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.
How’s Data Made Here?
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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
HIPAA
300
K+
Community of experts
400
K+
Total hours worked by our experts
10
%
Of talent are PhDs