Proxycurl

Extracts structured profile data from LinkedIn URLs without official API access by implementing web scraping with anti-detection measures, parsing HTML/JavaScript-rendered content, and normalizing unstructured profile information into standardized JSON schemas including work history, education, skills, and contact information. Uses rotating proxies and request throttling to avoid detection while maintaining data consistency across profile variations.

Scrapes and structures company information from LinkedIn company pages including employee count, industry classification, funding status, company description, and organizational hierarchy. Implements domain-based company matching to link company data with email domains and normalizes company metadata across different LinkedIn page variations and historical data.

Implements server-side response caching for frequently requested profiles and companies, reducing redundant scraping and improving response latency. Provides cache hit/miss indicators in API responses and supports cache invalidation through optional parameters. Implements request deduplication to identify duplicate requests within a time window and return cached results instead of re-scraping, reducing API quota consumption and improving performance.

Provides official SDKs and community-maintained libraries for popular programming languages (Python, JavaScript/Node.js, Ruby, PHP, Go) with language-idiomatic APIs, built-in error handling, retry logic, and type definitions. SDKs abstract HTTP request handling and provide convenient methods for common operations like profile lookup, company enrichment, and batch operations. Includes comprehensive documentation and example code for each language.

Supports webhook callbacks for asynchronous batch operations and long-running requests, delivering results to a specified endpoint when processing completes. Implements webhook retry logic with exponential backoff for failed deliveries and provides webhook signature verification for security. Enables real-time integration with downstream systems without requiring polling for results.

Extracts structured job posting information from LinkedIn job listings including job title, description, salary range, required skills, seniority level, and company details. Implements NLP-based job classification to categorize postings by role type, industry, and skill requirements, and tracks posting metadata including publication date and application count for job market analysis.

Extracts lists of employees from LinkedIn company pages by scraping employee directory data and implementing pagination to retrieve large employee rosters. Normalizes employee records with available profile information and links employees to company hierarchy when available. Handles rate limiting and anti-detection to maintain access while retrieving potentially thousands of employee records per company.

Performs reverse lookups on email addresses to identify associated LinkedIn profiles and company information by matching email domains to company records and parsing email patterns. Validates email format and deliverability while enriching with available LinkedIn profile data. Implements domain-based matching to link corporate emails to company profiles without requiring direct profile URLs.

Supports batch API requests for enriching multiple profiles, companies, or emails in a single operation, implementing request queuing and async processing to handle large-scale enrichment workflows. Provides webhook callbacks or polling mechanisms to retrieve results asynchronously, reducing latency for bulk operations and enabling efficient data pipeline integration. Implements request deduplication and caching to optimize API quota usage.

Normalizes extracted LinkedIn data into consistent JSON schemas across different data types (profiles, companies, jobs) with standardized field naming, data types, and null handling. Implements schema versioning to handle API changes and provides optional field filtering to reduce payload size. Handles nested data structures for work history, education, and skills with consistent formatting across all endpoints.

Implements tiered API rate limiting with free, paid, and enterprise tiers, providing different request quotas and rate limits per tier. Tracks quota usage in real-time and provides quota status in API responses, enabling clients to monitor consumption and implement backoff strategies. Supports quota pooling across multiple API keys for enterprise customers and provides quota reset scheduling.

Implements sophisticated anti-detection mechanisms including rotating residential proxies, request fingerprinting, and adaptive rate limiting to maintain access to LinkedIn data without triggering detection systems. Uses browser automation techniques to simulate legitimate user behavior and handles CAPTCHA challenges through integration with CAPTCHA solving services. Maintains proxy health monitoring and automatic failover to ensure consistent data availability.

Implements comprehensive error handling with specific error codes for different failure modes (rate limiting, detection, invalid input, server errors) and provides automatic retry logic with exponential backoff for transient failures. Distinguishes between retryable errors (rate limiting, temporary blocks) and permanent errors (invalid URLs, authentication failures) to optimize retry strategies. Provides detailed error messages and suggestions for resolution.