Find and fix weak answers
Feedback and the gap report show which answers to fix.
You deployed an AI assistant, but you have no idea if its answers are actually good — until a customer screenshots a bad one. Spot-checking transcripts does not scale, and quality can silently regress when content or models change.
Kelu collects thumbs up or down on every answer and logs the questions it could not answer as knowledge gaps. Conversations keep the citations behind each answer, and traces record it, so you can find the content problem, fix it, and ask again to check.
How it works
- 1
Users rate answers with message-level feedback (thumbs up/down).
- 2
Questions Kelu could not answer are logged as knowledge gaps.
- 3
Weak answers are inspected via the conversation, its citations, and the trace.
- 4
Fix the content, then ask the question again to check the answer.
What you get
- See which answers users rated down.
- Find the questions your docs don't cover yet.
- Go from a bad answer to the source it was drawn from.
- Close the loop: fix, re-sync, check.
Features that make it work
Got questions?
Frequently asked questions
How do I find weak answers?
Users rate each answer with thumbs up or down, and questions Kelu could not answer are logged as knowledge gaps. Kelu does not show automated eval scores.
Can I see why a specific answer was bad?
Yes. Conversations keep the question, the answer, and its citations, and traces record each answer — so you can tell whether the problem was missing content or the wrong source, and fix the right layer.
What typically causes low-quality answers?
Most commonly missing or outdated content (fix via doc proposals and syncs) or retrieval scoping issues (fix via source groups and configuration). Feedback, gaps, and traces tell you which one you have.
How long does setup take?
Most teams are live the same day. You connect a source — a docs URL, GitHub repo, Notion workspace, or a file upload — and Kelu crawls, normalizes, chunks, and embeds the content automatically. The website widget is a single script tag, and the Slack bot installs in a few clicks. There is no model to fine-tune and no infrastructure to run.
Are answers backed by citations?
Yes. Every answer from your docs includes a structured citations list with the URL, title, and excerpt of each source used, and the answer text cites sources inline. Users can click through to verify any claim against the original document — which is what makes the answers trustworthy enough for support, sales, and internal use.
Is my content used to train AI models?
No. Your indexed content, embeddings, and conversations are isolated to your workspace and are only used to answer your own questions. Content is never shared across customers, and data is encrypted at rest and in transit. Enterprise plans add OIDC/SAML SSO, a widget without Kelu branding, and a custom SLA.
Which knowledge sources can I connect?
24 source types: websites, GitHub (docs files, source code, issues, pull requests, discussions), Notion, Confluence, Google Drive, OneDrive, Zendesk (Help Center and solved tickets), Jira, Jira Service Management, Linear, Salesforce Knowledge articles, Salesforce Cases, Discourse, Stack Overflow for Teams, YouTube, OpenAPI specs, S3, curated Q&A, and direct file uploads (PDF, DOCX, XLSX, CSV, Markdown, TXT, HTML). Sources sync on a schedule, and GitHub sources can re-index automatically via webhook on every push.
What happens when the AI is not confident in an answer?
Answers are grounded in your sources. When they do not cover a question, Kelu returns a transparent, configurable fallback — typically pointing users to your support channel — instead of guessing. Those unanswered questions are logged in knowledge gap analytics so you can close the gap in your docs.
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Ready to find and fix weak answers?
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