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Training Data for AI Models: A Technical Guide

Acquiring high-quality, large-scale training data is a critical challenge for AI engineers. This guide provides a comprehensive technical overview of Bright Data’s infrastructure for building and managing data acquisition pipelines, designed to help you make informed decisions and get started quickly.

Technical Quick Reference

Feature	Specification
Data Formats	`JSON`, `NDJSON`, `CSV`, `XLSX`, and `Parquet`. Specify your desired format in the API request.
Authentication	All API requests are authenticated using a bearer token. Include your API key in the `Authorization` header.
Data Freshness	Archive: Historical. Pre-collected: Updated daily, weekly, or monthly. Custom: On-demand, near real-time.
Compliance	GDPR, CCPA, and SOC2 compliant. We adhere to a strict ethical framework for all data collection. See our Trust Center.
Developer Tools	We provide SDKs for Python and Javascript.
Free Trial	Sign up and receive a credit to test Bright Data. Download data samples for any dataset before purchasing.

Data Acquisition Strategies

Your strategy for data acquisition depends on your model’s needs. Choose the method that best fits your use case, from foundational training to specialized, real-time data collection.

Web Archive
Pre-collected Datasets
Custom Collection
Video & Media

Best for: Foundational, large-scale model training.The Web Archive provides access to a petabyte-scale repository of historical web data, making it the ideal source for training large language and diffusion models that require a comprehensive understanding of the digital world.

Use Case: Pre-training LLMs, historical analysis, building base models.
Next Step: Contact our data experts for access and pricing.
Learn More: Web Archive Documentation

Best for: Fresh, on-demand data from specific sources.Initiate programmatic data collection jobs to get real-time, structured data from any public URL. This gives you complete control over the freshness and specificity of your training data.

Use Case: Real-time applications, tracking dynamic data, custom knowledge bases.
Pricing: Based on the complexity and scale of the request.
Next Step: Contact us for a custom quote.
Learn More: Custom Dataset API Documentation

API Example:

curl "https://api.brightdata.com/datasets/initiate?dataset_id=YOUR_DATASET_ID&type=url_collection&view=YOUR_VIEW_ID" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '[{"url":"https://example.com"}]'

Best for: Training multimodal models at scale.Overcome the limitations of tools like yt-dlp by using our resilient infrastructure. The Web Unlocker API handles rate limits, geo-restrictions, and bot detection to ensure a reliable video data pipeline.

Use Case: Training video, audio, and image models.
KYC Required: Access requires a Know Your Customer process to ensure ethical and compliant data sourcing due to the sensitive nature of media content.
Next Step: Book a meeting with our data experts to begin the approval process.
API Reference: Media Extraction API, download video, audio, captions, thumbnails, and storyboards from YouTube, Vimeo, TikTok, and Bilibili.

How data is delivered

Once your data is collected, it can be delivered to a variety of destinations to seamlessly integrate with your existing cloud infrastructure. Supported Delivery Options:

Amazon S3
Google Cloud Storage
Microsoft Azure Storage
Webhook
SFTP/FTP
Snowflake
API Download

For detailed instructions on setting up your preferred delivery method, please see our Delivery Options documentation.

Documentation Index

Building an AI startup?

​Training Data for AI Models: A Technical Guide

​Technical Quick Reference

​Data Acquisition Strategies

​How data is delivered

Training Data for AI Models: A Technical Guide

Technical Quick Reference

Data Acquisition Strategies

How data is delivered