Web Scraping & Data Parsing

Web Scraping & Data Parsing Services

Structured data is one of the most valuable assets a business can hold. Most of it is locked inside websites, portals, and web applications that offer no export button and no public API. Beehive Logic builds custom web scraping and data parsing systems that extract, structure, and deliver that data — reliably, at scale, and within legal boundaries.

We deliver scraping infrastructure as a managed API, as a self-service UI product, or as an embedded component inside your existing platform. Projects are available as full outsource deliveries or as outstaffing engagements for teams that need Go scraping expertise.

Delivery Formats

Scraping as an API

Your application calls an endpoint; it receives clean, structured data. No scraping logic lives in your codebase.

• On-demand scraping API — your system sends a URL or a query; the scraper returns parsed data as JSON within seconds or via a webhook once the job completes
• Scheduled data feeds — scrapers run on a defined schedule (hourly, daily, weekly) and push results to your database, S3 bucket, or a webhook endpoint
• Bulk extraction API — submit thousands of URLs in a single request; results are streamed back as jobs complete
• Diff and change-detection API — monitor target pages for changes; receive an alert only when content actually changes, not on every poll
• Normalisation layer — raw scraped data is cleaned, deduplicated, and mapped to your schema before delivery

API responses are available in JSON, NDJSON (streaming), CSV, or Parquet for data pipeline compatibility.

Scraping with a User Interface

For teams that need to configure, monitor, and manage scraping jobs without writing code, we build dedicated web UIs:

• Visual scraper builder — point-and-click interface to define what to extract from a page: select elements, map them to data fields, preview results in real time before saving the configuration
• Job scheduler and dashboard — configure cron-based schedules, view run history, inspect failed jobs, download result files
• Live monitoring panel — real-time view of active scraping workers: pages per minute, error rate, proxy health, queue depth
• Data explorer — browse, filter, and export collected data without leaving the browser; supports inline editing to correct misparses
• Alert configuration — set rules to receive Slack, email, or webhook notifications when data changes, jobs fail, or result counts fall outside expected ranges
• Multi-user access — role-based access so data analysts, developers, and business stakeholders each see and control what is appropriate for them

Technical Capabilities

Browser Emulation

Many modern websites render content entirely in JavaScript, protect data behind login walls, or actively detect and block simple HTTP scrapers. We handle this with full browser automation:

• Playwright (via playwright-go) — cross-browser automation supporting Chromium, Firefox, and WebKit; handles JavaScript rendering, SPAs, and shadow DOM
• Rod — lightweight Go-native Chromium DevTools Protocol driver; low overhead for high-concurrency headless scraping
• Stealth mode — patches that suppress headless browser fingerprints: disabling navigator.webdriver, spoofing canvas and WebGL signatures, randomising user-agent and viewport
• Human behaviour simulation — randomised mouse movement, realistic typing delays, scroll patterns, and click timing to reduce detection probability
• Session and cookie management — maintaining authenticated sessions across multiple pages and requests, handling CSRF tokens and dynamic form fields

Anti-Bot Bypass

We have experience working around common anti-scraping measures — within ethical and legal limits:

• CAPTCHA solving integration — 2Captcha, Anti-Captcha, CapSolver, and heuristic pre-solving where applicable
• Cloudflare and WAF bypass — Cloudflare Turnstile, JS challenge handling via headless browsers and TLS fingerprint spoofing
• Rate limiting mitigation — adaptive request throttling based on response codes, retry-with-backoff strategies, and request jitter
• Dynamic rendering detection — automatic fallback from HTTP to headless browser when JavaScript-rendered content is detected

Proxy Infrastructure

IP reputation is the most common reason scrapers get blocked. We design and integrate proxy layers that make scraping resilient:

• Residential proxy pools — integration with providers such as Bright Data, Oxylabs, Smartproxy, and IPRoyal; residential IPs that appear as genuine end-user traffic
• Datacenter proxy rotation — cost-effective for targets with lighter anti-bot measures; rotated automatically per request or per session
• Mobile proxy integration — for targets that specifically trust mobile carrier IP ranges
• Geo-targeting — route requests through IPs from specific countries, regions, or cities to access geo-restricted content
• Custom proxy pool management — if you run your own proxy infrastructure, we build the rotation logic, health checking, and automatic failover
• Sticky sessions — maintain the same IP across a multi-step workflow (login → navigate → extract) where IP changes would break the session

Data Parsing & Extraction

Raw HTML is rarely useful on its own. We build parsing layers that turn markup into structured, reliable data:

• CSS selector and XPath extraction — precise targeting of specific elements; robust to minor layout changes
• LLM-assisted parsing — where page structure is inconsistent or highly variable, we use language models to extract fields from natural language content (product descriptions, legal text, unstructured tables)
• PDF and document parsing — extracting data from PDFs, DOCX, and XLSX files linked from or embedded in web pages
• Image and screenshot OCR — extracting text from images using Tesseract or cloud OCR services
• Structured data extraction — JSON-LD, Open Graph, schema.org microdata parsed directly from page source
• API reverse engineering — identifying and calling the internal JSON APIs that a website’s frontend uses, bypassing HTML parsing entirely where possible

Storage & Pipeline Integration

Scraped data needs to go somewhere useful:

• PostgreSQL / MySQL — relational storage with proper schemas, indexes, and deduplication keys
• MongoDB — for semi-structured or highly variable data shapes
• ClickHouse / BigQuery — for analytical workloads where you query millions of rows
• S3 / GCS / Azure Blob — raw file storage for JSON dumps, CSV exports, and screenshot archives
• Kafka / RabbitMQ — streaming scraped records into your existing data pipeline
• Webhook delivery — push each scraped record to your endpoint in real time as it is extracted

Common Use Cases

Legal & Ethical Boundaries

Web scraping exists in a legally nuanced space. We only build systems that:

• Target publicly accessible data not hidden behind authentication (or target authenticated data with your own valid credentials)
• Respect robots.txt directives unless you have specific grounds to do otherwise and accept the associated risk
• Comply with GDPR, CCPA, and applicable data protection regulations — we do not build systems designed to collect personal data unlawfully
• Operate at request rates that do not constitute a denial-of-service attack on target infrastructure
• Align with the Terms of Service of target platforms, or where scraping is legally permitted despite ToS restrictions (jurisdiction-dependent)

We discuss the legal posture of every scraping project during discovery and will decline engagements where the intended use is clearly unlawful.

Engagement Models

Contact us to discuss your data requirements and get a technical feasibility assessment.