Control AI agentsbefore they go rogue.
HVT is the sovereign control layer for autonomous AI. Every agent action is verified, authorized and recorded before it touches a real system, and anything unsafe halts into SAFE HOLD.
View the evidenceTwo products. One sovereign stack.
Control what your AI agents can do, and run them on infrastructure you own.
HVT Agent Control
A fail-closed gate between every AI agent and every real system. Unverified, out-of-policy or high-risk actions never execute: they halt into SAFE HOLD and are logged.
HVT Private AI
Open-weight models run on hardware you control, behind identity, policy gates and an immutable evidence log. No commands or data touch third-party cloud APIs.
Follow one action through the loop.
Capture agent requests, tool calls, context and system state as they happen.
How to keep your AI agents under control
Autonomous agents are powerful and fallible. The SSOS governance loop sits between every agent and every real-world system, from energy and ports to aviation, defense and cyber — so a hallucinating, hijacked or runaway agent is stopped at the gate, not after the damage.
Each agent has a tool-call budget. Exceed it and the circuit breaker blocks further calls until the window recovers.
Switch governance OFF and trigger a rogue agent: actions reach critical systems and domain integrity collapses. Switch it ON: the same actions die at the gates and are logged.
Why you need a control layer
Deploying AI agents without a control plane means trusting third-party clouds, opaque models and unaudited autonomy with your critical systems.
Data & decision sovereignty
Open-weight models run on hardware you control. No commands or sensitive data touch third-party cloud APIs.
Agents that cannot go rogue
Models recommend; policy gates decide. Unverified, out-of-policy or high-risk actions never execute — they halt into SAFE HOLD.
Audit every autonomous act
Tamper-evident, hash-chained evidence records let regulators, auditors and courts replay exactly what an agent did and why.
Defense in depth
Seven control layers, from identity and policy gates to bounded tool adapters, so one failed check never means an unchecked action.
Law and human oversight built in
Compliance rules, human sign-off levels and multi-signature authorization map your policies and regulation directly into the control loop.
Staged, evidence-first adoption
A 24-week programme with 8 exit gates lets you prove capability on your own workloads before committing.
See every decision as it happens.
Throughput, block rate, threat mix and gate latency in one view. Simulated telemetry shown.
Write the rules once. Enforce them on every call.
Switch rules on and off, pick an action an agent might attempt, and see exactly how the gateway would decide.
policy: default-agent-policy rules: - min_evidence: L2 - egress: allowlist - budget: 14 calls / window - high_risk: require_approval - pii: redact
Evidence level L1 is below the required L2.
- Matched rule
- min_evidence: L2
- Evidence presented
- L1
- Logged
- Yes, hash-chained
The failure modes that make agents go rogue.
Prompt injection
Hostile instructions hidden in documents or tool output are rejected at the Verify gate before they reach a decision.
See it containedPrivilege escalation
An agent that tries to grant itself new authority is stopped by policy and logged with the evidence level it presented.
See it containedData exfiltration
Calls that move datasets to external endpoints are blocked unless an allowlist and a human sign-off both agree.
See it containedOne call between your agents and the real world.
Agents propose. The gateway verifies identity, checks policy, requires sign-off where needed, and records the result. Illustrative interface shown.
from hvt import Gateway
gw = Gateway(tenant="ministry-of-energy")
decision = gw.authorize(
agent="logistics-agent",
action="reroute_grid_load",
domain="earth",
evidence_level="L3",
)
if decision.allowed:
decision.execute()
else:
print(decision.state, decision.gate) # SAFE HOLD, POLICYEvidence your auditors can actually use.
Every decision is logged with the rule, the evidence level and the approver. Export it when someone asks.
This is a mapping to help gather evidence. It is not a certification and not legal advice.
Patent-pending inventions by Salem Salah bin Omair AlShamsi.
The control layer rests on four pending inventions, conceived and architected by Salem Salah bin Omair AlShamsi in Abu Dhabi.
HVT SWITCH™ Live-Gate AI Arbitration
A fail-closed physical and deterministic logical choke point intercepting all consequential agent actions. LLMs and autonomous models are prevented from triggering external effects without valid, unexpired sovereign authority.
Autonomous Execution Envelopes & Authority Graph
Cryptographic multi-dimensional boundaries capping rate, velocity, financial thresholds, geography and blast radius, so many individually permitted acts cannot sum up to one forbidden outcome.
Deterministic State Synchronization & DM-CODE
A tamper-evident, single-source state ledger providing continuous telemetry correlation across heterogeneous endpoints, designed for complete resistance against desynchronization.
Four Axioms Runtime Enforcement Engine
A constitutional governance engine embedding the Four Axioms That Never Bend into every compute layer: Capability ≠ Authority, Connected ≠ Authorised, Executed ≠ Verified, and Unknown = Safe Hold.
Status: patent pending. No patent has been granted, and these descriptions summarise pending applications by Salem Salah bin Omair AlShamsi, not issued claims. Filing details are available on request through the contact form.
Private AI: Client-Sovereign LLM Infrastructure
No client data or operational commands touch third-party commercial cloud APIs. Open-weight foundation models run strictly on customer-controlled high-memory GPU servers with hardware-enforced policy gates.
Evidence Over Claims
Performance, accuracy, concurrency, and cost are benchmarked on actual client workloads before accepting results.
No Unverified Execution
The model can recommend or prepare actions, but policy and authorization gates decide whether a tool or command may execute.
Fail Safely & SAFE HOLD
Ambiguous authorization, stale lease, or failed dependency halts into an explicit SAFE HOLD state with auditable logs rather than executing a guessed action.
Strict Order of Work
1. Prompts & Policy Gates → 2. Verified Retrieval (RAG) → 3. LoRA/QLoRA adapter tuning only where justified. Never pre-train blindly.
Approved internal applications, operator consoles, encrypted telemetry
Mutual TLS, tenant/role access, cryptographic request IDs, rate quotas
Allowlists, compliance rules, human sign-off triggers, SAFE HOLD engine
Qwen3.8-27B dense or Kimi K3 MoE on vLLM/SGLang with strict memory isolation
Vector embeddings with tenant metadata isolation; strict source-citation audit
Idempotent schemas, hard timeouts, schema validation, zero direct DB execution
Tamper-evident run records capturing prompt hashes, tool params, and gate decisions
The 8-Step Sovereign Governance Loop
Autonomous agents must operate inside strict boundaries across every system they touch. No step in the loop proceeds without verified evidence.
Capture agent requests, tool calls, context and system state as they happen.
Fuse signals, map what each agent can reach, and flag anomalies such as injection or drift.
CRITICAL GATE: Validate identity, check crypto signatures, test invariants.
Generate candidate actions or policy interventions for the agent request.
Check compliance rules, human sign-off levels, and multi-signature gates.
Run the approved action atomically through a bounded tool adapter.
Observe telemetry delta, measuring actual vs predicted performance.
Commit cryptographic attestation to immutable audit records.
Unverified claim; strictly rejected at Gate 03.
Telemetry timestamped by originating node.
Traceable schema and cryptographic signature verified.
Automated regression and invariant checks passed.
HSM attestation plus human operator multi-key.
Built for every sovereign AI deployment.
Sovereign states
- Keep data and decisions on national hardware
- Map national law into the authorization gates
- Replay every autonomous act for oversight bodies
Defense & security operators
- Bounded authority across every operational domain
- Hardware-enforced policy gates on all tool calls
- SAFE HOLD instead of guessed actions
Critical infrastructure
- Energy, ports and aviation agents under bounded authority
- Prompt-injection and privilege-escalation containment
- Staged rollout with eight exit gates
Start small. Scale on evidence.
Sizing is indicative and confirmed by benchmarks on your own workload before you buy hardware.
Pilot
- GPU: 1× RTX PRO 6000 Blackwell 96 GB / 1× H100 80 GB
- Memory: 128 GB ECC RAM, 2-4 TB Gen5
- Context: 262k native (ext. to 1M)
- Agent gateway, policy engine and evidence log
- Shadow mode on your live traffic
Enterprise
Most chosen- GPU: 16× H200 (2.26 TB VRAM) or 16× B200 (2.88 TB VRAM)
- Memory: 1-2 TB Server-Grade RAM, 8-16 TB NVMe Fabric
- Context: 1M Token Context
- Everything in Pilot
- Named-approver workflows and exportable evidence
Sovereign
- Fully air-gapped deployment
- Customer-held keys and HSM attestation
- Independent red-team assessment (Gate 7)
- Runbook training for operators and approvers
- Tailored to your regulator
Eight exit gates. Evidence at every one.
A 24-week programme where each phase must pass a measurable gate before the next begins.
Agent & Workload Discovery
Inventory every agent, tool, data store and external destination. Define risk tiers and the security perimeter.
Isolated Runtime Baseline
Provision customer hardware, pin drivers, and benchmark the isolated model runtime on real workloads.
Policy Design & Gateway
Write allowlists, budgets, approval rules and evidence requirements. Deploy the identity-aware gateway in shadow mode.
Knowledge Ingestion (RAG)
Tenant-isolated vector indexing, metadata filters and source-attribution verification.
Technical Video Archive
Recorded hardware testbenches, simulated laser handovers, and live terminal captures of policy gates in action.
The Age of Autonomous AI & Governed Infrastructure
Strategic architectural overview of multi-agent autonomous decision systems, cryptographically enforced boundary gateways, and sovereign intelligence foundations built for mission-critical operations.
The Age of Autonomous AI & Governed Infrastructure
Autonomous Multi-Agent Architecture // Strict Boundary Gates // Zero Trust
UturnU Decision Intelligence & Autonomous Travel Agent
UturnU Autonomous Agent // Multi-Attribute Utility Engine // Live UI
Multi-Domain SSOS Observation & Policy Authorization Cycle
Stage 01 Observe // SSOS Governance Loop // Access Authority Gating
Questions, answered.
It sits between your AI agents and the systems they act on. Each requested action is verified, checked against policy, held for a human when risky, executed through a bounded adapter, and recorded in a tamper-evident log.
What We Don't Claim
Credibility requires stating the boundaries of what the product does and does not do.
Guardrails Reduce Risk, They Do Not Remove It
No control layer can prove an agent will never misbehave. HVT narrows what an agent can do and records what it did. Residual risk remains and must be owned by the operator.
Hardware Sizing Is Indicative, Not a Purchase Guarantee
GPU VRAM requirements (for example 16× B200 for Kimi K3) are derived from parameter math and batch overheads. Final sizing requires benchmarks on your actual workload before you buy hardware.
Models Do Not Replace Deterministic Rules
Open-weight LLMs are probabilistic. In this architecture the model is never the authoritative source for system state, financial balances or safety-critical commands.
Demos Are Modeled, Not Production Telemetry
The interactive simulator on this site uses scripted scenarios to illustrate the control flow. Measured results come from the staged rollout gates on your own infrastructure.
Compliance Mapping Is Not Certification
We map controls to common frameworks to help with evidence gathering. That is not a certification or legal advice. Your auditors and counsel make the final determination.
Talk to our team
Tell us which agents you run and which systems they touch. We will walk you through the control layer, share benchmark profiles under NDA, and scope a pilot.
Stay current on sovereign AI control.
Research notes and test results, when there is something worth sending.