Product System
Strategy → Discovery → Productization → Launch → Scale
Five gates govern when the product may advance. Six decision lenses test whether the evidence is complete.
Hyperion Physical AI Decision Lab
The Decision Foundry is Hyperion’s planned Industrial and Physical AI lab: one reconfigurable environment for testing product value, system boundaries, model behaviour, human authority, failure recovery and the evidence required for the next commitment.
Concept in development
The physical facility is not yet commissioned. Current proof consists of runnable digital demonstrations, measured bench work and Hyperion-owned R&D. Proposed zones and missions below remain illustrative until built, tested and labelled otherwise.
The proposition
A model demonstration asks whether one behaviour can work under chosen conditions. The Decision Foundry asks whether the complete product should advance. Customer value, intelligence, hardware, software, safety, operations and economics are evaluated together. A convincing output is not a pass: the evidence determines whether the decision is proceed, redirect, partner, pause or stop.
One connected system
The Product System governs why and when the product advances. The Physical AI system architecture governs how the system behaves in operation.
Product System
Strategy → Discovery → Productization → Launch → Scale
Five gates govern when the product may advance. Six decision lenses test whether the evidence is complete.
Physical AI runtime
Sense → Connect → Compute → Reason → Act → Orchestrate
Trust, safety and cybersecurity surround every layer.
Evidence return
Incidents, field variance, technical discovery or economics can reopen an earlier decision. Nothing advances automatically.
The visitor mission
Proposed lab zones
Follow one bounded initiative from declared intent to an inspectable decision record. As you move, the architecture resolves around what must be observed, authorized and proved.
Name the intended use, accountable owner, system boundary, acceptance threshold and stop condition before a model is selected.
Output: decision contractObserve the declared baseline, connect field signals to governed knowledge and compare options with sources, uncertainty and operating context visible.
Output: bounded proposalSchema, allow-list, policy and authority checks determine whether a proposal may reach deterministic control. Ambiguity or unsafe intent stops here.
Output: authorization recordRun one bounded action, inject declared variance, watch operator and system response, and prove that degradation, stop and rollback paths work.
Output: observed system behaviourCompare the result with acceptance and kill thresholds. Record the evidence, open assumptions and a proceed, redirect, partner, pause or stop recommendation.
Output: Product System gate recordIllustrative architecture
Change one condition. The model may interpret and propose; the system boundary determines what happens next.
Mistral-first. System-bounded.
Hyperion selects Mistral first for language, multimodal understanding, speech, retrieval and model adaptation, then tests the choice against the task, deployment boundary, licence, region, latency, cost and evaluation set. The least-complex sufficient answer may still be rules, search, a smaller open-weight model, another model or no LLM.
Available capability
Selected Ministral and Voxtral models can interpret bounded image, language, audio and operator input at the edge or through managed endpoints.
Available capability
OCR, embeddings, retrieval and Search Toolkit connect documents, incidents and technical knowledge to inspectable sources. OCR remains document understanding—not a safety-critical decision-maker.
Available capability
Structured generation compares options, exposes uncertainty and requests allow-listed tools. Function execution remains the developer’s responsibility.
Public preview
MCP Connectors and durable Workflows can coordinate tools, data and human checkpoints. Preview interfaces require evaluation and change control before production use.
Evidence-gated
Prompting and RAG come first. Fine-tuning, distillation, custom SLMs or Forge follow only when a versioned evaluation set proves the need and lifecycle burden.
Configuration-dependent
Managed API, an explicitly configured regional endpoint or customer-controlled open-weight inference may be selected when model availability, licence, residency and infrastructure permit it.
No direct model-to-machine path
In the Foundry architecture, no Mistral response is a direct PLC, robot, charger or vehicle command. A proposal must pass schema validation, a typed allow-list, policy and authority checks, and deterministic control. An independent safety function may reject or stop the action and remains outside model authority.
Access-dependent exploration
Robostral Navigate and Mistral’s physical-world research are exploration tracks—not current Hyperion integrations. They remain experimental until access, licence, hardware, safety review and measured results are established.
Hyperion Consulting is independent from Mistral AI. References to Mistral models and services do not imply endorsement, sponsorship, certification, reseller status, partnership or special access. Provider nationality alone does not establish data residency, sovereignty or regulatory compliance.
Verify in official Mistral documentation
First mission packs
Each mission begins as planned and illustrative. It becomes measured only when the reference cell exists, the protocol is published and the result is reproducible.
Read machine state and a governed maintenance corpus, show supporting passages, state uncertainty and propose a bounded work order—without autonomously diagnosing equipment or issuing control commands.
Planned · illustrative until commissioned
Give the system an ambiguous or unsafe instruction. Intelligence may propose or abstain; typed interfaces, policy authority and independent safety determine whether anything can reach the controller.
Planned · illustrative until commissioned
Disconnect external connectivity and observe local inference, cached knowledge and deterministic fallback against declared degraded-mode requirements.
Planned · illustrative until commissioned
Challenge perception and learned behaviour with glare, occlusion, unfamiliar parts, drift and workstation variation to expose—not hide—the validated boundary.
Planned · illustrative until commissioned
Test a revision in simulation, release it to one controlled asset, expand only while acceptance thresholds hold and roll back when they do not.
Planned · illustrative until commissioned
Industry mission packs
The first three align with Hyperion’s published industry priorities. Smart infrastructure, logistics and defence are research contexts; publication does not imply sector client delivery.
Primary
Inspection, manipulation, cycle time, operator intervention, degraded modes and repeatable line deployment.
Primary
In-vehicle, edge and cloud boundaries; lost connectivity; staged OTA change; fleet observability and rollback.
Primary
Local autonomy, asset and fleet coordination, offline operation, incident recovery and cost to serve.
Research
Distributed sensing, multi-owner authority, privacy, cybersecurity, continuity and public-service constraints.
Research
Exceptions, human handover, mixed fleets, site variance, utilisation and repeatable deployment.
Research · bounded
Unclassified, non-kinetic and non-targeting missions using public or synthetic data. No weapons targeting or autonomous lethal decisions.
Evidence Passport
A demonstration is useful only when a buyer can tell what happened, under which conditions and what the result does not prove.
The record travels with the result
Question · intended use · data origin and rights · model, prompt, tool, firmware and dataset revisions · operating conditions · authority boundary · acceptance and kill thresholds · expected and observed result · failures · limitations · reproduction date · what the run does not prove
JARVIS · Lab OS
JARVIS lets a visitor observe system state, stress a bounded scenario, compare decisions and explain the result against cited evidence. It may synthesize and propose; it cannot waive an acceptance threshold, certify a system or authorize unsafe physical action.
Ask JARVIS about the FoundryAvailable now
These are current digital, bench and internal-R&D artefacts—not the planned physical facility. Each page states what it can and cannot prove.
One-image automation and safety observations; not a site audit, engineering assessment or certification.
Run the demonstrationA model describes what an industrial inspection layer might flag; not a validated defect detector or production-quality measurement.
Run the demonstrationSource-grounded general information about the EU AI Act; not legal advice or a conformity assessment.
Run the demonstrationA self-assessment across data, sensors, connectivity, ML readiness and governance; not an audit of your systems or a validated maturity benchmark.
Run the demonstrationA first-pass payback period and 3-year range from six inputs; not a quotation, a vendor recommendation or an engineering estimate.
Run the demonstrationA model reads a sensor CSV and drafts plausible anomalies and a schedule; not a trained maintenance model or a basis for maintenance decisions.
Run the demonstrationMeasured on the bench
AMD Ryzen AI Max+ 395 (Strix Halo) · 128 GB LPDDR5X-8000 unified memory · medians of three runs after a discarded warm-up · no tuning
qwen3:30b-a3b — 82.3 t/s · gpt-oss:20b — 38.6 t/s · devstral:latest — 14 t/s · mistral-small:latest — 13.8 t/s. These are configuration-bound observations, not a standardised benchmark or performance guarantee.
Read the complete field notesReachy Mini + SO-101
Measured · simulated · dry-run. Real sensing and teleoperation evidence stays separate from simulated autonomy and unexecuted robot actions.
Inspect the robotics evidenceAuralink
Pre-production · Hyperion-owned R&D. An inspectable reference implementation—not a client deployment or commercial-outcome claim.
How the complete system works
Select a stage to follow the system end to end.
01 / 08Device & Control
Sensors & environment. The physical world, sensed — cameras, depth, radar and OT signals.
See how we engineer this02 / 08Embedded Platform
Embedded platform. A real-time, deterministic, securely-updatable edge runtime.
See how we engineer this03 / 08Perception & Robotics
Perception. Mapping, detection and world-state resolved on-device.
See how we engineer this04 / 08Intelligence & Knowledge
Intelligence. Open-weight models and VLM/VLA policies propose an action.
See how we engineer this05 / 08Device & Control
Deterministic control. A deterministic controller turns a proposal into a precise command.
See how we engineer this06 / 08Trust, Safety & Cybersecurity
Safety & cybersecurity. An independent boundary accepts or blocks every command.
See how we engineer this07 / 08Perception & Robotics
Physical action. The validated command drives the machine in the real world.
See how we engineer this08 / 08Orchestration & Operations
Operations & fleet. Telemetry returns to operations; the system improves across a fleet.
See how we engineer thisOwned R&D portfolio
Hyperion-owned ventures at different maturity levels keep product, architecture and evidence questions concrete. Maturity labels are explicit; none is presented as a client deployment.
The coordination plane for physical AI
Exercises: IntegrationReliability
AI-Powered Product Management Intelligence
Exercises: ArchitectureIntegration
AI-Powered VC Intelligence
Exercises: DataArchitecture
Vehicle Intelligence Platform
Exercises: IntegrationArchitecture
Creative AI Super-Assistant
Exercises: ArchitectureIntegration
The Regulatory Shield
Exercises: GovernanceData
AI-Powered Business OS
Exercises: ArchitectureData
Static Analysis for AI-Generated Code
Exercises: GovernanceReliability
AI Adoption Copilot for European SMEs
Exercises: GovernanceData
AI-Powered Enterprise Transformation Intelligence
Exercises: GovernanceArchitecture
Decision instruments
The Foundry uses the same canonical Product System, architecture and decision tools as an engagement.
The system architecture from sensing to operations, surrounded by trust and safety.
Map deployment constraints to a hardware platform class.
A first-pass economics model for a robotics cell.
Test the system across architecture, data, operations and governance.
Inspect curated robot apps, datasets, policies and agents from the open ecosystem.
Commercial path
The Decision Foundry is an environment used inside Hyperion’s three existing mandates—not a fourth service category.
Make one consequential product decision with evidence. Receive an executive decision memorandum, evidence and risk map, and a prioritised 90-day plan.
Lead one Physical AI product from its current state to the next named evidence gate, with agreed artefacts, acceptance evidence and handover.
Embed fractional CPO or Head of Product leadership across product direction, architecture decisions, operating cadence and capability transfer.
Decision Foundry questions
No. The physical facility is in concept development and is not commissioned. Current digital demonstrations, measured bench work and Hyperion-owned R&D are labelled separately.
No partnership or special access is claimed. Hyperion is an independent, Mistral-first consultancy and verifies model, licence, regional and deployment fit for each implementation.
No. Model outputs are proposals that must cross schema, allow-list, policy and authority checks before deterministic control. Independent safety remains outside model authority.
No. It does not replace legal, safety, cybersecurity, conformity-assessment or certification specialists. It creates product and architecture evidence for a bounded decision.
A bounded decision record: observed evidence, unresolved assumptions, limitations and a proceed, redirect, partner, pause or stop recommendation.
Manufacturing, automotive and energy are primary contexts. Smart infrastructure, logistics and defence are explicitly labelled research contexts; publication does not imply sector client delivery.
Bring one stuck initiative
In a 30-minute fit call, Mohammed will identify the decision, the missing evidence and whether a Foundry mission or one of Hyperion’s three mandates is appropriate—or say plainly that it is not.
30 minutes · no obligation · Mohammed leads every conversation