Solutions / Library / AI & Machine Learning / Use case
RAG (Retrieval Augmented Generation)
Build AI applications that query knowledge bases to provide accurate, contextual responses.
The problem
Where teams get stuck
- 01
LLM hallucinations and inaccurate responses
- 02
Difficulty connecting AI to company knowledge
- 03
Manual knowledge base maintenance
- 04
Lack of source attribution in AI responses
How Tray.ai solves it
The solution
Tray.ai connects vector databases, knowledge bases, and LLMs to build RAG pipelines that ground AI responses in verified data.
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