Question 1

How do proxies help with LLM training data collection?

Accepted Answer

LLM training requires collecting data from thousands of sources over extended periods. Rotating residential proxies ensure no single IP accumulates enough requests to trigger rate limiting or blocking. Each request appears as fresh organic traffic from a different user, allowing continuous collection at any scale.

Question 2

Can I use sticky sessions for AI agent workflows?

Accepted Answer

Yes. Sticky sessions pin your agent to a single IP for the full duration of a multi-step workflow — login, navigate, extract, submit — without session resets mid-task. You can hold a sticky session for up to 120 minutes via a sessid parameter or dedicated sticky port.

Question 3

What proxy type is best for AI data collection?

Accepted Answer

Residential proxies are the standard for AI training data collection. They use IPs assigned to real home internet connections, making them indistinguishable from organic traffic. Datacenter IP ranges are blocked by most major web sources and unsuitable for continuous scraping pipelines.

Question 4

How do I avoid rate limits when collecting training data at scale?

Accepted Answer

Use rotating residential proxies so each request originates from a different IP. Set a realistic request cadence — mimic human browsing intervals rather than sending requests at machine speed. For sources with aggressive rate limiting, distribute collection across multiple geographic locations using geo-targeting.

Question 5

Can I collect geo-diverse training data from 210+ countries?

Accepted Answer

Yes. RaxyProxy supports country, state, and city-level geo-targeting across 210+ countries. This lets you build training datasets that represent global linguistic and cultural diversity — critical for multilingual and region-aware AI models.

Question 6

How do proxies support RAG (Retrieval-Augmented Generation) pipelines?

Accepted Answer

RAG pipelines need continuous access to live web sources to keep LLM knowledge current. Proxies provide unblocked access to news sites, documentation portals, market data feeds, and other sources that block datacenter IPs or rate-limit heavy access. Your retrieval system stays current without being blocked.

Question 7

What scraping frameworks work with RaxyProxy for AI projects?

Accepted Answer

Any framework that supports standard HTTP/HTTPS or SOCKS5 proxies works with RaxyProxy: Scrapy, Playwright, Puppeteer, Selenium, BeautifulSoup with requests, LangChain web loaders, LlamaIndex data connectors, and custom Python or Node.js scrapers. No SDK or proprietary integration required.

Question 8

Do you have high-volume plans for AI teams collecting training data?

Accepted Answer

Yes. RaxyProxy uses pay-per-GB pricing with no subscription commitment — scale from a few GB for initial experiments to terabytes for full pre-training pipelines. Contact our team for enterprise pricing if your monthly volume exceeds standard plan thresholds.

Typ	Am besten für	Erkennungsresistenz
Residential Proxys	Scraping, Monitoring, Datenpipelines	Höchste
Mobile Proxys	Social Media, mobile Plattformen	Höchste (Carrier-ASN)
Datacenter Proxys	Geschwindigkeitskritische, wenig erkannte Ziele	Niedrig
Premium Residential Proxys	Hochwertige Überwachung, Markenschutz	Höchste + Uptime-SLA

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Warum RaxyProxy für KI & LLM-Datenerfassung?

LLM-skaliger IP-Pool

Georepräsentative Daten

Kontinuierliche 24/7-Pipelines

Sticky Sessions für Agenten

Bot-Detection-sicher

Jeder Stack, direkt einsetzbar

Gängige Workflows

LLM-Trainingsdatenerfassung

KI-Agenten-Workflows

Echtzeit-Daten für RAG

Residential Proxys

KI & LLM-Datenerfassung: der vollständige Leitfaden

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