Knowledge Infrastructure

Your company's knowledge, one question away.

Turn scattered documentation into a single knowledge layer that your team — and your systems — can query in plain language.

Talk to us →See how it works
Knowdex
What’s our policy on refunds for annual plans?
Annual plans cancelled mid-term are eligible for a prorated refund calculated from the next billing cycle. If the customer received an annual discount, the refund is adjusted at the monthly rate for months used. Refunds process within 5–7 business days.
Billing & Refund Policy — Notion, updated 12 days ago
Have we made exceptions before?
Two recent cases: a full refund was approved in March after a 3-day outage (VP of CS), and a partial exception in January for an enterprise contract renegotiation.
#support-escalations — Slack, Mar 14 & Jan 22

The information exists. Finding it is the problem.

Your company's knowledge is spread across Notion, Google Drive, Confluence, Slack, SharePoint, shared folders, and — most critically — people's heads.

The result is predictable. People search three tools and give up. New hires ask the same questions the last batch did. Senior team members become human knowledge bases, interrupted ten times a day. Support agents put customers on hold to dig through wikis that haven't been updated in months.

The knowledge exists. It's just not accessible.

🔍

Search that doesn't work

Internal search returns too many results or the wrong ones. People give up and ask a colleague instead.

💬

Same questions, over and over

Senior team members spend hours answering repeated questions. The answers exist somewhere, but nobody can find them.

📁

Scattered across tools

Policies in Drive. Processes in Confluence. Product specs in Notion. Decisions in Slack. No single place to look.

Stale documentation

Wiki pages from two years ago sit next to current docs. People stop trusting the knowledge base entirely.

🤖

AI tools hallucinate

Generic AI assistants make up answers without your company's context. Confidently wrong is worse than nothing.

🔗

No API for your knowledge

When you build automations or AI agents, they can't access internal knowledge programmatically.

How It Works

Connect. Index. Query.

1

Connect your sources

Point Knowdex at the tools where your documentation lives. No migration needed — your docs stay where they are. We sync and watch for changes.

OAuth integration for cloud tools. File upload for PDFs, docs, and markdown. Incremental sync keeps the index current.
2

Automatic indexing

Documents are parsed, chunked, and embedded into a vector index with metadata preservation. The system understands document structure and hierarchy — not just keywords.

Chunking with overlap. Metadata tagging by source, date, section. Re-indexes on document changes automatically.
3

Query in plain language

Ask questions through the chat interface, embed a widget in your internal tools, or call the API from your own applications. Every answer cites its source so you can verify and go deeper.

RAG pipeline with retrieval, re-ranking, and grounded generation. Answers include source links and confidence signals.
Who Uses It

One knowledge layer, multiple surfaces.

The same indexed knowledge is accessible to different people and systems in different ways.

Answers in real time, on a live call.

Support agents query Knowdex while they’re on a call or handling a ticket. No more putting customers on hold to search through three different systems.

Look up return policies, billing rules, and product details mid-conversation
Surface troubleshooting steps from past resolutions
Reduce average handle time without sacrificing answer quality
New agents ramp faster with instant access to institutional knowledge
Example query — support agent
Customer says their integration stopped syncing after upgrading to v3.2. What changed?
In v3.2, the OAuth token refresh flow was updated. Integrations configured before the upgrade may need to re-authenticate. The customer should disconnect and reconnect from Settings → Integrations. No data loss will occur.
Migration Guide v3.2 — Confluence, updated 3 days ago

Connects to the tools your team already uses

📝Notion
💾Google Drive
🌊Confluence
📧SharePoint
💬Slack
📄PDF / Docs
📓Markdown
🔗REST API
Example Deployment

B2B SaaS company — 65 employees, 12-person support team.

A growing software company whose support team was drowning in repeat questions while product docs, internal guides, and troubleshooting notes lived across four different tools.

Before

Support agents spent an average of 6 minutes per ticket searching for answers — checking Notion for product docs, Google Drive for internal guides, Confluence for engineering notes, and Slack for past edge cases.

New agents took 3–4 weeks to ramp because there was no single place to learn the product. Tribal knowledge lived with senior agents who were constantly interrupted.

After

The support team queries Knowdex directly from their helpdesk. New agents onboard in 10 days instead of four weeks. And the company's customer-facing chatbot pulls from the same knowledge base, resolving 40% of common questions before they become tickets.

Time searching per ticket~6 min
After deployment~1.5 min
New agent ramp-up3–4 weeks
After deployment~10 days
Tickets deflected by chatbot0%
After deployment~40%
Knowdex \u2014 Support workspace
Customer can’t export reports since the last update. Known issue?
Yes — there’s a known bug in v4.1.2 where report exports fail for users with custom date range filters. Engineering deployed a hotfix yesterday (v4.1.3). The customer should clear their browser cache and refresh. If the issue persists, they may need to recreate the saved report.
#eng-incidents — Slack, yesterday & Release Notes v4.1.3 — Notion
Is there a workaround if the hotfix doesn’t help?
The support team has been using a manual export path: navigate to Analytics → Raw Data → apply filters there and export as CSV. This bypasses the report builder entirely. Three agents confirmed this works in the #support-workarounds channel.
#support-workarounds — Slack, 2 days ago
Under the Hood

Retrieval-augmented generation, built for your docs.

Sources feed into a central index. Queries hit the index through multiple surfaces. Every answer is grounded and cited.

Data Sources
📝Notion
💾Google Drive
🌊Confluence
📧SharePoint
💬Slack
📄PDF / File Upload
sync & parse
Knowdex Engine
Document Processingchunk + embed + metadata
Vector Indexsimilarity search + re-ranking
Generation LayerLLM + source grounding
grounded answers
Query Surfaces
💬Chat Interface
🔗REST API
🧩Embeddable Widget
🤖AI Agent Integration
🔔Slack Bot

See what your team's knowledge looks like when it's actually accessible.

We'll map your documentation landscape, identify the highest-impact use case, and show you what a deployment would look like.

Start a conversation →