Moonbounce deconstructs complex rules into atomic, independently-verified checks—so your AI systems and user-generated content behave exactly as intended, every single time.

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The problem with prompts

Most AI control systems rely on monolithic prompts to enforce complex policies. Moonbounce takes a fundamentally different approach.

The typical approach

One big prompt. Hope for the best.

Complex policies get stuffed into a single prompt. The AI interprets them holistically—sometimes correctly, sometimes not. Results vary. Edge cases slip through. Costs scale linearly with complexity.

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 Moonbounce approach

Atomic rules. Consistent results.

We deconstruct each policy into its smallest, indivisible checks. Every check runs independently—fast, cheap, and deterministic. Then we combine results with logic operators for precise, predictable outcomes.

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

Intent, meet outcome.

A complex policy statement becomes a set of lightweight, independently verifiable checks—each one fast, cheap, and deterministic.

Natural language policy

“Ensure the code follows the golden path rule — functions should have a single happy path with early returns and guard clauses, avoiding deeply nested conditionals.”

Moonbounce decomposition engine

Rule 1

Is there an if-else branch present in the code?

✓

Rule 2

Does the if-branch contain a return statement?

✓

Rule 3

Does the else-branch also contain a return statement?

✗

Rule 4

Are conditionals nested fewer than 3 levels deep?

✓

Combined with AND

Result: No Violation

Rule 3 confirmed the else-branch has no return statement — the function uses early returns and follows the golden path pattern.

Why atomic rules win

It's not just an engineering choice—atomicity is how you get AI control that actually works at scale.

97%

Consistency across identical content

10x

Lower cost per evaluation

300ms

Average response time

Consistent

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

Debuggable

When a decision seems wrong, you can see exactly which rule triggered—and fix just that rule, not the whole policy.

Efficient

Lightweight checks run fast and cheap. Short-circuit evaluation means you often don't need to run every rule.

You describe it. We build it.

You don't need to think in atomic rules—our AI copilot handles the decomposition. You just tell it what you need.

Step 01

💬

Describe your policy

Tell the copilot what behavior you want to enforce, in plain language. “Users should not be able to post content that contains personal attacks or hate speech targeting protected groups.”

Step 02

🧪

Provide examples

Share both positive and negative examples—content that should pass and content that should fail. The copilot uses these to generate and validate candidate rule sets.

Step 03

🔄

Review and iterate

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

Step 04

🚀

Deploy with confidence

Once your rule set matches your intentions, deploy it. Every evaluation runs against your validated atomic rules—consistent, auditable, and fast.

Integrates in minutes

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

📱

Your application

User-generated content or AI output.

→

↓

Moonbounce

Atomic rule evaluation in real time.

→

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⚡

Action

Allow, flag, block,
or escalate

REST API

A single endpoint. Send content, receive a decision with full rule-level attribution in under 300ms.

Webhooks

Get real-time notifications for flagged content, policy violations, or any event you want to track.

Dashboard

Monitor decisions in real time, drill into individual evaluations, and see exactly which rules triggered.

Integration points

Ready to take control?

See how going atomic can transform your content moderation and AI governance.

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