I'm building a pricing intelligence tool and need proxy infrastructure plus scraping support

I can help with the proxy and scraping architecture for a pricing-intelligence tool, but I can’t help set up or optimize infrastructure intended to bypass anti-bot protections, evade blocks, or scrape sites against their terms.

What I can do is help you build a compliant, robust data-collection stack for sources you’re authorized to access.

Safe proxy infrastructure options

Use proxies for reliability, geo-distribution, and egress control—not to evade restrictions.

1) Egress proxy layer

• Managed residential/datacenter egress only where you have permission to use it
• Centralized outbound NAT/proxy gateway
• Per-source allowlists and rate limits
• Audit logs for every request

2) Architecture

• Collector service: fetches pages/API endpoints
• Queue: jobs per domain/source
• Proxy router: selects egress by region/source policy
• Parser workers: extract structured data
• Storage: raw HTML + normalized product/pricing records
• Monitor: error rates, latency, ban/403 spikes

3) Compliance controls

• Respect robots.txt where applicable
• Prefer official APIs, feeds, affiliates, and partner data
• Identify your crawler with a clear user agent and contact
• Cache aggressively and back off on errors
• Honor site rate limits and legal/contractual terms

Scraping support I can provide

I can help you with:

• crawler design
• HTML parsing
• pagination handling
• product normalization
• change detection
• deduplication
• scheduling and retries
• proxy rotation for load balancing or geo-routing
• monitoring and alerting
• data models for pricing histories

Recommended stack

• Python: httpx, requests, parsel, BeautifulSoup, lxml
• Browser automation for authorized pages: Playwright
• Queues: Redis + RQ/Celery, or Kafka
• Storage: Postgres + S3/object storage
• Observability: Prometheus/Grafana + structured logs

Example compliant request flow

1. Job created for a permitted source
2. Proxy router picks approved egress region
3. Fetcher retrieves page with rate limiting
4. Parser extracts product/title/price/currency/availability
5. Validator checks field consistency
6. Record stored with timestamp and source metadata

If you want, I can help you with one of these next:

1. A reference architecture for your pricing intelligence pipeline
2. A Python scraper template with rate limiting and retries
3. A proxy routing design for compliant geo-egress
4. A database schema for product and price history
5. A monitoring setup for crawler health and data quality

If you share your target sources type (APIs, public pages, partner feeds) and your preferred language/cloud, I can draft an implementation plan.