> For the complete documentation index, see [llms.txt](https://daokraft.gitbook.io/daokraft-docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://daokraft.gitbook.io/daokraft-docs/governance-intelligence-stack.md).

# Governance Intelligence Stack

Governance isn’t voting. It’s decision intelligence.\
Most governance failures originate before voting — from unclear proposals, missing context, or poor impact analysis.\
\
DAOKraft reframes governance as a compounding intelligence system:\
Idea → Structured Proposal → Governance Analytics → Outcome Simulation → Execution Tracking → Reputation Feedback\
Each layer reinforces the next, creating a continuously improving governance loop.<br>

<figure><img src="/files/7Wr7VKQ3D4MEVmyaYhKY" alt=""><figcaption></figcaption></figure>

#### 4.1 Proposal Intelligence

* Standardized proposal structuring
* Automatic risk, budget, and context detection
* Proposal quality scoring (clarity, completeness, feasibility)

#### 4.2 Governance Analytics

* Participation and turnout forecasting
* Delegate and voter distribution analysis
* Community sentiment detection
* Historical comparison with similar proposals

#### 4.3 Outcome Simulation

* Treasury and resource impact modeling
* Execution complexity and risk scoring
* Momentum and participation projections

#### 4.4 Execution & Accountability Intelligence

* Milestone and timeline monitoring
* Execution delay detection
* Post-execution reporting

DAOKraft does not execute transactions or control DAO assets.\
All intelligence is derived from DAO-native and publicly verifiable systems.

#### 4.5 Reputation & Feedback Loop

Outcome-based reputation profiles are built for:<br>

* Proposal authors
* Contributors and reviewers
* Consultants and agencies

Reputation is based on observable outcomes, not intent, and feeds back into future recommendations.<br>


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