Data Engine

When high-quality, structured data for AI matters most

CloudFactory’s Data Engine helps organizations unlock the full potential of their AI by delivering the highest quality data through expert collection, curation, and annotation—fueling smarter, faster model performance.

Data collection

Data curation

Data annotation

AI trust gap

“It's critical for AI to be trained on data that truly reflects real-world conditions”*

70%

of AI projects fail to meet their goals due to issues with data quality and integration

(McKinsey & Company, 2023)

60%

or more of firms are trying to find data. It’s a huge productivity loss.

(IDC, 2024)

Poor Data Quality – Incomplete, noisy, or biased data leads to unreliable, error-prone models.
Fragmented Datasets – Disconnected systems make it hard to build clean, unified training data.
Lack of Data Diversity – Homogeneous data limits real-world model performance and generalization.
Manual Data Prep – Teams waste time cleaning and labeling instead of developing models.
Untapped Unstructured Data – Text, images, and audio go unused due to lack of tools or expertise.

*Gartner, 2024

Common AI needs

What we’re hearing from
clients

"I need high-quality, AI-ready data to train LLMs, CV, or behavioral models with minimal preprocessing and maximum performance."

"I need to clean and structure disorganized data lakes to create refined datasets for labeling, testing, or fine-tuning."

"I need to increase dataset diversity and reduce bias to improve model generalization, fairness, and trust."

"I need accurate, scalable annotation to label complex, multimodal datasets efficiently and reliably."

"I need to accelerate data prep workflows to get models into production faster and reduce manual overhead."

Meeting you where you are

An enterprise-ready AI platform service

Designed to power AI with high-quality, human-labeled data—curated, structured, and optimized for precision, diversity, and real-world reliability.

High-performance

Clean, complete and diverse data support

Data collection

Ai-ready datasets

Dataset construction

From structured or unstructured data

Dataset diversity

Augmentation, metadata enrichment

AI assisted pre-labeling

Automated, AI-assisted classification

Accurate annotation

Multimodal support

Data Engine