TOP 7 Proxies for Training LLMs (ChatGPT, Perplexity, Copilot, Gemini, Claude, DeepSeek, etc)

Large Language Models, such as copilots and assistants, translators, conversational models, and research agents, have already become a part of everyday life for many people. However, most casual users don’t understand the sheer volumes of data that go into their chatbot. In this article, we’ll focus on the backend of LLM development and specifically on common problems AI specialists face in training their models.

The issue with LLM training and AI data collection is two-fold, and I’d like to address it as such so that this article can be helpful for both entrepreneurs building their own AI models and professionals working with existing tools at scale. Both instances require processing massive amounts of diverse, current, and clean data, which is impossible to achieve without proxies.

Why You Need a Proxy for LLM Training and AI Data Collection

Proxies are the backbone of any serious data pipeline. Whether you’re web-scraping training data for building AI’s next big thing or using well-known LLMs to their full potential, this work demands arguably the most intense scraping pipeline imaginable – continuous, uninterrupted, fresh, and often geographically-specific. If you’re working with LLMs closely, chances are you’re already aware of these recurring hardships but let’s go over them one by one and find out how proxies solve them.

IP Bans and Rate-Limiting

Training a general LLM requires trillions of text tokens, code snippets, and forum discussions. Aggressive scraping of even one domain from a single cloud-server address can get your IP blacklisted within minutes.

Why proxies: Rotating proxies solve this by distributing requests across a large pool of IPs, which are changing constantly and automatically, ensuring that no single address triggers ban thresholds.

Throttling

Even if your IP doesn’t get outright banned, many servers will throttle repeated requests from the same source, forcing your connection to crawl at extremely low speeds and degrading data freshness.

Why proxies: With a rotating proxy pool, each request appears to come from a different user, bypassing the platform’s throttle logic and maintaining consistent scraping speed.

Global Geo-Targeting

Building an LLM with multilingual capabilities is kinda expected in this day and age, moreover, it significantly boosts your brand reach. However, if your model just speaks the language without knowing the associated culture, regional nuances, native dialects, and local trends – your money basically goes down the drain.

Why proxies: Proxies with granular geo-targeting allow you to scrape local geo-restricted or otherwise altered content (news, pricing, search results, social feeds) by routing traffic through IPs in specific countries, cities, or even ISPs.

Anti-Bot Systems

This issue is especially prevalent for social media, live ticketing, fintech services, and popular e-commerce platforms. As to be expected, the most valuable training data often sits behind aggressive Web Application Firewalls (WAFs) like Cloudflare, Akamai, or DataDome.

These platforms use layered bot detection that includes behavioral analysis, fingerprinting, CAPTCHA challenges, and honeypot traps, allowing them to detect and block machine requests instantly.

Why proxies: Well-configured residential and mobile proxies (especially if paired with a Web Unblocker) mask the cloud-infrastructure origin, automatically mimic organic human browser fingerprints and solve CAPTCHAs natively before the connection is banned.

Real-Time Data Collection

LLM training stops when you stop feeding it data, making your model ultimately frozen in time of that exact moment. While the chatbot won’t mind living in the past, you cannot expect the same from your users, nor can you prohibit them from asking about the current news or events.

Why proxies: Real-time data collection is crucial but it means maintaining a high request volume continuously. The only way of keeping the data flow uninterrupted is a large proxy pool, which ensures that the requests go through without delay even if one IP gets banned.

Additionally, many companies employ Model Context Protocol (MCP) servers with integrated proxies, which act as an abstraction layer for LLM agents. When a user asks an AI agent about a live event, the agent can programmatically invoke a proxy-shielded tool to safely crawl search engines or dynamic public web pages without getting blocked.

Stable Connection for Deep Crawling

Scraping linear articles is easy, but training an AI to understand human dialogue requires downloading deeply nested social forum threads, community discussions, and comment chains. To accomplish this task successfully and follow long online conversations, you need persistent, stable sessions.

Why proxies: By adding sticky sessions (30-60 minutes or Keep-Alive option) to your residential or ISP proxies, you’re providing the scraper stable connection to download entire human conversational trees safely.

Compliance and Legal Auditing

On top of the quality of training data, it’s important to pay attention to *how* said data was obtained, as unethical sourcing carries real legal repercussions like copyright claims, GDPR, and platform ToS disputes.

Why proxies: Some proxy providers enforce strict Know-Your-Customer (KYC) checks and guarantee fully ethical, opt-in peer networks, which can help greatly in proving that your data was gathered through legal public nodes. To know exactly what has been scraped, look for providers that offer audit logs and usage records. Following these practices creates a paper trail that in turn supports your compliance reviews.

API Rate Limits & Concurrency Ceilings

AI providers (like OpenAI or Anthropic) place strict limits on how many requests or tokens you can send per minute. When using existing LLMs as part of a data pipeline (summarization, annotation, synthetic data generation), exceeding that limit is not uncommon for enterprises operating from a single office server.

Why proxies: To save yourself from IP blocks with a “429 Too Many Requests” error, distribute the traffic across a proxy pool and scale your operation headache-free.

Corporate Data Leaks

The risk of internal data being exposed in outbound traffic occurs when thousands of employees use web-based AI tools. Furthermore, public AI platforms track the incoming IP addresses of companies to see what they are working on, which, by itself, poses a threat to your business.

Why proxies: Proxies act as an intermediary layer. By masking the company’s internal network infrastructure and location, they ensure that competitors or AI platforms cannot track your team’s usage patterns, origin, or operational scale. Additionally, it protects your company from being tied to any specific scraping activity.

AI Chat Ban-Loops

Ban-loops can happen on both sides of the LLM workflow. If you’re employing an AI agent to research or scrape data for you, the websites it visits will quickly detect it and flag it as a bot, ultimately banning your IP. On the other hand, you can be banned by the LLM itself – services like ChatGPT, Gemini, or Claude might suspend your account if they suspect automated or high-volume usage.

Why proxies: Both instances, however, can be resolved with proxies. In the case of the AI agent, you’ll need to attach a rotating proxy pool directly to the agent, forcing it to change its digital disguise on every single search it performs. For the second case, use the proxy pool with anti-fingerprinting software on your device. This will reduce detection risk by making each session appear as an independent user.

Multi-Account Management

Operating multiple LLM accounts for testing, benchmarking, or scaling API traffic requires each account to appear as a unique, independent user. Otherwise the AI provider’s fraud detection might flag it as account abuse and terminate the workspace.

Why proxies: The solution here is assigning a clean residential or ISP proxy (often paired with an altered browser fingerprint) to each individual account profile, preventing platforms from linking them and triggering mass bans.

Audit Trails and Cost Allocation

This issue is not an obvious one for young entrepreneurs and rookie CEOs, but it is a concern that constantly looms over your business and always comes back to bite you if you’re not careful, so it’s better to prevent this problem before it burns a hole through your budget.

At enterprise scale, with dozens of teams using AI concurrently, tracking the exact usage of every department and project becomes impossible. This, in turn, significantly complicates further budget allocation, as well as team accountability.

Why proxies: Proxy providers with sub-user management, usage dashboards, and session logging let you tag traffic or even every prompt with specific metadata, which makes it significantly easy to track further down the line.

Which Proxy Type to Choose?

Not all proxies are created equal. There are no winners or losers, top or bottom tiers, rather, each proxy type exists in its own field and a well-configured proxy will provide marvelous results regardless of where it’s coming from – real device or a data center. Choosing the right proxy type for your workflow is essential as it defines the “root” of your connection and in turn, largely determines the success of your operation in advance. In this section, let’s go over pros and cons of every proxy type available on the market and establish their best use cases.

Before diving into the details, here’s the quick version: detection risk drops as you move from datacenter to mobile IPs.

Residential Proxies

Residential proxies are IPs that come from real household devices such as WI-FI routers, smart TVs, or laptops around the world. Owners of these devices often agree to lend their IP addresses to proxy providers for monetary compensation. That is, if the provider has an ethical IP acquisition policy in place and doesn’t acquire residential addresses in sketchy ways. In terms of LLM training, as we’ve established in the previous section, ethical data sourcing is non-negotiable, as operating through unlawfully obtained nodes carries strict legal repercussions.

Residential IPs are the golden standard of many (if not most) data collection and scraping workflows – because of their “human” origin, these proxies are rarely detected by anti-bot services, trigger fewer CAPTCHAs, and hardly ever banned even by the strictest of platforms. Additionally, these IPs are valued for precise geo-targeting, given that they are tied to real physical locations and Internet providers.

On the downside, your proxy speed and connection depends on your host’s system. If the hosting device goes offline, the proxy you’re using dies instantly, same goes for any latency issues the IP owner might have.

Best for: Web scraping from highly-secure or geo-restricted databases and platforms like e-commerce, web-based social media, search engines; scraping multimodal datasets; dialogue, dialect, and localization training; real-time data collection; ChatGPT, Perplexity, Claude, DeepSeek.

What to pay attention to: Provider’s acquisition ethics and geo-targeting depth; IP pool size, cleanliness, and Content Delivery Networks (CDN) reputation; rotation abilities and protocol support.

Datacenter Proxies

The origin of datacenter proxies is right in the name – these IPs are hosted on the cloud servers of large data centers. Datacenter IP addresses are highly popular due to their low cost, stable connection, and low latency. They are often used for tasks that require maximum speed or deal with high volumes of public data, but have a high risk of being blocked by anti-bot systems resulting in frequent flags on high-security sites.

When it comes to LLM training and data collection, datacenter proxies are rarely a primary pick for many developers, but they do have their own niche. These IPs are a great and budget-friendly option for targets with light or no bot protection such as wikis, open-access databases, code repositories, academic journals, and other publicly accessible, legally available data platforms.

The applicability of datacenter IPs goes further than just scraping; they serve as the foundational computing pipelines for downstream AI engineering, processing, and multi-model deployment.

Best for: Web scraping open-access platforms/datasets; load testing and benchmarking; synthetic data scaling; text preprocessing, filtering, and deduplication; load balancing

What to pay attention to: Dedicated pools availability, protocol support, geolocation of data centers, subnet and ASN diversity, hardware ownership, maximum traffic speed and concurrency.

Mobile Proxies

Mobile proxies route your IP through a cellular network using SIM cards assigned to real smartphones. The method makes them similar to residential proxies with one distinction hidden in the difference of operations between internet service providers and mobile operators.

Statistically, one residential IP address is shared between 16 to 32 (in the case of budget ISPs – 62 to 128) households, roughly one medium-sized apartment complex. Cellular carriers have a more aggressive approach – mobile phones consume less continuous port connections than a regular home router, which allows mobile networks to push subscriber density to the max. A single mobile IP address assigned to a cellular tower is more akin to a “channel,” used simultaneously by hundreds to over 1,000 active users.

This discrepancy is the exact reason why, among all proxy types, mobile IPs have the highest trust score and are considered, ultimately, unbannable by anti-bot systems – any platform that tries to block a suspicious cellular connection risks blocking over a thousand of its honest users. As for drawbacks, there’re a couple – mobile IPs have the highest price on the market and offer variable speed.

Best for: Tasks that require cellular connection – mobile apps and social media scraping, account creation and management. Hyper-localized SERP, mobile-first e-commerce platforms, highly protected conversational hubs, Gemini, Grok.

What to pay attention to: Provider’s acquisition ethics, cellular network authentication, ASN and carrier targeting, real-time OS and network fingerprint alignment, multi-port concurrency, manual rotation option, strict traffic capping.

ISP Proxies

ISP (or Static Residential) proxies are the combination of datacenter and residential IP addresses. Large data centers often buy out these IPs from real internet service providers and later host them on their cloud servers. In turn, ISP proxies deliver the data center’s top-notch performance and budget-friendliness, while anti-bot systems see them as regular home addresses registered under well-known providers.

On the surface, ISP proxies sound like a one-size-fits-all type of deal, but that’s not the complete truth. Although ISPs perform outstandingly in any task, they can still be detected by top-notch anti-bot systems for their excessive “cleanliness”.

Another point of consideration is their price – oftentimes ISP IPs sit somewhere in-between cheap datacenter and pricey residential options. However, in some cases, your best bet is to upgrade to residential IPs from the get-go. It is best to weigh your approximate use cases carefully before purchase, so you don’t spend money on proxies that are poorly fit for your workflow.

Best for: Data-heavy or multimodal scraping from streaming platforms; highly-protected business repositories, e-commerce marketplaces, academic libraries; continuous fact-checking and knowledge retrieval (RAG infrastructure); Copilot, Claude.

What to pay attention to: Carrier information and IP sourcing, dedicated pools availability, protocol support, pool replacement and refresh policies.

Best Use Practices – Proxies for LLM Data Collection and Scraping

Now, as we’ve established, proxies are a necessity for any LLM task, if you want to streamline your workflow and save your business from unpleasant consequences – you need proxies.

In this section, let’s review common use cases from the realm of web-scraping and AI data collection and establish what the best proxy configuration would look like for each task individually. Hopefully, later on, you can use this article as a guide for all your proxy needs.

Here’s how dramatically the required proxy pool size can swing depending on the task — from 10K IPs for open-access scraping to 100M+ for real-time RAG pipelines.

High-Volume Scraping from Open-Access Datasets

Bulk-downloading publicly available text, code repositories, and academic papers (Wikipedia, arXiv, GitHub, Common Crawl) at maximum throughput for base model pretraining.

Security level: Low

Data volume: High, tens of TB to PB-scale

Main challenge: Low scraping speed and unstable connection

Social Forum & Conversational Thread Deep Crawling

Downloading deeply nested discussion threads, comment chains, and Q&A exchanges (Reddit, Quora, StackOverflow) to train dialogue and reasoning capabilities.

Security level: Medium to High, depending on the platform

Data volume: Medium, hundreds of GB to low TB-scale

Main challenge: Maintaining consistent sessions across multiple requests; triggering bot-detection systems

Multilingual & Localized Training Data Collection

Scraping geo-restricted content, regional forums, local social feeds, and country-specific search results to build culturally aware, multilingual LLMs.

Security level: Medium to High, depending on the platform

Data volume: High, tens of TB-scale

Main challenge: Accessing geo-restricted and/or geo-altered content without a local IP; triggering bot-detection systems

Scraping Behind WAFs and Anti-Bot Systems

Extracting training data from highly protected platforms like LinkedIn, Instagram, Amazon, or financial data providers that deploy Cloudflare, Akamai, or DataDome.

Security level: High

Data volume: Medium, hundreds of GB to low TB-scale

Main challenge: Bypassing strict anti-bot systems

Real-Time Web Scraping for RAG Pipelines

Continuously feeding a Retrieval-Augmented Generation (RAG) system with fresh data from news outlets, live blogs, financial feeds, and search engine results pages (SERPs).

Security level: Medium to High, depending on the platform

Data volume: Low-Medium, continuous stream rather than bulk volume

Main challenge: Maintaining an uninterrupted request pipeline at high frequencies; triggering bot-detection systems; accessing geo-restricted and/or geo-altered content without a local IP

Best Use Practices – Proxies for LLM and AI Tools Training

In this section, we’ll determine the best proxy configurations for existing LLMs – useful for AI training pipelines and developers working with well-known models at scale. If you’re not building your own AI model, but need to use one available on the market to its full potential, this section is for you.

Best Proxy for ChatGPT Training

Running high-volume OpenAI API calls for fine-tuning, synthetic data generation, or annotation pipelines requires managing multiple API keys and accounts without triggering OpenAI’s rate limits or fraud detection.

Security level: Medium

Main challenge: Staying under per-key rate limits and avoiding account suspension across concurrent API sessions

Best Proxy for Perplexity Training

Using Perplexity at scale for real-time research automation, retrieval-augmented pipelines, or benchmarking its search-grounded outputs demands clean session management to avoid throttling and account flags.

Security level: Medium

Main challenge: Maintaining consistent session identity across high-frequency, search-grounded requests; triggering bot-detection systems

Best Proxy for Copilot Training

Integrating Microsoft Copilot into enterprise-scale workflows for code generation, document processing, or automated reasoning, requires stable, authenticated sessions across multiple accounts and regions.

Security level: Medium to High

Main challenge: Bypassing strict anti-bot systems; triggering identity verification or account lockouts; maintaining persistent sessions

Best Proxy for Gemini Training

Utilizing Google Gemini for large-scale multimodal training tasks, API benchmarking, or automated data pipelines means navigating Google’s aggressive fraud detection and strict per-key concurrency limits.

Security level: Medium to High

Main challenge: Bypassing strict behavioral analysis; per-API-key concurrency ceilings across sessions

Best Proxy for Claude Training

Using Anthropic’s Claude for enterprise annotation, RLHF data generation, or large-scale summarization pipelines requires careful session and account management to stay within Anthropic’s strict usage policies.

Security level: Medium to High

Main challenge: Avoiding account suspension under Anthropic’s usage monitoring; sustaining high-throughput, multi-account API pipelines

Best Proxy for DeepSeek Training

Deploying DeepSeek for large-scale inference, fine-tuning pipelines, or cross-regional benchmarking introduces unique challenges around geopolitical access restrictions and platform-level traffic monitoring.

Security level: Medium to High

Main challenge: Regional access restrictions; platform surveillance

Best Proxy for Grok Training

Training with or benchmarking Grok at scale through X’s API or consumer interface requires managing multiple accounts across X’s aggressive bot detection systems and region-specific access controls.

Security level: High

Main challenge: Layered bot-detection and account integrity systems; sustaining concurrent, high-volume API or interface-based training sessions

Best Proxy Providers for LLM Training

Once you’ve figured out your primary use cases and identified the necessary proxy pipeline, the hunt begins. The game is not played alone – around half of your workflow’s success depends on complementary tools and services you’re utilizing. That claim holds especially true in the context of LLM training, AI data collection, and proxy services. Finding the provider that meets your needs is crucial, otherwise you risk losing time, money, and your patience.

Here are the providers I entrust my tasks to most often, each with their own strengths and weaknesses, so let’s analyze them together.

Provider	Proxy Types	Pool Size	Geo-targeting Abilities	Rotation Abilities	Protocol Support	Starting Price
Floppydata	Residential, Datacenter, Mobile, ISP	65+ Million across 195+ countries	Country, City, State, ASN	Per-request, 5-60 minutes, Sticky sessions/Keep-Alive	HTTP, HTTPS, SOCKS5, UDP	Rotating proxies (Mobile, Residential, Datacenter)- $1/GB, Static datacenter – $1/IP, ISP – $5/IP
1browser	Residential, Datacenter, Mobile, Tor	N/A, 100+ countries supported	Country, City	Quick rotation, Sticky sessions	HTTP, HTTPS, SOCKS5	$7/mo
Gologin proxies	Residential, Datacenter, Mobile	~20 Million with worldwide coverage	Country, City	Automatic rotation every 5-30 minutes, custom rotation through SOCKS5 protocol and user proxies	HTTP, HTTPS, SOCKS5, SOCKS4	$4.50/mo
Oxylabs	Residential, Datacenter, Mobile, ISP	175+ Million across 195+ locations	Continent, Country, City, State, ASN, ZIP code	Per-request, up to 24 hours, Custom sticky sessions	HTTP, HTTPS, HTTP/3, SOCKS5, UDP	Residential – $6/GB, Datacenter – $1.20/IP, Mobile – $7.50/GB, ISP – $1.60/IP
Decodo	Residential, Datacenter, Mobile, ISP	125+ Million across 195+ locations	Country, City, State, ASN	Per-request, 1-60 minutes, Custom intervals up to 24 hours	HTTP, HTTPS, SOCKS5, UDP	Residential – $3.75/GB, Datacenter – $0.6/GB, Mobile – $3.75/GB, ISP – $3.33/IP
Rayobyte	Residential, Datacenter, Mobile, ISP	40+ Million residential proxies across 163+ countries	Country, City, State, ASN	Per-request, 1-60 minutes	HTTP, HTTPS, SOCKS5	Residential – $3.50/GB, Datacenter – $0.30/GB, Mobile – $250/mo, ISP – $5/IP

Floppydata

Floppydata has been my favourite proxy provider for a while. The service provides amazing performance and speed across all proxy types while not costing you an arm and a leg. On top of that, the provider offers a full suite of advanced proxy configuration options – deep geo-targeting with city, state, and ASN levels available; flexible rotation from per-request to Keep-Alive; full protocol support including UDP.

Floppydata’s unique selling point is the “Rotating proxy” plan, which includes three types of IPs (residential, mobile, and datacenter) you can switch between at any given point, paying only for bandwidth – $1/GB. This makes Floppydata one of the best providers for AI data collection, as it allows you to scrape different sources with ease at no extra charge.

Key Features:

• All-encompassing data plan for rotating proxies includes datacenter, residential, and mobile IPs, which you can use at your own discretion, paying only for GBs
• Dedicated scraper APIs for popular use-cases and platforms
• Flexible rotation: per-request, 5 to 60 minute intervals, and sticky/Keep-Alive support
• Great granular geo-targeting
• UDP protocol support
• AI integrations
• Live customer support
• No setup fees, easy plan upgrades/downgrades

Best for: High-volume training data collection; budget-conscious LLM workflows; high-volume multilingual and localized training data collection; real-time scraping pipelines; pinpoint geo-targeted scraping; rotating pipelines; ChatGPT, Perplexity, Claude, DeepSeek.

1browser

1browser is an anti-detect browser with built-in proxy circumvention and multi-accounting capabilities. While anti-detect browsers might not be a first choice when searching for proxy providers, they are a great tool that encompasses all features necessary for LLM workflow into a clean interface – fingerprint isolation, session management, and proxy assignment all handled from one place.

1browser offers a full suite of rotating proxies, several free options, and the ability to connect your own custom IPs for just $7/month, making it a very budget-friendly option for data-heavy tasks. Additionally, the platform supports mobile devices, which can help greatly with processes requiring cellular connection and/or interface. 1browser is a strong pick for developers working with AI accounts at scale, wishing to cut down on setup complexity.

Key Features: 

• Browser fingerprint protection for every profile created
• Built-in residential, datacenter, and mobile proxies
• Free public proxies and free Tor proxies available, making the browser ultimately free-to-use for low-scale tasks
• Custom user-owned IPs supported
• Each profile is fully isolated and customizable – you can assign new proxy, location, and fingerprint data to every account
• 2GB of residential proxies included in paid plans (top-up available)
• No-logs policy
• Mobile and desktop interface support with automatic synchronization across devices
• Simple set-up and user-friendly UI

Best for: AI agent workflows, multi-account scraping, testing LLM tools across isolated sessions; browser-based automation with built-in fingerprint protection; mobile-interface testing; ChatGPT, Gemini, Perplexity.

Gologin proxies

Gologin started as an anti-detect browser and has since expanded into a full-stack automation platform that offers native proxies, cloud profiles, and API frameworks. Like 1browser, Gologin offers built-in fingerprint protection and multi-accounting management, making it a natural fit for LLM workflows that involve browser-based automation, AI agent scraping, or mobile-first platform access.

Gologin provides amazing performance while its interface remains clean, well-structured, and easy-to-use. Enterprises and big teams will appreciate the platform’s account and session sharing that streamlines teamwork and your not-so-tech-savvy co-workers will thank you for choosing Gologin. On top of that, the service offers a 7-day free trial to test the service and decide if it’s the right fit for you.

Key Features:

• Built-in fingerprint and device management
• 7-day free trial
• Proxies can be used outside of Gologin’s app
• Cloud Android phone profiles available for mobile-first platforms
• High performance API, SDK, MCP, and Cloud launch frameworks built for automation, scraping, and AI agents in mind
• 2GB of location data included in paid plans (top-up available)
• Simple set-up and user-friendly UI
• Protected by AES-256 encryption, firewalls, and hosting on secure servers
• Account and session sharing for easy teamwork

Best for: Social media data collection, account-separated scraping, short-session LLM data gathering; browser-based AI agent automation; mobile-first platform access via Cloud Android profiles; team-shared scraping pipelines; ChatGPT, Perplexity, Gemini.

Oxylabs

Oxylabs is a heavy-lifter among proxy providers. The service upholds its reputation by offering a diverse suite of tools, sophisticated proxy infrastructure, enterprise-grade user protection, and outstanding performance.

However, this premium service is reflected in Oxylabs’ pricing – this provider is one of the most expensive on the list. Overall, Oxylabs would be best fit for enterprises, where proxies are needed across departments and workflows as the price-per-GB will go down the more you buy.

Key Features: 

• Residential proxies with fingerprint protection
• Dedicated account managers for enterprise tiers
• Chrome extension, web scraper and SERP APIs, AI Studio, as well as managed datasets
• Automated retry systems
• 99.95% uptime SLA with automated failover

Best for: Enterprise-scale LLM training pipelines; high-volume multimodal scraping; RAG infrastructure and continuous real-time data collection; Gemini, Copilot, Grok.

Decodo

Decodo (formerly Smartproxy) is a reputable mid-tier provider popular for its competitive pricing and great performance. Decodo is a good fit for LLM workflows due to the platform’s AI toolset, which includes a web-scraper API, AI parser, and video downloader, among other useful integrations.

To try out the service, Decodo offers a 3-day free trial for all proxy types (except dedicated static residential (ISP) and dedicated datacenter proxies) with 100 MB of traffic and a 14-day money-back guarantee for paying customers.

Key Features:

• No-code integration support (n8n and similar)
• Multi-account management support
• Additional APIs for scraping and SERP, AI parser, prebuilt templates
• CAPTCHA handling built into the infrastructure
• 3-day free trial with 100 MB of traffic
• 14-day money-back guarantee
• Browser fingerprint protection

Best for: Mid-scale AI data collection and scraping workflows; social forum and conversational thread crawling; ChatGPT, Perplexity, DeepSeek.

Rayobyte

Rayobyte is a reputable provider with over a decade of industry presence. The provider focuses on strict compliance policies and ethical sourcing, which makes it a great fit for enterprises, bound by legal obligation, or developers involved with web-scraping for LLM training. Rayobyte is also one of the few providers that’s able to flaunt direct infrastructure ownership – by operating its own ASN, Rayobyte is able to provide utmost performance and lower market prices for their datacenter and ISP proxies.

Key Features:

• Web unblocker, web scraping API, and self-hosted browser available
• Unlimited threads and sessions
• Ethically sourced IPs with full end-user consent
• Self-owned ASNs provide better performance for datacenter ranges
• Pay-as-you-go model paired with non-expiring data policy
• Complete use-case audits and strict KYC policy before purchase

Best for: High-volume scraping from open-access databases, Microsoft Copilot training, other datacenter and ISP use cases, compliance-sensitive AI projects.

Conclusion

LLM training and AI data collection pipelines require not only massive amounts of data but careful preliminary consideration of the exact complementary tools and infrastructures you have to employ. Hopefully, this article managed to shed some light on this complex subject.