Web Scraping & AI
Reputation-aware IPv4 pools with stable geolocation help reduce blocks and retries, keeping scraping and AI data pipelines reliable at scale.
Why Scraping Fails Today
Most scraping pipelines fail not because of tooling or concurrency limits, but because IP behavior is detected at the network level.
Shared proxy pools reuse the same address ranges, triggering subnet-level bans. Aggressive rotation creates abnormal traffic patterns. Frequent IP churn degrades reputation faster than it recovers. Over time, platforms stop evaluating requests individually and start blocking entire ranges.
The bottleneck is no longer software—it is IP reputation and address structure.
The i.lease Technical Fit
Simplify complex operations and maintain full visibility over your IP assets.
Recommended Block Size
/22 to /20 support controlled rotation and parallel workloads without overexposing a single subnet.
Registry Preference
RIPE and ARIN for broader acceptance and more consistent global reputation signals.
Reputation Validation
Each block is assessed through the Global IP Health Report to ensure high baseline reputation before deployment.
Why it Changes Outcomes
Address space is sourced across distinct ranges instead of fragmenting a single subnet. This reduces correlated bans, enables safer rotation strategies, and keeps traffic patterns closer to legitimate ISP behavior—resulting in fewer sudden block events and more stable long-running data jobs.
Primary Constraint
Reputation + range correlation
What Changes
Dedicated ranges, cleaner footprint
Expected Impact
Fewer sudden block events.
