The Situation
A CTO, VP Operations, or Head of Enablement where onboarding takes too long, escalation costs are too high, and the knowledge experienced employees carry in their heads is locked in documents, wikis, email threads, and tribal memory nobody can efficiently access. Every resolved problem disappears into a ticket close note instead of becoming a reusable asset. Commercial AI tools either can't reach the internal knowledge or expose it to data-privacy risk the organization won't accept.
The Value
SCKB deploys a KCS v6-governed knowledge base that captures knowledge at the moment of problem-solving — so resolving an issue automatically improves the knowledge base for the next person. The system runs on your own infrastructure using PostgreSQL full-text search — no external AI APIs, no vector database licensing, no data leaving the building. It is auditable, maintainable (standard Scala/PostgreSQL stack), and extensible.
How It Works
- KCS Readiness & Knowledge Source Inventory — existing documentation, wikis, and ticket history assessed; article types mapped; data quality reviewed.
- SCKB Deployment & Configuration — deployed on client infrastructure; KCS workflow, access controls, and article templates configured.
- Article Seeding & Migration — 20–50 seed articles built covering the highest-escalation topics.
- Team Onboarding & Workflow Validation — KCS workflow walkthrough; retrieval quality validated against real queries.
- Handoff & Documentation — architecture, user, and operations guides; admin team confirms independent operation.
What You Get
| Deliverable | Description | Value to You |
|---|---|---|
| Deployed SCKB Instance | Production installation on your infrastructure — PostgreSQL, application layer, configured KCS workflows | A working, governed knowledge base — not a design document |
| Seed Article Corpus | 20–50 KCS-structured articles covering highest-escalation topics | Immediate value on day one |
| KCS Workflow Configuration | Article types, capture workflow, publish review process, and access roles | The system improves over time without a dedicated knowledge manager |
| Retrieval Quality Validation | Test query set executed and documented; search tuned | Confirms the system finds what it should before handoff |
| Architecture, User & Operations Guides | Deployment config, authoring patterns, and upgrade path documented | Enables independent operation and extension |
Typical Duration
4–6 weeks. Well-organized existing documentation with a defined initial scope completes in 4–5 weeks including seeding. Fragmented knowledge assets or a large seed corpus typically require 5–6 weeks.
Why Now
The cost of inaccessible institutional knowledge is paid continuously — in onboarding time, escalation volume, and decisions made without information that exists somewhere in the organization. SCKB's KCS approach breaks this loop: the first resolution produces the article, the second encounter finds it. The infrastructure cost is server time, and the data stays on-premise — no per-seat AI licensing, no data-privacy exposure.
Grounded in Real Experience
Grounded in a decade at Art Technology Group (ATG), where Tony built deep expertise in enterprise commerce, search, and knowledge management. SCKB itself is an open-source system TJM Solutions built and operates.
Ready to Talk?
Schedule a call to discuss whether KCS Knowledge Base Implementation is the right starting point for your organization.
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