/Inapse In(c)law

/COMPLIANCE AT THE INPUT LAYER

Inapse In(c)law embeds regulatory compliance and rule enforcement directly into the execution pipeline — before actions reach the network.

Define what agents can do, what they cannot, and what must be verified — all enforced at the keyboard level.

AgentintentIn(c)lawrulesExecutioncompliantAuditverified

/The Problem

/COMPLIANCE IS AN AFTERTHOUGHT

Today's AI agents and automated pipelines execute first, comply later. Regulatory checks happen at the cloud layer — after data has already left the device, after transactions are already submitted.

Post-hoc compliance

Rules checked after execution, not before

Cloud-layer enforcement

Compliance depends on server-side middleware

No agent awareness

AI agents have no built-in regulatory model

Jurisdiction blind

Execution ignores geographic and legal context

"If compliance happens after execution, it's not compliance — it's damage control."

/The Shift

/MOVE RULES TO THE ORIGIN

In(c)law moves compliance enforcement to the input layer — the earliest possible point in the execution pipeline. Rules are evaluated locally, before any action leaves the device.

Before — Cloud Compliance

01Action submitted
02Cloud receives data
03Rules checked remotely
04Violation detected (too late)

After — Input-Layer Compliance

01Intent captured
02Rules evaluated locally
03Non-compliant actions blocked
04Compliant actions proceed

"Compliance at the origin means violations never happen — they're prevented."

/How It Works

/RULE ENGINE AT THE KEYBOARD

In(c)law operates as a programmable rule engine embedded in the input layer. Every intent is evaluated against configurable compliance policies before execution.

01

💡

Intent captured

02

Rules evaluated

03

🛡

Violations blocked

04

Compliant executed

Rule types

Jurisdictional, financial, behavioral

Evaluation

Local, sub-millisecond

Updates

OTA policy refresh

/Compliance Domains

/WHAT IN(C)LAW ENFORCES

In(c)law supports multiple compliance domains — from financial regulations to data sovereignty, from agent behavior limits to cross-chain transaction rules.

FINREG

Financial compliance

Transaction limits, KYC/AML rules, spending caps, and multi-signature requirements enforced before execution.

GDPR / CCPA

Data sovereignty

Geographic restrictions on data movement. Intent stays local when regulations require it.

AGENT POLICY

Agent behavior limits

Configurable boundaries for AI agent actions — what they can execute, how much they can spend, which chains they can access.

CHAIN RULES

Cross-chain rules

Chain-specific compliance rules applied before bridging or multi-chain execution.

"One rule engine. Every compliance domain. Enforced at the source."

/AI Agent Compliance

/AGENTS THAT FOLLOW RULES

As AI agents gain execution capabilities, compliance becomes critical. In(c)law ensures every agent action passes through a rule evaluation layer — no exceptions.

Without In(c)law

  • Agents execute freely
  • No spending limits
  • No jurisdiction checks
  • Compliance is optional

With In(c)law

  • Agents execute within rules
  • Configurable spending limits
  • Jurisdiction-aware execution
  • Compliance is enforced

"In(c)law doesn't restrict agents — it makes them trustworthy."

/Role in Inapse

/THE COMPLIANCE LAYER

In(c)law sits between intent capture and execution — the compliance checkpoint that ensures every action meets defined rules before it reaches Inclave or the network.

01

Input

Captures intent

02

K2K

Secures intent

03

In(c)law

Enforces rules

04

Inclave

Executes value

COMPLIANCE BY DESIGN

/RULES BEFORE EXECUTION.

Every action verified. Every rule enforced. At the input layer.