Turn approved knowledge into trusted answers
Knowledge-Based AI Grounded in Your Sources
Give people a conversational way to use the information you have reviewed, with clear scope and uncertainty rules.
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What it is
A focused agent, not an open-ended promise
Knowledge-based AI retrieves relevant material from a maintained source set and uses it as context for an answer. Qlynk adds agent purpose, boundaries, publishing, and review around that process.
Benefits
Designed around trustworthy usefulness
Ground answers in maintained material
Use approved facts, FAQs, notes, links, and documents as the working knowledge.
Reduce unsupported improvisation
Tell the agent what belongs in scope and how to respond when the answer is absent.
Improve from real gaps
Review conversations and unanswered topics to decide what knowledge deserves to be added.
How it works
From source material to a shareable agent
- 01
Curate
Choose the smallest source set that fully supports the agent’s job.
- 02
Structure
Turn critical details into clear facts and FAQs instead of relying only on long documents.
- 03
Maintain
Test answers and update the source when policy, availability, or instructions change.
Illustrative response. The published answer depends on the knowledge and rules the owner approves.
Frequently asked questions
What to know before you build
Does knowledge grounding eliminate hallucinations?
No system can promise that. Good sources, narrow scope, explicit uncertainty behavior, testing, and human escalation reduce the risk.
Is this the same as model retraining?
No. You update the knowledge supplied to the agent; you do not need to retrain a foundation model.
What should stay out of the knowledge base?
Keep out passwords, access codes, private customer data, confidential records, and material you are not permitted to use.
Related solutions
AI Knowledge Platform for Shareable Answers
Organize approved information, define how an agent should use it, and make it available through a public page or embedded chat.
AI Documentation Assistant for Faster Answers
Help readers find and understand maintained documentation while preserving the source as the authority.
AI hallucinations and approved knowledge
Understand why language models produce unsupported answers and how sources, scope, testing, uncertainty, and handoff reduce risk.
Turn your approved knowledge into a trusted AI agent.
Start with one job, add what you know, define the limits, and share the result.
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