We Do Not Start With the Technology
A successful Knowledge Hub begins with understanding the organization.
Before recommending SharePoint structures, AI agents, automations, licensing, or technical tools, Pixeldust studies how information is created, stored, shared, protected, and used across the business.
Our Discovery Framework uses ten focused assessment areas to uncover:
- Where important knowledge currently lives.
- Which information employees struggle to find.
- What knowledge exists only in employees’ heads.
- Which documents can be trusted.
- Who should be allowed to access different information.
- Where AI can provide practical value.
- What must be corrected before implementation.
- How the system will be maintained after launch.
The result is not simply a collection of completed questionnaires. It is a clear implementation plan based on the organization’s actual needs, risks, systems, and priorities.
What the Discovery Process Produces
The Discovery Framework gives Pixeldust the information needed to define:
- The business problems the Knowledge Hub should solve.
- The departments, locations, and users included in the project.
- The documents, systems, and employees that hold critical knowledge.
- The information that must be captured, rewritten, organized, or excluded.
- The security and permission structure.
- The best starting point for an internal assistant or website agent.
- Required Microsoft, Google, or other platform capabilities.
- Licensing and technical dependencies.
- Testing and acceptance requirements.
- Governance and ongoing maintenance responsibilities.
- Project scope, deliverables, schedule, and estimated cost.
Not every organization completes every question at once. A focused pilot may require only selected assessments, while a company-wide Knowledge Hub may require all ten across several departments.
The Ten Discovery Assessments
1. Executive Discovery
Goal
Establish why the organization is considering a Knowledge Hub and what business results leadership expects.
This assessment identifies the project’s strategic purpose, executive sponsor, priorities, boundaries, risks, and definition of success.
Example Questions
- What knowledge problem is creating the greatest cost or risk?
- Which repeated questions continue reaching owners or senior employees?
- What would a successful first phase accomplish?
Outcome
A defined business case, executive sponsorship, initial scope, priority use cases, and measurable project objectives.
2. Information Asset Inventory
Goal
Locate the information that already exists and understand where it is stored.
Knowledge may be scattered across SharePoint, Teams, Google Drive, shared folders, inboxes, databases, paper files, employee computers, and business applications.
Example Questions
- Where are policies, procedures, forms, manuals, templates, and price lists stored?
- Which documents are considered authoritative?
- Which information sources should be reviewed first?
Outcome
An inventory of important information sources, content owners, file types, systems, sensitivity levels, and migration priorities.
3. Department Knowledge Discovery
Goal
Understand how each department actually works and what employees need to know to perform their jobs.
This assessment examines official procedures as well as the practical methods, exceptions, workarounds, and judgment calls employees use every day.
Example Questions
- What questions do employees repeatedly ask?
- Which tasks depend on help from a specific experienced employee?
- Where do handoffs, delays, or inconsistent answers occur?
Outcome
A department-level map of workflows, responsibilities, recurring questions, procedures, decision rules, dependencies, and knowledge requirements.
4. Data Quality Assessment
Goal
Determine whether existing information is accurate and reliable enough to become part of the approved Knowledge Hub.
Uploading every available document does not create a trustworthy system. Outdated files, conflicting instructions, duplicate procedures, and unclear ownership must be addressed first.
Example Questions
- Are multiple versions of the same procedure being used?
- Who can resolve conflicts between documents?
- Which content should be corrected, archived, rewritten, or excluded?
Outcome
A documented content-cleanup plan identifying authoritative sources, duplicate material, outdated information, missing ownership, and required revisions.
5. Security and Permissions Assessment
Goal
Define who may access each type of organizational information.
The Knowledge Hub must distinguish between public, internal, confidential, regulated, and highly restricted information. Employees should only receive information appropriate to their identity, role, department, location, and responsibilities.
Example Questions
- Which roles should have access to each knowledge area?
- Does the organization handle employee, customer, financial, legal, or health information?
- What information must never be available through a public website agent?
Outcome
A permission model covering access groups, restricted content, public information boundaries, approval responsibilities, retention requirements, and security exceptions.
6. Knowledge Gap Assessment
Goal
Find valuable knowledge that has never been properly documented.
Some of the organization’s most important knowledge may exist only through experience, memory, informal training, or conversations with long-term employees.
Example Questions
- Which critical processes exist mainly in someone’s head?
- What would slow down if a key employee became unavailable?
- Which exceptions are missing from official procedures?
Outcome
A prioritized knowledge-capture plan identifying subject-matter experts, interviews, process walkthroughs, demonstrations, new documentation, and validation requirements.
7. AI Readiness Assessment
Goal
Determine whether the organization’s information, permissions, technology, and expectations are ready to support AI-assisted access.
AI cannot provide dependable business answers when the source material is incomplete, outdated, contradictory, or poorly secured.
Example Questions
- What specific questions or tasks should AI help with first?
- Are approved sources available for those use cases?
- Which questions should the assistant refuse or escalate?
Outcome
A practical AI readiness score, recommended first use case, technology requirements, agent boundaries, human-review expectations, and identified preparation work.
8. User Acceptance Testing
Goal
Confirm that the Knowledge Hub and its AI assistant work correctly before broad release.
Real employees test real questions based on their roles. Testing evaluates accuracy, usefulness, citations, permissions, failure behavior, and information exposure.
Example Questions
- Did the answer use the correct source?
- Did the system reveal anything the user should not see?
- Did the assistant respond safely when reliable information was unavailable?
Outcome
A documented test record, correction list, security validation, content updates, configuration changes, and formal business approval for launch.
9. Governance and Ownership
Goal
Create the operating process that keeps the Knowledge Hub accurate after implementation.
A Knowledge Hub is a living business asset. New procedures, decisions, lessons, policies, and answers must continue entering the system through a controlled process.
Example Questions
- Who owns each department or knowledge domain?
- How will new information be reviewed and approved?
- Who is responsible for correcting outdated or conflicting information?
Outcome
A governance model defining ownership, submission, review, approval, publishing, retirement, permission changes, review schedules, feedback, and escalation.
10. AI Roadmap and Future Opportunities
Goal
Identify how the Knowledge Hub can expand after the foundation and first use case have been proven.
Future opportunities may include additional department agents, onboarding support, customer service, sales enablement, website chat, workflow automation, reporting, and system integration.
Example Questions
- Which department should be added next?
- Which repeated task creates the most delay or expense?
- Which opportunities should be deferred until the information or process is ready?
Outcome
A phased roadmap that ranks opportunities by business value, implementation effort, risk, licensing, technical dependencies, and readiness.
How Discovery Is Conducted
The assessment process may include:
- Leadership interviews.
- Department workshops.
- Employee questionnaires.
- Subject-matter expert interviews.
- Document and system reviews.
- Workflow mapping.
- Permission reviews.
- Recorded and transcribed discovery sessions with approval.
- Sample searches and test questions.
- Review of Microsoft 365, Google Workspace, or other existing platforms.
Pixeldust adapts the process to the size and complexity of the organization. A small pilot may focus on one department and one clear problem. A larger implementation may require interviews and assessments across multiple locations, teams, systems, and information classes.
From Discovery to Implementation
Discovery findings are translated into a defined project plan.
Pixeldust uses the results to determine:
- What information is included.
- What must be cleaned or documented.
- Which users and departments are included.
- How permissions will work.
- Which technology and licensing are required.
- Which AI agents or interfaces should be created.
- How the system will be tested.
- Who will maintain the information.
- What the project will deliver.
- What the implementation will cost.
The final quote and Statement of Work define the approved scope, deliverables, responsibilities, assumptions, schedule, licensing, acceptance criteria, and change-control process.
Why This Framework Matters
Many AI projects begin with a chatbot and only later discover that the organization’s information is scattered, unreliable, poorly secured, or undocumented.
Pixeldust reverses that process.
We first understand the organization. Then we organize and protect its knowledge. Only after the foundation is ready do we configure the tools that make that knowledge easier to use.
This reduces technical risk, prevents uncontrolled project scope, protects sensitive information, and gives the organization a Knowledge Hub built around how the business actually operates.
Start With a Focused Assessment
You do not need to solve every knowledge problem at once.
Pixeldust can begin with one department, one recurring problem, or one high-value use case. The Discovery Framework identifies the most practical starting point and creates a roadmap for expanding the Knowledge Hub over time.
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