RAG Integration:
Knowledge fused
with intelligence.
Ground every AI response in your own trusted data with our high-performance RAG pipeline. Verifiable answers, always.
The RAG Formula
Any LLM
Multi-model
Grounding
100%
Sources Linked
12/12
How RAG works
Four steps to accurate, grounded AI responses
Retrieve
Semantic search identifies relevant passages from your entire knowledge base.
Rank
Re-ranking models filter noise, keeping only the highest-quality context.
Augment
Context is assembled and optimised for the model's context window.
Generate
LLM synthesises a grounded answer with inline citations to sources.
See it in action
Watch the RAG pipeline transform a question into a grounded answer
"What were our top revenue drivers in Q3?"
Natural language question parsed and embedded
Trust in every response
RAG grounds every answer in your actual documents, making responses verifiable and traceable.
Grounded by Default
Every response is anchored to your source documents. If the answer isn't in your data, the system tells you. Verifiable responses you can trust.
Inline Citations
Every claim is linked back to source passages so users can verify and trust responses. Click any citation to view the original context.
Streaming Responses
Real-time token-by-token generation provides immediate feedback. Users see answers form as they're generated, with no waiting for complete responses.
Your model, your choice
RAG works with any LLM. Switch models without changing your application code.
GPT-5
OpenAIClaude 4.5
AnthropicDeepSeek V3
DeepSeekGemini 3
GoogleQwen 3
AlibabaMistral Large
MistralBuilt for your workflow
Enterprise Knowledge
Employees waste hours searching across multiple systems. RAG unifies all knowledge into one AI-powered interface with grounded, accurate responses.
Single source of truth with role-based access, citation tracking, and SSO integration.
Research & Analysis
Analysts spend more time finding documents than analysing them. RAG surfaces relevant insights across thousands of documents instantly.
Highlighted excerpts, cross-reference discovery, and semantic clustering.
Customer Support
Support teams struggle to find answers quickly. RAG provides instant access to product docs, FAQs, and past resolutions.
Past resolution lookup, knowledge gap detection, and agent assist capabilities.
Powered by the platform
RAG brings together search, citations, and parsing into one unified pipeline
Ready to fuse your data with AI?
See how RAG Integration can power accurate, grounded AI responses for your applications.