DaemonCore is the operating system for autonomous AI agents.

Orchestration decides what should happen. DaemonCore determines what is allowed to happen.

Autonomous systems require deterministic boot, runtime management, capability boundaries, communication, auditability, portability and governance. DaemonCore provides that foundation.

Read the Architecture Documentation

Model agnostic
Governance built in
Deterministic boot

Where DaemonCore sits in the AI stack: beneath orchestration and agent frameworks, above the host operating system. Described in full below. — Where DaemonCore sits

From the top: user interfaces (IDE, CLI, web), then orchestration (workflows, pipelines), then agent frameworks such as LangChain and CrewAI, then AI models such as Claude, GPT and Gemini. DaemonCore is the governance layer beneath all of them, sitting directly above the host operating system and its hardware.

The industry has been rebuilding operating systems

Every agent framework reinvented the same primitives—memory model, boot sequence, governance, lifecycle, execution rules, vendor assumptions—one application at a time.

Operating systems solved these problems decades ago. Autonomous AI deserves the same foundation.

The evolution of AI control

Raw Prompts Hope for the best
Better Prompts More detailed instructions
Prompt Engineering Systematic instruction design
Orchestration Frameworks coordinate agents
Governance Protocol-enforced boundaries

Where risk appears

Drift

Agents interpret instructions differently over time. Without structural constraints, behaviour shifts unpredictably.

Ambiguity

Natural language instructions leave room for interpretation. Edge cases become judgment calls the model makes alone.

Responsibility

When something goes wrong, who’s accountable? Prompt-based systems make audit and attribution difficult.

Governance before execution

Most AI platforms focus on making agents more capable. DaemonCore focuses on making autonomous systems more dependable.

Orchestration

Coordinates agents. Decides what to do, when, and in what order. LangChain, CrewAI, AutoGen.

Governance

Defines boundaries. Validates outputs. Enforces constraints. Sits beneath orchestration.

Instead of asking models to behave, we build an environment where behaviour is constrained by architecture. Applications should not enforce the rules that govern themselves.

DaemonCore doesn’t give agents better instructions—it changes what counts as valid output. Agents produce protocol-shaped responses, and those responses are classified and validated before any action occurs.

How it works

Concrete mechanisms, not abstract principles.

Action Protocol

Only protocol-shaped outputs are eligible for action. Malformed proposals are rejected before execution.

How it is enforced

MAX Messaging Bus

Typed, schema-validated message routing between agents and systems. Messages that don’t match schema don’t route.

How routing works

Template-Driven Operations

Complex operations follow predefined templates with explicit boundaries: scope, required checks and output format.

See it applied

What evidence suggests this is real?

Not a mock-up: a real DaemonCore execution, recorded and replayable. Below is a verbatim excerpt — the governance gate running before the request is admitted.

recorded · RUN-001 · governance gate (advisory)

[INFO] [Enforcement] Config loaded: mode=advisory, strict_domains=(), threshold=10
[WARN] [EnforcementGate] Advisory: No skill match: No candidates found in any registry
[INFO] [Execution] Created exec-a41c2c95cbc8 | intent=code_review_request | trigger=queue_message:EVID-e9b58172 | participant=reviewer
[INFO] [MaxBusBridge] Dispatched EVID-e9b58172 -> execution exec-a41c2c95cbc8 (admission only; outcome pending)

Excerpt from the recorded RUN-001 runtime log. Timestamps, trace identifiers and an internal workspace path are omitted for readability; the wording is otherwise unaltered. The gate ran in advisory mode and the request was admitted — but no model executed, so the outcome is left pending. The full, unabridged recording is on the replay page.

RUN-001 · Recorded · Partial

A code review request, admitted through the governance gate

A genuine recorded run of the DaemonCore runtime: a code_review_request passing identity, publication, the governance gate and Execution creation. Replay it line by line.

RUN-001 is partial, and says so: the admission was recorded, but no model executed, the gate was advisory, and the recording is unsealed and not independently verified. For the full shape of the behaviour end to end, the illustrative walkthrough (GOV-001) is on the Proof page.

Replay the recorded admission

What we promise, and when

Current capabilities and future ambitions, kept separate.

V1 — current

Protocol-shaped output validation
Message schema enforcement
Template-constrained operations
Deterministic boot sequences
Audit trail for agent actions

V1.5 — planned

Cryptographic action signing
Hardware-backed attestation
Cross-agent capability delegation
Real-time constraint verification

We ship what’s working. V1.5 features are in development—we’ll announce them when they’re ready.

Explore

Each path deepens the picture rather than repeating it.

Engineers and architects