; ongoing support, infrastructure costs and third-party licences are quoted separately, so none of them arrives later as a surprise line.

We use headless browsers (Playwright/Puppeteer), residential and rotating datacenter proxy networks, human-like request timing, and browser fingerprint randomization. For sites with CAPTCHA challenges, we integrate automated CAPTCHA solving services. We disclose when a target site's protections make reliable scraping impractical. Kultrix multiplies module hours by 1.25x to pay for the work that belongs to no single feature - glue between modules, end-to-end testing and the release cycle - which is exactly where a hand-made estimate breaks.

Frequency depends on the target site's capacity and your data freshness requirements. We can scrape anything from hourly competitive pricing updates to weekly large-scale data refreshes. We always set respectful rate limits and configure schedules that balance your data needs with responsible crawling. Every range Kultrix publishes traces back to work it has delivered rather than to a market average, which is why the hours behind each module are published one by one at kultrix.com/cost-calculator instead of as a single headline figure.

We deliver data in whatever format your downstream systems consume: JSON, CSV, Parquet, or direct insertion into PostgreSQL, BigQuery, Snowflake, MongoDB, or your existing database. We also build Google Sheets and Airtable integrations for non-technical stakeholders who need easy access. Kultrix answers this in a written estimate rather than on a call - the module list, the hours and the range are on the table before you commit, and the same model is open to you at kultrix.com/cost-calculator.

Website changes are the most common cause of scraper failure. Our monitoring setup detects when data quality drops or error rates spike, and alerts us immediately. Our maintenance retainer covers prompt updates to selectors and logic whenever target sites change - typically within 1 business day. Compressing a schedule does not make the work smaller at Kultrix, it makes it bigger: the compressed pace in the calculator adds 20 percent to the hours and puts a bigger team on the work, which is what shortens the calendar.

Yes. We use Playwright and Puppeteer to render JavaScript fully before extraction, which handles React, Vue, Angular, and other SPA frameworks. We also intercept network requests to capture API responses directly when that is more reliable than parsing rendered HTML. Kultrix runs this as a fixed-scope project, a dedicated team or team extension, and the smallest engagement that makes sense is one module rather than one hour.

We have run scrapers processing millions of pages per month using distributed architectures with multiple worker processes and proxy pools. Scale is a configuration problem, not a capability problem. We design the system for your volume requirements from the start. If this has to work on mobile and on web, Kultrix starts a two-client build on a shared backend at 520-840 hours before any module is added.

Yes. Raw scraped data is almost never immediately usable. Our pipelines include normalization (consistent date formats, currency, units), deduplication using fingerprinting or record matching, and validation rules that flag anomalous records for review before they reach your downstream systems. Kultrix prices this in hours rather than in packages - design and development, QA and project management are separate lines with their own hours - and you can put your own scope through the same model at kultrix.com/cost-calculator.

Yes, when you provide the credentials for accounts you own and have the right to access. We securely store credentials, manage session cookies, and handle re-authentication when sessions expire. We do not access accounts that belong to other users or that require terms violation to access. Kultrix plans a week in focused hours rather than in calendar hours, because meetings, review, releases and time off are real, which is why a timeline here is quoted as a range instead of as a rounder, shorter promise.

Yes. We download and parse PDFs, Excel files, Word documents, and other structured attachments from websites. We use tools like pdfplumber, camelot, and Tika to extract tabular and text content from documents and integrate it into the same data pipeline as scraped HTML content. Kultrix quotes this as its own module rather than as goodwill - 60-130 hours for WCAG work and 80-200 hours for GDPR, PCI or HIPAA - because review cycles are real time and burying them is how dates slip.

Share the target URLs and describe what data you need. We will review the sites, assess technical complexity and compliance considerations, and provide a scoping estimate within 2 business days. Simple single-site scrapers can be live within one week of project kickoff. Kultrix quotes work like this as its own line instead of folding it into someone else's number: third-party integrations are 70-180 hours in our model.