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
Proven in Production
Proven in Industrial Operations
Measurable outcomes from real deployments in manufacturing, automation, and software environments.
15k Jira Issues Exposed Hidden Product Gaps
Structured product intelligence for clearer UX priorities, & faster onboarding
Onboarding Cut from 24 → 6 Months
AI-Driven Knowledge Refinement for a Software Provider
68% Auto-Categorization in 8 Weeks
Scaling Operational Efficiency for a fast-growing B2B SaaS Company
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.