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Controlled autonomous AI · in development for defence

Autonomous where it counts. Governed where it matters.

Aegis AI is a controlled, autonomous multi-agent intelligence platform for defence and other high-assurance environments. It is designed to plan, act and improve on its own — with every action passing through a military-grade safety architecture you stay in command of, on your own hardware, with no cloud dependency. Our most ambitious system, in active development.

The control layer

The reason autonomous AI is safe to deploy.

Autonomy is only useful if you can trust it. Aegis is built to govern every action through a layered safety stack — the difference between an AI that acts, and an AI you can hand authority to.

Kill switch & authority gating

An atomic halt that stops the system instantly, with revival gated behind operator authority. Role-based control — system-admin, operator, observer, autonomous — decides who can do what.

Five-stage escalation

A formal escalation state machine (Normal → International) with a risk multiplier. Higher-stakes actions demand higher assurance before they ever execute — no silent escalation of capability.

Values-alignment gate

An immutable identity core with a fixed set of values that every action is checked against, in two layers. The system cannot quietly redefine its own purpose or step outside its mandate.

Hallucination & injection defence

A multi-component hallucination-detection pipeline, prompt-injection blocking and PII redaction — so outputs are filtered and adversarial input is contained before it reaches an agent.

The intelligence

A 38-agent runtime, on your own cluster.

A single orchestrator routes each task across a swarm of specialist agents — security, reasoning, engineering and analysis — backed by a six-layer memory.

OrchestratorSecurityGuardianGuardrails SwarmCommanderCausalReasonerSymbolicReasoner MetaLearnerSelfReflectionMemoryKeeper LearningMasterPlanningArchitectCodeMaster DebugExpertDevOpsResearchAnalyst DataScienceSandboxAgentMultiModal QualityGuardianSystemMonitor+ 18 more

Orchestrated multi-agent swarm

One entry point routes each task to the best-fit agent(s) — a SecurityGuardian for threat detection and policy enforcement, plus reasoning, engineering and analysis specialists — under one coordinator.

Built to be autonomous

Two self-running loops give it initiative: a perceive–plan–act–reflect–learn cognitive cycle, and a self-improvement engine that audits, diagnoses and evolves its own behaviour.

Six-layer persistent memory

A hybrid memory spanning a structured store, vector recall, an append-only ledger and episodic layers — so the system remembers context, decisions and lessons across restarts.

On-premise & air-gappable

Designed to run on open models on your own hardware — edge devices to a private cluster — with no cloud dependency, for environments where data physically cannot leave the building.

How a task flows

Every action runs the gauntlet.

1
Intake & alignmentA request enters one runtime and passes the values-alignment gate before anything runs — checked against the system’s immutable mandate.
2
Route & reasonThe orchestrator dispatches the task to the best-fit agent(s); the cognitive loop plans and acts, grounded in six-layer memory.
3
GovernOutput runs the safety stack — hallucination detection, injection & PII filters, escalation checks. Operator authority and the kill switch sit above it all.
4
LearnThe self-improvement engine records the outcome and adapts — under the same governance, never outside it.
Our most ambitious system — and the earliest in its build. The safety architecture and 38-agent runtime are real and substantial; Aegis is in active development, not yet a deployable product. We’re building it the honest way: governance first, capability second. If your team lives behind the “data cannot leave the building” constraint, we’d like to build it with you.