AI That Thinks With Your Data
Boxed AI uses Retrieval-Augmented Generation (RAG) to pull directly from your knowledge base before responding — so answers are always accurate and contextual.
In traditional AI models, answers are generated based on general knowledge — sometimes resulting in hallucinations or irrelevant responses. With Boxed AI’s RAG architecture, the system first retrieves information from your own documents, then uses that data to construct precise, trustworthy answers. Whether your team is referencing training manuals, technical specs, compliance reports, or product sheets — Boxed AI always responds with content pulled from your own knowledge ecosystem.
Key Benefits:
Cited, Verifiable Answers:
- Responses include references to the original documents.
Reduced Risk of Hallucination:
- AI doesn’t fabricate answers — it generates them from real data.
Trustworthy AI for Regulated Industries:
- Especially valuable for manufacturing, energy, healthcare, and more.
Real-World Use Case:
A plant manager asks:
What are the pressure safety limits for Pump Unit 4?
- Boxed AI finds the relevant section in the pump manual and generates a summarized response with direct citations.
How It Works Section:
Retrieve Phase:
- The system scans your indexed files for content relevant to the user query.
Augmentation:
- It feeds that real-world content into the prompt.
Generation:
- The AI creates a human-readable response grounded in the retrieved data.
Citation:
- The response includes document references for transparency.
Trust & Transparency:
Boxed AI allows users to verify each response:
- View source files and pages
- Understand how the answer was formed
- Build confidence in high-stakes environments
