PLATFORM

A neurosymbolic runtime for agent orchestration and policy enforcement.

ColleaiQ sits between the LLMs and tools you already run and the policies your operation has to satisfy. It plans every action, enforces the rules you loaded, traces the result, and lets you replay it against a future policy version.


ARCHITECTURE

What sits where.

The planner proposes the next action. The symbolic policy core checks it against the rules you loaded. The trace surface writes a structured record. Customer LLMs and tools attach at the edges.

Every agent action is checked against policy before execution, the way an OS kernel checks every syscall.

PLANNERCOLLEAIQ CORESYMBOLIC POLICY CORETRACE SURFACECUSTOMER ENVIRONMENTCUSTOMER LLMSCUSTOMER TOOL SERVERSCUSTOMER IDPCUSTOMER VAULT── solid 1px runtime data flow┄┄ dashed 1px trust-boundary crossing

Conceptual architecture. Box names map to real components; nothing here is a product screenshot.


COORDINATION

How multiple agents are composed and constrained.

A session holds a roster of agents with declared capabilities. The planner picks the next agent for the next step. The kernel runs the policy check before any state change. Cross-agent handoffs are explicit and logged with the rule that allowed the handoff.


KERNEL

Policy as data. Action gates. Signed rejections.

Rules compile to a symbolic graph the planner consults before every tool call. The kernel pins each trace to the policy version that produced it. Rejected actions return a signed rejection with the citation, not a silent failure.


TRACE

What each agent saw, considered, rejected, and decided.

Each step writes inputs, alternatives, the chosen action, the policy citation, and the human reviewer who released the action where one was required. Engineering teams replay traces against updated policies to see which past decisions a new rule would have changed.

Agent utterance

The action the agent proposed and the chain of reasoning that produced it.


Policy applied

The rule that allowed the action and the policy version that produced it. Signed against the version in force at the moment of execution.


Evidence captured

The inputs the agent saw, the sources it consulted, and the tool responses that informed its proposal.


Human review

The reviewer identity and decision where one was required by policy. Absent on actions the kernel released without escalation.


Outcome

What actually happened: the action taken, blocked, or held for review, with the timestamp recorded against the trace identifier.

What a trace records, per action. Replayable against future policy versions to see which past decisions a new rule would change.


INTEGRATION

Wraps the models, tools, identity, and storage you already run.

Bring the LLM provider you pay for. Bring the tool servers your agents call. Auth flows through your IdP. Secrets stay in your vault. ColleaiQ adds the planning and policy layer between them.

Models

LLM-provider-agnostic

OpenAI, Anthropic, Mistral, or self-hosted. The planner is the same regardless of provider, and switching providers does not change traces.

Identity and tools

Through your existing stack

OIDC and SAML through your IdP, secrets in your existing vault, tool servers exposed through MCP or REST. The kernel wraps them with policy-aware contracts.

DEPLOYMENT

Where the engine runs.

VPC, on-premises, or an EU-sovereign instance. The operational footprint is named explicitly, not abstracted away. SaaS is not the default.

Sovereign EU cloud

You run it in your tenant

  • EU data residency, no US transfer
  • Customer-owned keys & audit logs
  • Hardened reference architecture

Our live manufacturing deployment runs on this model.

Recommended for NIS2 / DORA

On-prem / air-gapped

Inside your perimeter

  • No implicit access to data
  • Signed update channel
  • Hardening & deployment packs
Regulated operations, on-site data

Partner-managed (white-label)

Delivered by a managed-service partner

  • Multi-tenant isolation
  • Partner owns the customer relationship
  • We own the governance kernel
Regional scale, partner-operated

LIMITS

What the runtime does not do today.

An honest list of where the engine stops and the human reviewer stays in the loop. We do not auto-approve destructive actions. We do not generate the policies; you load them. We do not certify your operation against any framework; we generate the trace artefacts your auditor uses.


Want to see this in your plant? Write to christofferdreist@colleaiq.dk.