Training data for generative models
Generative AI Data
Image-text pairs, multimodal datasets, and synthetic data pipelines for diffusion and vision-language models.
Overview
What is Generative AI Data?
Generative AI models require vast quantities of high-quality paired data. We build image-text pairs, multimodal corpora, and synthetic data pipelines with safety filtering and quality scoring at every stage.
Why it matters: The output quality of a diffusion or vision-language model is only as good as its caption-image alignment and safety filtering. Weak captions and unfiltered data produce weak, unsafe models.
Image-Text Pairs
Dense, contextual captioning for diffusion model training
Style Coverage
Balanced datasets across artistic styles and visual domains
Safety Filtering
NSFW, copyright, and quality screening on every asset
Quality Scoring
Human-evaluated alignment and image-quality scores
Workflow
How We Do It
01
Dataset Design
Define modalities, distributions, style coverage, and safety requirements.
02
Data Collection
Gather raw images, text, audio, or video from licensed and approved sources at scale.
03
Caption & Annotation
Expert creators write detailed, contextual captions with attribute and style metadata.
04
Safety Filtering
Multi-layer NSFW, copyright, and quality filtering removes unsuitable content.
05
Delivery
Model-ready datasets with metadata, quality scores, and full documentation.
Case Study
Generative AI Startup
Generative AI Startup
Build a 10M image-text pair dataset with safety filtering
Solution
Licensed data pipeline with dense captioning and multi-layer content filtering
Results
10M
Image-text pairs
99.5%
Filter precision
14 wks
Delivery
Ready to Get Started with Generative AI Data?
Tell us about your project and we'll scope a pilot within 48 hours.