The Platform

Your Operating Platform for Human + AI workforces.

Your org, re-staffed as a coordinated team of humans and AI workers. Fully managed, 24×7, inside your perimeter. Operators govern what humans and agents may do, anchored in Identity & Trust. Human leadership remains non-negotiable.

FULLY MANAGED · 24×7 KERNEL · CONTROL PLANE NOTHING BYPASSES
Human and Agent route through the Operator gate, which anchors a single spine down through Identity and Trust, the Kernel, and Grounding and Substrate. Nothing bypasses the Operator — every action gated, every layer yours.
How it works

Three layers. One kernel. Every action gated.

Agent-HQ is not a wrapper around a model. It is a layered operating system that governs every human instruction that sets direction for agents, and every agent action that executes on that direction. Nothing in the agent workflow bypasses the kernel. Governance by architecture.

Layer 01

Grounding & Substrate

The living data and systems foundation for Agent-HQ. Your knowledge bases, your team's LLM queries and prompts, your connected systems & retrieval pipelines. Together they form your organization's digital brain. This is the substrate on which everything else runs.

Layer 02

Control & Coordination Kernel

The orchestration plane. Agent-HQ's kernel runs goal-directed missions — marshalling tasks across agents and humans, routing workloads, maintaining state, and enforcing sequencing.

Layer 03

Identity & Trust

Agent-HQ is built on global standards: auth.md, ID-JAG, and SPIFFE/SPIRE, ensuring every AI agent carries a verifiable identity. The Operator governs what each agent identity may instruct, approve, or execute, with human oversight anchored in your existing IAM systems.

Multi-modal by design

Every sense. One core. Autonomy matched to risk.

Vision, voice, text and live data all flow into a single multi-modal core running inside your perimeter. One model context, one memory, one audit trail, regardless of how the work arrives.

From that core, work runs at the autonomy level each function has earned: Co-pilot where humans decide, Human-in-the-Loop where humans gate key actions, and Full Autonomy - earned and monitored — where the risk profile allows it.

Vision, voice, text and data converge into one multi-modal core inside the perimeter, which fans out to three operating modes: Co-pilot where the human decides, HITL where the human gates, and Full Autonomy, earned and monitored.
The Operator

The gate between human intent and agent action.

The Operator gate moves along phase columns — Propose, Execute, Review — as autonomy is earned. It sits at Propose in Co-pilot, at Execute in HITL, and at Review in Autonomous. Every level is earned, every action is logged, accountability traces to a named person.

The Operator sits at the crown, connected directly to Identity & Trust. Every human instruction linked to agent actions crosses the Operator before reaching the kernel, ensuring governance is architectural, not optional.

Scale autonomy as confidence grows. Beneath every level, the same foundation holds: every action is audited, every deviation is logged, and accountability always traces to a named human. Not the system. Not the agent, a person.

Fully managed

We run it. You own it.

Agent-HQ is a fully managed service. We handle deployment, monitoring, incident response, model updates, and security: 24×7. You own the data, the decisions, and the outcomes.

Multi-Modal intelligence

AI that works the way your organization works, across text, vision, and voice. Agent-HQ natively supports every modality your team uses, with the same governance, identity, and security applied consistently. No silos. No workarounds. One unified framework.

Sovereign inferencing

Models run inside your perimeter. Nothing reaches a shared cloud inference endpoint unless you explicitly design it that way. Your data stays where it belongs — inside your boundary, under your control, always.

Model currency

We manage model updates, regression testing, and capability rollouts without disruption to running workloads. And also help you choose which models to run, because state-of-the-art isn't always the right fit for the job. Recommendations based on your needs, not a vendor's roadmap.

See it running against your work, not a demo script.

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