knowledge-base

Manual knowledge editing lets a human correct, add, or remove a knowledge base entry by hand so the bot answers right, with no autolearning involved.

Knowledge refresh with change detection keeps your support bot current. Re-scrape only what moved, re-upload changed files, edit by hand. No autolearning.

A knowledge graph for AI support links your documents, pages, and notes into connected facts, so the bot answers from how your content relates.

Document upload for your knowledge base lets your chatbot answer from your PDF, DOCX, TXT, and MD files. See how files become grounded answers, no autolearning.

Train your chatbot from your website with a full-domain crawl, a sitemap, or a single URL. See how grounded answers get built and kept fresh, no autolearning.

Test AI support responses in 5 steps: build a corpus, define a rubric, run the tests, triage failures, decide on launch. The QA framework most teams skip.

AI support that learns from feedback turns live conversations into knowledge base improvements. See the 3 mechanisms and what makes the loop compound.

A no-hallucination AI support agent grounds every answer in your documentation. The architecture, the guardrails, and the liability case for grounded support.

An AI chatbot from your docs answers visitor questions using your help center, PDFs, and FAQs. See the architecture, the sources that work, and the refresh cycle.

Train a support chatbot in 5 steps: gather sources, clean content, load into the KB, test with real questions, iterate from live conversations.