Enterprise-grade data infrastructure

This is the core of what we do. We are in a constant "arms race" against increasingly sophisticated anti-bot technologies, and we built our entire infrastructure to win it. A multi-layered strategy lets us reliably access data from the most difficult sources, including global e-commerce platforms and financial institutions. It combines several integrated systems:

Intelligent proxy & IP management: We operate our own global network of residential, ISP, and mobile proxies. Our platform automatically rotates IPs, mimics human browsing patterns, and uses geo-targeting to defeat IP-based blocking and rate limits.

Advanced anti-bot & CAPTCHA solvers: We use a fleet of smart, headless browsers that render JavaScript-heavy sites exactly as a normal browser would. These are equipped with our proprietary AI models trained to automatically identify and solve CAPTCHA challenges, so data collection keeps running. We are experts at defeating advanced measures like JS fingerprinting, HTTP/TLS fingerprinting, and even mouse movement intelligence.

Continuous adaptation: Our platform watches source websites for structural changes and new defenses. When a change affects data collection, the system raises an alert and our engineering team adapts the logic, within resolution times guaranteed by our SLA.

We designed our platform from day one for huge, unpredictable workloads. Every scraper we run sits on a highly available data acquisition engine.

Scalable by design: We run a decoupled microservices architecture on Kubernetes. This approach is designed to avoid single points of failure and allows us to perform rolling updates for any component without taking the whole system down, at a scale of billions of requests.

Contractual guarantees: We provide a standard 99.9% uptime SLA for our core systems that orchestrate scraper execution.

Yes. Scraping native mobile apps is a "completely different universe of complexity", and a rare skill set that most engineering teams lack. We specialize in it.

The mobile black box: Mobile apps use advanced security like private APIs, encrypted traffic, and SSL/certificate pinning to prevent data extraction. Our team uses advanced reverse-engineering techniques to understand how the app communicates with its servers.

Dedicated mobile infrastructure: We build systems that talk to the app's API exactly like a real phone, so we get around roadblocks like certificate pinning and pull clean, structured data straight from the source.

Getting data into your system should be the easy part. We deliver analysis-ready data straight into your environment with minimal effort from your team, through several integration methods:

Direct-to-warehouse: We use pre-configured, native connectors for major cloud warehouses like Snowflake, BigQuery, and Redshift. Data is automatically loaded into your specified tables on a set schedule.

Managed REST API & webhooks: You can pull data from our secure REST API on demand, or we can use webhooks to push new or updated data to your specified URL the moment it's ready.

Cloud storage & high-performance formats: We can drop files directly into your cloud storage bucket (e.g., Amazon S3, Google Cloud Storage). For massive datasets, we provide data in high-performance formats like Parquet or Avro, ready for BI & ML applications.

We are obsessed with data quality, because bad data corrupts analytics and erodes trust. Our QA process has two stages: automated checks first, then manual verification by our analysts.

1. Automated QA checks: Every dataset passes through a series of automated checks that validate its structural integrity and logical consistency. This includes checking for correct formatting, verifying completeness against previous runs, and flagging logical anomalies (e.g., a price that is completely outside a reasonable range).

2. Manual "ground-truth" verification: Automated checks catch a lot, and our QA analysts make the accuracy final. They take a data sample and compare it field by field against the source application, so the data we deliver matches what a real user sees, backed by the 99.93% accuracy in our SLA. Every discrepancy is documented and escalated for resolution, which is how we can guarantee accuracy in the contract.