Compliance-safe AI answers
PII masking, access controls, and audit trails built in.
Legal blocked your AI rollout: customer PII could leak into prompts, there is no audit trail of what the AI said, and access control is all-or-nothing. Shadow AI happens anyway — employees paste sensitive content into public chatbots.
Kelu is built for governed deployment: PII masking before content reaches the LLM, document-level visibility (public vs. restricted), per-knowledge-base chat permissions, OIDC/SAML SSO, and workspace audit logs. Full conversation traces mean every answer is reviewable — an approved tool beats a shadow one.
How it works
- 1
Opt-in PII masking scrubs sensitive data before content reaches the LLM.
- 2
Document visibility (public vs. restricted) and per-knowledge-base permissions control access.
- 3
OIDC and SAML SSO gate who can use internal surfaces at all.
- 4
Workspace audit logs and full conversation traces make every answer reviewable.
What you get
- Deploy AI your legal and security teams can actually approve.
- Keep PII out of prompts with opt-in masking of indexed content and widget, API and Ask questions.
- Review any answer after the fact via traces and conversation history.
- Replace shadow AI usage with a governed, auditable alternative.
Features that make it work
Got questions?
Frequently asked questions
How does PII masking work?
When you turn it on for a knowledge base, personal data is masked in indexed content and in widget, API and Ask questions before they reach the LLM. Questions from bots, the form deflector, helpdesk automation, MCP and search are not masked.
Is there an audit trail?
Yes — workspace audit logs record administrative activity, and conversations record what was asked, what was answered and the citations shown, and traces record each answer's latency and tokens, making the system reviewable end to end.
How granular is access control?
Three layers: SSO (OIDC/SAML) controls who signs in, per-knowledge-base chat permissions control which knowledge each member can query, and document-level visibility controls which docs are retrievable on which surfaces.
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.
Related use cases
Internal helpdesk for IT and HR
"How do I get a laptop repaired?" answered without a ticket.
Separate knowledge across products and versions
Source groups keep Product A answers out of Product B chats.
Stop losing knowledge when people leave
Institutional memory that survives offboarding.
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