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Knowledge work blueprint

Example Build

A delivery system that turns expert judgment into repeatable, reviewable work.

An example build for consulting, legal, engineering, finance, and professional services teams where documents, research, analysis, and approvals slow down delivery.

Example build. Not presented as a client result.

First workflow

Research-to-draft workflow with human review and source trail

Owner

COO, practice leader, delivery leader, or managing partner

Window

8-10 week first production sprint

Proof standard

Draft cycle time, review quality, source completeness, rework, and expert capacity returned

Decision Frame

What the first build has to answer.

Audience

Professional services leaders, COOs, practice leaders, and owners

Situation

High-value people spend too much time gathering context, formatting drafts, reconciling sources, and waiting for review.

Business question

Which parts of expert work can AI draft or check while humans keep judgment, quality, and client accountability?

Build Sequence

From idea to a managed operating workflow.

01 · Weeks 1-2

Map the expert workflow

Define inputs, source standards, draft types, review gates, quality criteria, and what must remain human-led.

02 · Weeks 3-6

Build source-grounded drafting

Create AI-assisted research, summarization, first-draft, QA, and citation workflows around approved knowledge sources.

03 · Weeks 7-10

Train the review cadence

Launch a manager review loop for draft acceptance, corrections, knowledge gaps, and quality improvements.

Operating System

What ClearForge would put around the work.

These layers keep the build tied to a workflow, not a demo. The goal is an owner cadence people can actually run.

Knowledge base

Connects approved templates, prior work, source files, and research rules.

Draft workflow

Turns intake and source material into reviewable first drafts.

QA checks

Checks missing evidence, unsupported claims, formatting, and policy issues.

Review loop

Captures edits, acceptance, reuse, and knowledge gaps for improvement.

Controls

Where humans stay in control.

No external delivery without human approval

Source trail required for claims and recommendations

Sensitive documents stay inside approved systems

Reviewers score draft quality and correction themes

Evidence To Bring

What makes the diagnostic useful.

Examples of recent deliverables and source materials

Current templates, review comments, and approval standards

Knowledge repositories and document permissions

Common rework themes and delivery bottlenecks

Value Signals

What leaders should inspect after launch.

Cycle time

Draft to review

Time from intake to first human-reviewable output.

Quality

Correction themes

What experts change and why.

Capacity

Expert hours

Time returned from low-judgment assembly work.

Related Paths

Keep moving from example to decision.