The Execution Boundaryfor Autonomous Systems.

A deterministic layer that governs how intelligence becomes action — enforcing limits, coordinating distributed instances, adapting routing under policy, and verifying every decision.

The execution layer beneath intelligence.

Explore Platform

Hybrid behavior trees meet LLM reasoning.

Your AI runs through structured decision paths, where language models produce reasoning and the runtime governs how that reasoning is executed. Behavior remains bounded and predictable. There are no uncontrolled processes and no silent failures. Every action is recorded and cryptographically verifiable.

Execution, intelligence, memory, and proof function together as a single system. The same runtime deploys consistently across servers, edge devices, and robotic hardware—preserving identical guarantees in every environment.

Observe how your systems operate in real time—how decisions evolve, how behavior adapts, and how each action is recorded and verified.

Every layer working together

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Execution

Runs AI with defined limits, ensuring behavior remains predictable across devices and fleets.

Intelligence

Handles decision-making using language models, while execution remains structured and controlled.

Memory & Proof

Keeps a complete record of decisions and execution, with cryptographic verification for auditing and review.

One System. Two Environments.

AI Agents

The same system governs AI execution in software and robotics environments.

If you're building AI agents that run on servers, see how execution, coordination, and verification apply to software-based systems.

If you're building robots or edge devices, see how the system integrates with ROS 2 and enforces safe, bounded AI execution in the physical world.

Different environments. The same nervous system.

Robotics

Build on the Nervous System

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All SDKs connect to the same unified execution and coordination layer. The API surface is consistent across languages, and behavior remains identical between local development and production environments.

Develop locally. Deploy anywhere. Same execution guarantees.

View SDK documentation

import { IgrisClient } from '@igris-inertial/javascript-sdk';

const client = new IgrisClient({ apiKey: process.env.IGRIS_KEY });

const result = await client.execute({

behaviorTree: "warehouse_navigation",

input: { waypoint: "A3" }

});

Verifiable execution by design

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Air-gapped operation

The system is designed to operate independently of network access. Deploy in secure facilities, remote environments, or fully offline locations.

Zero-trust device enrollment

Devices authenticate cryptographically before joining a fleet. Each device is verified individually. Untrusted or compromised hardware is rejected automatically.

Device-bound encryption

Models and execution data are encrypted and bound to specific hardware. If a device is lost or removed, its data remains inaccessible.

Verified updates

Model updates and configuration changes require cryptographic signatures. Unsigned or modified artifacts are rejected before deployment.

Verified fleet synchronization

When connectivity is available, fleet state and configuration changes are verified before being applied. Only signed and authorized updates propagate.

Deploy. Verify. Optimize.

Deploy

Install a single binary on any supported device. Execution, decision routing, memory, and proof are included from the start. The runtime operates independently of containers or external services.

Verify

Execution follows defined constraints. Behavior trees execute predictably. Each decision is recorded and cryptographically signed. Verification does not depend on network access.

Optimize

As deployments expand, visibility increases. The dashboard provides insight into execution health, decision routing, and verification status across the fleet.