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AI Data Extraction

Self-Adapting Pipelines — Structured Data, at Scale

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AI Data Extraction illustration

Your team spends hours every week on manual data collection, and the scripts that are supposed to help break every time a source updates. We extract structured data from websites, APIs, and public platforms — clean, formatted, and delivered in the exact structure you need — with self-adapting pipelines that keep running when sources change.

Obox Systems is an international software engineering company headquartered in the US, specializing in automated data extraction and intelligence pipelines. Engagements are led by our CTO, backed by a structured team with mandatory peer review; NDA available on request.

Proven: 20–30% less bad data and 30–40% faster validation for an enterprise analytics team; 90% less manual collection on a scraping pipeline; 20x faster ingestion on an e-sports data engine.

We can help you with:

  • Extraction from websites, e-commerce, and public platforms — Playwright and Selenium scrapers with proxy rotation for product, price, listing, and business data
  • API integration and raw data extraction — every source unified into one schema
  • Self-adapting pipelines — LLM-based parsing (Skyvern, Relevance AI, Vertex AI) that keeps working when page layouts change
  • Data cleaning and validation — Rust and Pandas pipelines for deduplication, normalization, and quality checks before delivery
  • Scheduled delivery — to your database, Airtable, or API, orchestrated with n8n, with monitoring and alerts
  • Full ownership — source code, infrastructure config, and docs stay yours

The Diagnostic Architecture Audit reviews your data sources and validates the extraction approach in five days — a written plan you own.

Technologies we use

  • Python
  • Selenium
  • Pandas
  • n8n
  • Rust
  • Skyvern
  • Relevance AI
  • Airtable
  • Vertex AI

Packages

Diagnostic Architecture Audit

A review of your data sources and current scripts — access, structure, change frequency, data quality risks, and a pipeline architecture with a technical roadmap

5 days

Rapid Technical Spike / PoC

A working extraction pipeline for one priority source — clean, validated output in your format, with a run report on accuracy and stability

10–15 days

Dedicated Engineering Squad

A dedicated Obox engineering team that runs and evolves your data pipelines — new sources, monitoring, fixes when sources change, with all code and IP staying yours

Monthly retainer

Core Modernization Sprint

Fragile scripts or manual collection replaced in phases by a self-adapting pipeline — scheduling, validation, monitoring, and delivery to your database or API

Milestone-based

Case Studies

Eneo Scraping project screenshot
AI Data Extraction

Eneo Scraping

Germany1 month

Built a Rust-based, AI-powered contact enrichment system with a hybrid scraping strategy that cut manual research workload by 90% and API costs by up to 80%.

DataFlow Automation Engine project screenshot
AI Data ExtractionRust Development

DataFlow Automation Engine

Ukraine3 months

A custom automation engine that authenticates, extracts data, and delivers it to analytics tables and Telegram in real time, with client-configurable columns and 24/7 monitoring.

Microservice System for Business Data Analytics project screenshot
Rust DevelopmentDevOps

Microservice System for Business Data Analytics

United States24 months

A high-performance Rust ETL pipeline for a data-analytics company, fetching from many remote sources asynchronously with custom transforms, multithreading, and resilient error handling.

Recruitment Automation Platform project screenshot
AI Systems Engineering

Recruitment Automation Platform

Ukraine1 month

Built an AI-driven recruitment automation platform that aggregates candidates from APIs and email scraping, eliminating 95% of manual data entry and increasing process setup speed by 50%.

FAQ

  • We build pipelines, not one-off scripts: ML and LLM-based parsing that adapts to layout changes, validation before delivery, and monitoring that flags a broken source before your data goes stale.

  • Every pipeline runs validation before delivery — schema checks, deduplication, and completeness rules agreed with you. You review a sample of the output before the full run, and quality checks stay in place after handover.

  • We schedule extraction at the frequency the data needs — hourly, daily, or event-driven — and track source changes, so updates reach your database or API automatically instead of through manual re-runs.

  • Skyvern automates browser workflows using AI, adapting to layout changes for tasks like form filling and data extraction, with local or cloud deployment. Relevance AI lets us create AI agents with low-code tools to automate tasks, ensuring security and efficiency across workflows.

  • Yes. Start with the five-day Diagnostic Architecture Audit, then a Rapid Technical Spike on one source. For ongoing needs, a Dedicated Engineering Squad on a monthly retainer runs and maintains the pipelines — cost spread over time.

  • Scraping projects have a known risk: target sites change layouts. We build resilient selectors and include monitoring in every delivery. Milestone budgets are fixed with clear scope — if a target site requires additional reverse engineering, we flag it with cost impact before proceeding.

  • An enterprise analytics client embedded our Rust data pipelines into their PySpark ETL — 20–30% less bad data and 30–40% faster validation. A web scraping pipeline cut manual collection by 90%, and an e-sports ingestion engine reached 20x faster throughput.

  • Yes. We sign NDAs before any technical discussion begins, on request.

  • You do. IP, source code, architecture docs, and deployment runbooks are fully assigned to you on completion — no vendor lock-in.

  • Yes. Signed contracts with fixed scope per phase. Wyoming LLC — you’re contracting with a registered entity, not an individual.

Book a free call

Consult with our engineering team to define the perfect solution for your needs.

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30 minutes