Is parsing legal in Germany?

Parsing publicly available data is legal when robots.txt and GDPR are respected. We only work with open data and advise on the legal aspects of each specific case.

What happens if the source site changes its structure?

We build parsers with resilience to changes and include a support period during which we adapt the solution when the source changes.

In what format do you deliver the collected data?

In any format that suits you: CSV, JSON, Excel, PostgreSQL or MySQL database, Google Sheets — we configure delivery to fit your infrastructure.

Data Parsing in Dresden

We develop parsers and scrapers for automatic data collection from open sources — for Dresden companies, research institutes, and analytics teams.

Competitor price monitoring, data collection for research, job aggregation, or market analysis — all of these require regular collection of large volumes of information from public sources. Doing it manually means spending your team's time on a task that's easy to automate.

We develop reliable parsers that collect the data you need automatically on a schedule and deliver it in a convenient format to your system. The entire process is organised in compliance with GDPR and ethical data collection standards.

What's included in parser development

Source analysis
we study target websites and APIs and determine the appropriate data collection method. You get a technical solution that works stably even when the source site changes.
Parser development
we write the script with bot protection bypass, error handling, and logging. You get a reliable tool that doesn't break at the first page structure change.
Processing and structuring
we clean, normalise, and structure the collected data. You get a clean dataset ready for analysis or import into your system.
Automation and delivery
we set up scheduled runs and data delivery in the format you need: CSV, JSON, database, Google Sheets. You get up-to-date data automatically without manual triggering.

Research organisations
automated data collection for scientific and analytical projects.
Tech companies
competitor monitoring, news aggregation, and tracking technology trends.
Manufacturing enterprises
parsing supplier prices and monitoring raw material markets.
Tourism services
aggregating availability and pricing data for accommodation and transport.
Startups
building training datasets for ML models and market analysis.
Marketing teams
collecting reviews, mentions, and data for competitive analysis.