AI & LLM Data Collection Proxies

AI teams have become the largest new buyers of proxy bandwidth: crawling for pretraining corpora, keeping RAG indexes fresh, and letting agents browse in real time.

Crawling for training data

Pretraining and fine-tuning corpora need breadth across millions of domains. Cost per successfully fetched document — not per GB — is the metric that decides whether a crawl is viable.

Keeping RAG fresh

Retrieval indexes decay. Recrawling changed pages on a schedule needs stable, high-success proxying plus cheap change detection via conditional requests and content hashing.

Browsing agents

Agents that click and read pages behave unlike crawlers: bursty, session-bound, and latency-sensitive. Give them sticky residential sessions and a managed browser rather than a raw rotating gateway.

Respecting the commons

Honour robots.txt, publish an identifiable user agent, throttle politely and cache hard. Aggressive AI crawling is what pushed most large publishers behind bot walls in the first place.