AI coding agents
Review evidence behind AI-generated code changes before merge or release decisions.
Product
Make AI-assisted work reviewable before it becomes trusted.
MindForge Guard is a deterministic governance evidence layer for single-agent AI workflows. It helps teams inspect authority, evidence, state, and decision boundaries before AI-assisted work is accepted into business or engineering processes.
Single-agent governance evidence for human review
Not an approval system. Not a blocker. Not a control plane.
Guard remains recommendation-only, non-executing, deterministic, local-first where applicable, and human-review-oriented.
Support agents
Inspect authority scope, action trace, and missing evidence before service actions are trusted.
Operations agents
Review execution evidence and risk/drift signals before operational follow-through enters a human process.
Internal workflow agents
Keep internal approvals, handoffs, and workflow actions reviewable without turning Guard into a control plane.
From Evidence Pack to governance report
An Evidence Pack is the review bundle behind an AI-assisted action: task context, allowed scope, action trace, tool/data references, outputs, missing evidence, and reviewer notes.
Guard turns that evidence bundle into a governance report so reviewers can inspect authority boundary, execution evidence, missing evidence, and risk/drift signals before AI-assisted work is trusted.
Review your first single-agent action with evidence
Start with a sample agent action. Guard validates the evidence bundle, generates a governance report, and shows reviewers the authority boundary, execution evidence, missing evidence, and risk/drift signals.
Start with a sample agent action.
Validate the evidence bundle locally.
Generate a governance report for reviewer reading.
Inspect the authority boundary, execution evidence, missing evidence, and risk/drift signals.
A synthetic sample evidence bundle for local validation can help teams see the workflow without narrowing the product story to one sample workflow.
Editions by customer outcome
See the current governance evidence for one agent workflow.
Track governance signals over time.
Compare evidence states and uncover deeper signals.
Standardize adoption, review packets, and procurement around the same bounded runtime posture. No extra runtime authority.
Trust and workflow docs
Use these docs to compare editions, explain the bounded posture, and move from evidence bundle to review bundle without authority expansion.
Secondary technical install
When you are ready to run Guard locally, install the current recommended v7.0.1 package: npm install -g @veeduzyl/mindforge-guard@7.0.1.
Then follow the first report workflow in the docs to review a sample single-agent action with evidence.
Boundary
Guard stays recommendation-only, additive-only, non-executing, default-off where applicable, non-control-plane, deterministic, local-first where applicable, and human-review-oriented.
No approval system. No blocking system. No safe-to-deploy claim. No legal compliance guarantee. No compliance certification. No maturity certification.