Data for Tuning RAG

Retrieval augmented generation (RAG) connects your large language model (LLM) to a curated, dynamic database. By combining your data and world knowledge with LLM language skills, grounded generation is more accurate, up-to-date, and relevant to your specific needs.
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How’s Data Made Here?

Document Collection
Use our expert-sourced documents or your own for domain-specific needs.
Question generation by experts
Our experts create realistic questions aligned with real-world business needs.
Expert answers with citations
Long-form answers by domain experts, customizable with citations and docs per data point.
High-touch Quality Control
Multi-layer validation ensures clarity, relevance, and accuracy with peer reviews, and technical checks,

Unique Dataset Features

Reduces Hallucinations
We use hierarchical document-structured chunking to minimize  AI errors, delivering precise and well-annotated context.
Expert Curated
Meticulously curated by top  1% industry experts, including Ph D holders, our data ensures unmatched accuracy and reliability.
Domain Specific Dataset
A  rich dataset tailored to cover all relevant information within a specific domain

"Deccan AI’s high-quality human data and RAG capabilities have transformed our LLMs — making them faster, more accurate, and perfectly aligned with real-time insights. A true partner in driving AI innovation."

-  Senior AI Director, $10B  SF Bay Area AI Company

The Deccan AI Advantage

Multi-touch Collaboration
Up to 3 annotators per data sample ensure high accuracy and thoroughness in annotations.
Real-time Feedback
Immediate feedback ensures smooth annotation processes and enhanced quality control.
Anti-Cheating Indicators
The platform ensures data integrity by preventing the use of LLMs during annotation

Enterprise Certifications

ISO 27001
SOC2
GDPR
Coming soon
HIPAA
Coming soon

300

K+

Community of experts

400

K+

Total hours worked by our experts

10

%

Of talent are PhDs

Experience the Modern Way to Outsource

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