DataMate builds a one-stop data governance hub for large models, covering the entire process of data collection, management, cleaning, annotation, synthesis, and format conversion. It comprehensively addresses data pain points in large model deployment, from private knowledge base construction to training data preprocessing, prompt optimization to response data feedback.
As an enterprise-level solution, DataMate supports concurrent processing of tens of millions of data points and is compatible with mainstream large model formats, enabling rapid transformation of data value into model competitiveness.
End-to-end data governance
Automatically handle noisy data, standardize formats, and structure knowledge, enabling large models to feed accurate information. Compatible with 10+ data formats, seamlessly integrating with model training and inference scenarios!
Open-source and extensible
Support custom data processing plugin development to adapt to enterprise private data scenarios. The ecosystem is rich, high-performance, and low-latency, easily meeting TB-level data processing needs!
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Large model deployment, data first
Intelligent data augmentation
Based on the capabilities of large models, automatically generate high-quality training samples and expand knowledge bases. Reduce manual annotation costs and improve model training efficiency by 300%!
Enterprise-level security assurance
Support private deployment, with data never uploaded to the cloud. Complies with third-level security standards of the Information Technology Security Management System (ISO 27001). Fine-grained permission control, ensuring the security of core data assets!
Lightweight and quick to get started
Visual configuration interface, no complex coding required, 10 minutes to set up the data processing flow. Provides complete API interfaces, easily integrating with existing business systems!
Let every piece of data be the core competitiveness of large models