Skip to content

The product is launching soon and still being built. This site is the public preview.

← Back to MasterEngine.ai

Product

Governed action for revenue operators

Agents propose value-moving work. Policy evaluates every action. Humans approve where required. Evidence proves what ran.

Four primitives, one operating model

MasterEngine is an approval and policy layer your revenue actions would run through — not a chatbot bolted onto your CRM.

Typed Missions

Value-moving work scopes into durable missions with explicit proposals — not silent scripts against your revenue stack.

Policy & Approval Layer

Deterministic policy evaluates tenancy, budget, and risk before anything consequential can run.

Exact-subject approval

Protected actions pause for a human decision bound to the exact subject. Change the action and the approval invalidates.

Approval history

What was proposed, who approved it, and what ran is recorded in an action history operators can review, with approval decisions kept append-only.

How one action moves: propose → policy → approval → evidence

Each step below describes how the platform is designed to behave, next to what the public synthetic demo shows today. The demo uses example data only and performs no live writes.

Governed action lifecycle (design vs. public demo)
StepWhat the platform is designed to doWhat the synthetic demo shows
1. ProposeAn agent drafts a typed proposal inside a Mission: action type and version, tenant, risk level, required approval level, expected value and cost, linked evidence, explicit preconditions, and an idempotency key. Nothing has run yet.The example mission “Recover lead leakage from paid search” for the fictional tenant Northstar Labs.
2. PolicyDeterministic checks run before anything continues: the tenant matches, the action type is allowed for that tenant, the data classification is permitted, at least one evidence record and explicit preconditions exist, expected cost fits the remaining budget, and high-risk actions carry an approval level. A pass only lets the proposal continue; it never executes it.GET /api/control-plane/policy/demo returns the allow/deny decision and reasons for a synthetic proposal, with execution reported as disabled.
3. ApprovalProtected actions wait for a human decision bound to the exact subject. If a bound field such as the target, arguments, or cost changes, the earlier approval no longer applies.Approve, Defer, and Reject are shown in Mission Control but stay disabled.
4. EvidenceWhat was proposed, what policy decided, who approved, and what ran is recorded in an action history with recorded approvals instead of a chat transcript.GET /api/control-plane/evidence/demo returns example evidence records with synthetic source URIs.

The ordering matters: a model can draft a proposal, but only deterministic policy and, where required, a human decision can move it forward. A model, retrieved document, or memory item never grants itself permission.

What you can inspect today

Honest boundaries: this marketing surface shows the model without pretending writes are live.

Public positioning

Homepage, security posture, and an honest waitlist path — no fake product claims.

Synthetic Mission Control

A labeled Mission Control demo showing mission → policy → approval → evidence with example data only.

Demo API routes

GET-only routes under /api/control-plane/*/demo that self-report mode: synthetic_demo.

What this public site does not do

There is no approval-layer write path from these pages, no billing, and no connector that can write to a customer system from this surface. Governed writes stay on the approval layer.

See the synthetic demo

Walk through Mission Control with example missions, approvals, and evidence — no live side effects.