Most AI projects fail not because of the model — but because of what feeds it. Organizations sit on terabytes of tribal knowledge hidden in tickets, chats, and project pages. We built The Knowledge Refinery to fix that.
The Problem: 80% of Knowledge Never Makes It Into Systems
Decisions, fixes, and expertise live inside tools like Jira, Confluence, Teams, and Slack — not your databases. Everyday interactions capture context, reasoning, and judgment that traditional “knowledge management” never touches.
That’s the undocumented 80% — the intelligence your AI never learns from.
Built for industrial companies where operational knowledge is competitive advantage—manufacturing, machinery, automation, and process industries.
The Solution: Refining, Not Replacing
The Knowledge Refinery transforms that unstructured, operational knowledge into a dynamic, living base of intelligence.
Instead of endless “knowledge collection” projects, we:
The result: a self-updating knowledge layer that actually mirrors how your teams work — not how a consultant thinks they should.
Why Jira and Confluence First
They’re the most used, most hated, and most important systems in your stack. Every ticket, comment, or documentation update is a trace of human reasoning — your organization’s collective intelligence in motion.
Starting here:
Instead of collecting obsolete data for 12 months, we start generating value in 12 days.
Beyond Jira: The Expansion Path
Once the Refinery has proven value in JIRA/Confluence, it systematically extends to new knowledge domains — through API-level integration, not new deployment projects.
Each expansion builds on proven methodology, not new experiments. The Jira pilot validates the approach; the roadmap scales the value.
How It Works
They’re the most used, most hated, and most important systems in your stack. Every ticket, comment, or documentation update is a trace of human reasoning — your organization’s collective intelligence in motion.
Starting here:
Built on an API-first, agentic architecture for deterministic task orchestration and traceable outcomes.
What Makes This Different
Not Another Chatbot or Productivity Tool
We solve the meta-problem: systematically capturing the 80% of knowledge that never gets documented.
The Result: A Dynamic Knowledge Base That Learns With You
Not a static wiki. Not a fragile LLM integration. But a continuously learning knowledge layer — resilient, explainable, and enterprise-ready.
Traditional Knowledge Management vs. The Knowledge Refinery
Traditional Approach:
- ✗ 12-month implementation projects
- ✗ Outdated before launch
- ✗ Nobody uses it
- ✗ Isolated from daily workflows
The Knowledge Refinery:
- ✓ Value in weeks, not months
- ✓ Self-updating through usage
- ✓ Built where teams already work
- ✓ Grows with your operations
From Chaos to Clarity
Transform the 80% of knowledge your systems ignore into the foundation for real AI success.
Phase 1: Discovery – Map your knowledge landscape
Phase 2: Automation – Turn insights into working intelligence
Phase 3: Integration – Embed automation in your daily workflow
Book Your Friction Audit – Begin with discovery, scale with automation.