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Custom-tailored data
Get data tailored to your project, reduce development time, and ensure the AI is trained only on the most relevant data.
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Artificial Intelligence
AI Data Collection
Scale your data collection for AI model training and automate processes with our advanced proxies and web scraping solutions tailored to your needs.
HTML, JSON, or table format
100% success rates
No CAPTCHAs
#1 in IP quality
Unlimited threads & concurrent sessions
14-day money-back option
Train AI models with diverse, high-quality data
Diverse, high-quality, and real-time data is crucial for AI development. It ensures the model can perform well across various contexts and tasks, making your application more accurate and reliable.
Real-time information
Keep up to date by periodically scraping the web to update your AI model with the latest relevant information and trends.
Bias avoidance
Collect large amounts of diverse data to ensure that the model remains unbiased and considers multiple sources.
Gather web data without restrictions
Effortlessly scrape any website without encountering rate limitations or IP blocks. With Smartproxy’s premium quality proxies, you can bypass CAPTCHAs and other challenges, ensuring seamless access for your scripts to the target data. Maximize the potential of our schedulable SERP, eCommerce, Web, and Social Media Scraping APIs to receive up-to-date information in easy-to-read JSON, HTML, and table formats, perfect for integration with LLMs.
Top IP quality
Get top-notch IPs from worldwide locations with high success rates to ensure access to any website without limitations.
Multiple output options
Enjoy multiple output options ranging from JSON to HTML – no matter whether you need your data raw or parsed in a table.
Effortless data collection
Access scraping tools that make data collection a breeze, from ready-made scraping templates to task scheduling.
Streamline data integration
Fastest time to value
Use web scrapers to speed up AI application development by giving on-demand access to vast amounts of real-world data. This data can be directly integrated into ML pipelines, which cuts down the time needed to collect and prepare training data.
Secure training data for LLMs and AI models
Web scrapers can be configured to follow privacy regulations, ensuring safe and compliant data usage. By automating data collection, organizations avoid regulatory fines and ensure that the data used for training AI models meets privacy standards, providing a secure base for machine learning development.
Improved ML performance
Web scrapers help gather diverse data from different online sources, essential for improving machine learning performance. They automatically extract large amounts of well-labeled, high-quality data, enabling the creation of more robust ML models that perform well in various contexts and applications.
Tailored datasets
Customized and personalized datasets offer a clear edge over ready-made options by focusing on data that fits your specific needs. This method simplifies learning by removing excess and irrelevant information. By tailoring datasets to match your needs, you optimize AI model performance and accuracy.
Easy-to-use proxies
Our proxies work with all popular programming languages, ensuring a smooth integration with other tools in your business suite.
using System;using System.Collections.Generic;using System.Linq;using System.Net;using System.Net.Http;using System.Text;using System.Threading.Tasks;class Program{static void Main(string[] args){Task t = new Task(DownloadPageAsync);t.Start();Console.ReadLine();}static async void DownloadPageAsync(){string page = "https://ip.smartproxy.com/json";var proxy = new WebProxy("gate.smartproxy.com:10001"){UseDefaultCredentials = false,Credentials = new NetworkCredential(username: "username",password: "password")};var httpClientHandler = new HttpClientHandler(){Proxy = proxy,};var client = new HttpClient(handler: httpClientHandler, disposeHandler: true);var response = await client.GetAsync(page);using (HttpContent content = response.Content){string result = await content.ReadAsStringAsync();Console.WriteLine(result);Console.WriteLine("Press any key to exit.");Console.ReadKey();}}}
Explore our products
- What are proxies?
A proxy is an intermediary between your device and the internet, forwarding requests between your device and the internet while masking your IP address.
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Residential proxies from $2.2/GBReal household device IPs with certain physical locations.
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Static residential proxies from $2/IPISP IPs blending residential proxy authenticity with datacenter proxy stability.
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Site Unblocker from $6/IPAdvanced proxy solution helping to effortlessly avoid CAPTCHAs and IP bans.
Other popular use cases
Need global, trustworthy coverage to manage multiple social media profiles or scrape the web? Look no further – our premium proxies work for all targets and use cases.
Web scraping
Gather public web data to generate valuable insights and scale your business. Learn more
Price aggregation
Track and monitor prices to keep up with the ever-changing markets. Learn more
Multi-accounting
Create and manage multiple eCommerce accounts with ease. Learn more
Configurations & integrations
Learn how to set up solutions by exploring our integration guides. Effortlessly set up and plug in our proxies with the most popular web scrapers, bots, tools, libraries, and other third-party software.
Configurations
Integrations
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Frequently asked questions
What is data scraping used for?
Data scraping, also known as web scraping, is the process of extracting data from websites. The gathered data is collected and formatted and can be used for various purposes. The most popular use cases include market research, content aggregation, sentiment analysis, data mining, and AI model training.
How to collect data for LLMs?
To collect data for large language models, you’ll need to find sources from which you want the model to learn. These can be public sources such as books, websites, prepared datasets, or social media platforms, depending on what you’re trying to teach. You can then choose a method to collect this data, such as APIs or web scraping tools. The final step includes cleaning and storing the data so that it’s easy to acquire and read.
What type of data is used to train generative AI models?
Generative AI is trained through various types of data. The kind of data depends on what the AI model is expected to do – a chatbot, for instance, will learn from text-based data such as books, articles, or social media. An image-generating model will learn from large amounts of images such as photos, artworks, or diagrams.
How is data for AI gathered?
There are several ways to get data for AI. For example, there are many public repositories available that offer large datasets that are immediately ready for use. Such data is easy to acquire but can be limited in knowledge for specific areas. If you want the AI model to learn from more concrete sources, APIs and web scraping tools can help narrow down the type of information it learns from.
Where to get training data for machine learning?
You can get training data from public repositories, government databases, APIs, or scraping the web.