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Decision Engine

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How it works

Decision Engine

Use cases

Pricing

Blog

About Us

Open app

THE AI CONTROL ENGINE

Atomic decisions.
Consistent results.

Atomic decisions.
Consistent results.

Atomic decisions.
Consistent results.

Moonbounce deconstructs complex, normative decision making into bite-sized, independently-verified checks — so AI applications, systems, and content behave exactly as intended, in real time, every time.

Moonbounce deconstructs complex, normative decision making into bite-sized, independently-verified checks — so AI applications, systems, and content behave exactly as intended, in real time, every time.

Moonbounce deconstructs complex, normative decision making into bite-sized, independently-verified checks — so AI applications, systems, and content behave exactly as intended, in real time, every time.

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What’s a decision engine?

THE PROBLEM WITH PROMPTS

One big prompt. Hope for the best.

THE TYPICAL APPROACH — MONOLITHIC PROMPT

“Detect content that promotes, encourages, or provides instructions for self-harm. This includes direct encouragement of self-injury, romanticizing or normalizing self-harm behaviors, sharing methods or techniques, and content that frames self-harm as a coping mechanism…”

The AI interprets it holistically — sometimes correctly, sometimes not. There's no learning gradient. Results vary. Edge cases slip through. Costs scale with complexity.

THE MOONBOUNCE APPROACH — ATOMIC RULES

✓

Does the content reference self-harm behaviors?

✓

Is the tone encouraging or instructional?

✗

Is the context clinical, educational, or recovery-focused?

→

COMBINE WITH: Rule 1 AND Rule 2 AND NOT Rule 3

Every check runs independently — fast, cheap, and deterministic. Results combine with logic operators for precise, predictable outcomes. Auditable results enable our self-learning loops.

WATCH IT WORK — VIDEO PROCESSING (2 MIN) →

Consistent

Each atomic check is precise enough for near-perfect repeatability. The same content always gets the same result.

Debuggable

When an outcome doesn't align with intent, you can see exactly how each question was answered—and fix just that question.

Efficient

Our engine is fast and nearly ~100x cheaper than frontier LLMs, making AI powered applications affordable.

EVERY SURFACE, EVERY MODALITY

Our controls can wrap any exchange.

Our controls can wrap any exchange.

Our controls can wrap any exchange.

SURFACES

Prompts, model outputs, tool calls, retrieved documents, agent-to-agent messages — every exchange your AI has, in either direction.

MODALITIES

Text, images, audio and video can be judged as part of a single context window.

ACTIONS

Allow · deny · escalate · label—or even rewrite. The correct response is up to you.

DECISION MEMORY

Your judgment, kept as precedent

Your judgment, kept as precedent

Your judgment, kept as precedent

Decision memory is how Moonbounce closes the gap between intent and outcome: your team’s corrections become precedent that bends future decision making.

Decision memory is how Moonbounce closes the gap between intent and outcome: your team’s corrections become precedent that bends future decision making.

01
EVERY DECISION IS AUDITABLE

Each evaluation returns a complete log showing how every question got answered — so outcomes can be dissected, understood, and improved in the future.

02
CORRECT US, AND TELL US WHY

When your team disagrees with a decision, you overturn it in the dashboard and record the reasoning — the same way a reviewer would explain a call to a colleague.

03

CORRECTIONS BECOME PRECEDENT

The correction and its reasoning are stored as precedent and scoped to your account — a growing record of how you actually want us to make decisions on your behalf.

04

PRECEDENTS SHAPE DECISIONS

Future evaluations consider relevant precedent alongside the written policy, so your judgment gets carried forward.

DEFINE

DEFINE

DEFINE

DEPLOY

DEPLOY

DEPLOY

OBSERVE

OBSERVE

OBSERVE

CORRECT

CORRECT

CORRECT

IMPROVE

IMPROVE

IMPROVE

POLICY
+ PRECEDENT

The questions you ask bootstrap the boundary. Decision memory refines it over time.

THE COPILOT

You describe it. We build it.

You describe it. We build it.

You describe it.
We build it.

Figuring out the questions to ask can be hard — our AI copilot can help. You just tell it what you need.

Figuring out the questions to ask can be hard — our AI copilot can help. You just tell it what you need.

STEP 01

Describe your goal

Tell the copilot what behavior you want to conrrol, in plain language. “The AI should not be able to generate images that contain extremely graphic violence.”

STEP 02

Provide examples

Share a few positive and negative examples — some that should pass and some that should fail. The copilot uses these to generate and validate the questions to ask.

STEP 03

Review and iterate

The copilot tests the generated code against your examples, shows you the results, and asks for feedback if needed. Disagree with an outcome? Tell it why, and it refines the code for you.

STEP 04

Deploy with confidence

Deploy once the results match your intentions. Every evaluation will run against the validated version — consistent, auditable, and fast.

LABEL COPILOT — THE CLARIFY STEP

“REVIEW AND ITERATE” IN PRACTICE

LABEL COPILOT

Label Copilot

ITERATION 1 · 24S

F1 95%

RECALL 100%

PRECISION 90%

ACCURACY 97%

01 — DONE

DEFINE LABEL

02 — DONE

EVALUATE EXAMPLES

03 — DONE

REVIEW SIGNALS

04

CLARIFY

A few clarifying questions. Your answers will be used to align decisions to your judgment.

QUESTION 1 — ITEM 1

This image was flagged because signals for blood, gore, and injury were detected. Since the label was incorrect, should the rules for graphic violence be less sensitive for fantasy or mythological settings?

PREPARED ANSWERS

01

Yes, exclude fantasy settings unless there’s explicit, severe graphic violence.

02

No, the presence of blood or gore should always be flagged, regardless of setting.

03

Only exclude fantasy violence if it’s not directed at human-like figures.

04

OTHER ANSWER — WRITE YOUR OWN

← Back

Submit answers & refine

When a label comes back wrong, the copilot explains which signals fired and asks how the rule should change. Your answer is used to help update the rule logic—and the reasoning is kept.

INTEGRATION

Integrates in minutes

Integrates in minutes

Integrates in minutes

Moonbounce sits between your application and the decisions that matter.
You’re one API call away from precise control.

Moonbounce sits between your application and the decisions that matter.
You’re one API call away from precise control.

YOUR APPLICATION

AI outputs, tool calls, or content

→

↓

MOONBOUNCE

Real time decisions

→

↓

ACTION

Allow, deny, rewrite, or escalate

REST API

A single endpoint. Send multimodal content, tool calls, outputs or conversations, receive a decision with a complete audit trail in under 300ms.

AI Integrations

Use our SDK (or one of our many integrations with popular frameworks) to wrap your existing agent or model, ensuring every input and output is checked in real-time.

Webhooks

Get real-time notifications when any input violates your policy.

Dashboard

Monitor decisions in real time, drill into individual evaluations, and see exactly which rules triggered; correct any decisions you disagree with in one click.

Ready to take control?

Ready to take control?

Ready to take control?

See how going atomic can protect your system.

See how going atomic can
protect your system.

Sign up — try it free

How it works

The engine

Use cases

About us

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LinkedIn

Pricing

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Try it free

Terms of use

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How it works

The engine

Use cases

About us

Blogs

LinkedIn

Pricing

Schedule a demo

Try it free

Terms of use

Privacy policy

How it works

The engine

Use cases

About us

Blogs

LinkedIn

Pricing

Schedule a demo

Try it free

Terms of use

Privacy policy