In today’s fast-changing world of artificial intelligence (AI), data plays a more important role than ever before. AI models are becoming smarter, more powerful, and more complex. Among them, multimodal large language models (MM-LLMs) and dynamic prediction models are leading the way. These models require large amounts of high-quality data — from different formats and from all over the world.

But collecting the right data isn’t easy. Websites often block repeated or automated access. Some content is region-specific. Others are hard to access due to speed, privacy, or security issues. This is where smart proxy services come in — especially residential proxies.

In this blog, we’ll explore how residential proxies help collect data for powerful AI models. We’ll look at how they support image and audio downloads, give fast access to online services, and provide worldwide reach for collecting real-time and regional data. Let’s get started!

1. Introduction: The Role of Data in Next-Gen AI Models

AI is getting better at understanding human language, seeing images, listening to sounds, and predicting future events. This is all possible thanks to new kinds of AI models:

Multimodal Large Language Models (MM-LLMs): These models understand not just text, but also images, audio, and sometimes even video. They are used in tools like image captioning, voice assistants, and visual question-answering.

Dynamic Prediction Models: These models are designed to predict changes in real-world data — like product prices, user preferences, or stock market movements.

Both types of models need huge amounts of real-world data. And not just any data — it must be fresh, accurate, and diverse.

To get this kind of data, many businesses and researchers use web scraping. This means collecting data from websites in an automated way. However, scraping has challenges. Many websites don’t allow scraping or block it if they detect it. Others serve different content depending on the location of the user.

Proxies, especially residential proxies, help solve these problems. They allow users to collect large amounts of data safely, quickly, and from different places around the world.

2. Fast Multimodal Data Collection with Residential Proxies

What Are Residential Proxies?

A residential proxy is an IP address that comes from a real device, like a home computer or mobile phone. This makes it look like the data request is coming from a real person, not from a bot or a scraper.

Unlike data center proxies (which often get blocked), residential proxies are trusted by websites. They are less likely to trigger security systems.

Why Are They Important for Multimodal Data?

Multimodal models need a lot of data from many formats — images, videos, and audio files, in addition to text.

Let’s say you’re building a model that can describe images. You’ll need thousands or millions of labeled images. Downloading these from the internet can take time and bandwidth — especially if you’re collecting from multiple websites.

Residential proxies help in two ways:

Speed – You can use many proxies at once (this is called rotating proxies) to download data faster.

Stability – Since these IPs are from real users, websites allow more access and fewer blocks.

Real Examples:

Computer Vision: Gathering photos of everyday objects, animals, or faces for training.

Speech Recognition: Downloading voice recordings or podcasts to teach machines to understand spoken words.

Video Understanding: Scraping short video clips from platforms that show user actions, sports events, or product demos.

3. Low-Latency Access for Continuous Multimodal Services

Some AI models don’t just need data once. They need constant access to real-time data. This is common for services like:

Voice assistants that respond instantly to user questions.

AI chatbots that answer both text and image-based questions.

Live captioning tools that generate subtitles in real time.

These tools must access online services without delay. Low-latency proxies are key here. They send and receive information very fast, making the experience smooth and quick.

With low-latency residential proxies, developers can:

Monitor live content without interruption.

Test apps that work in different countries and languages.

Access video streams, live chat tools, and image APIs in real-time.

Without low-latency access, multimodal AI systems may lag or miss updates. This is why proxies with fast response times are essential.

4. Domain-Specific NLP: Legal, Healthcare, and Finance

Natural Language Processing (NLP) is the part of AI that deals with understanding and generating text. In general, it’s easy to find everyday language online. But what if you want to train a model that understands complex fields like law, medicine, or finance?

In these fields, the language is very specific and technical. You need data from real legal documents, medical studies, or financial reports.

However, these websites often:

Require user login or payment.

Are limited to certain regions (due to law or licensing).

Block multiple visits from the same IP.

This is where residential proxies become useful again. They allow:

Anonymity – so you can access the data without being blocked.

Geolocation control – so you can access data that’s only available in specific countries.

Automation – scrape hundreds of documents per hour without being detected.

Use Cases:

Healthcare: Collecting electronic health records (EHRs) and research papers.

Legal: Downloading court decisions, legal articles, and policy papers.

Finance: Scraping stock news, company earnings, and investment analyses.

All this data helps build specialized NLP models that can summarize, translate, or analyze documents in expert domains.

5. Data Collection for Dynamic Prediction Models

Prediction models use current data to guess what might happen in the future. Some examples include:

Predicting when product prices will drop.

Forecasting which items people will buy during holidays.

Alerting when stock levels are low or a product is trending.

For this, models need live, real-time, and changing data.

Let’s say you want to know how the price of a smartphone changes on Amazon. If you check once a day, you might miss small price changes. But if you check every hour, you’ll get better insights.

Residential proxies help you scrape frequently, without getting blocked. This is especially helpful for platforms like:

Amazon

Shopee

Google Shopping

eBay

Walmart

These platforms use strong anti-scraping systems. But with rotating proxies, you can visit them again and again — like a real user from different places.

6. Global IP Coverage: Training Models for Regional and Multi-Language Use

AI models shouldn’t be biased. They should work well across countries, languages, and cultures. To do this, you need data from many regions — and many languages.

Proxy providers often have IPs in 190+ countries. This means you can scrape data from:

Local news websites in Africa.

Shopping platforms in Southeast Asia.

Legal databases in Europe.

Social media content in South America.

This kind of data helps build AI that understands:

Different currencies, time zones, and formats.

Local slang, cultural terms, and regional behaviors.

User preferences in different regions.

It also helps with geo-targeted alert systems — like when prices rise in a specific country, or when laws change in a certain region.

Without global IPs, you would miss this local flavor — and your AI model wouldn’t perform as well worldwide.

7. Conclusion: Building Smarter AI Starts with Smarter Data Collection

In the world of AI, your model is only as good as the data you feed it. Whether you’re building a chatbot, a pricing engine, or a language model, you need:

Fast, large-scale access to the internet.

Real, region-specific user data.

The ability to collect data from multiple formats and platforms.

Residential proxies give you the power to collect this data easily, safely, and at scale. They offer:

High-speed scraping for multimedia files.

Low-latency access for live and real-time data.

Wide geographic coverage to get global data.

With proxies, you can train models that are not only smarter — but also more accurate, fair, and up-to-date.

So the next time you think about building an AI system, remember: smart data collection is step one. And residential proxies are your best tool to get there.