Auralink: A Physical AI Research Reference Architecture
Auralink is a Hyperion-authored Physical AI research agentic software system for EV-charging infrastructure — a safety-relevant, standards-governed domain. It has been evaluated in simulation and bounded environments; it is documented only within its published research boundary. This page uses it as architecture and safety evidence, not as certification, a client engagement or proof of production deployment.
Last reviewed: June 2026
Contents
Auralink is a Hyperion-authored Physical AI research agentic software system for EV-charging infrastructure, built by Hyperion's founder. Its charger OS is aligned to ISO 15118-20 and OCPP. Its implemented architecture provides an inspectable reference for edge-first operation, explicit service boundaries and bounded agent authority. Evaluation is limited to simulation and bounded environments; Auralink is documented within a controlled research boundary. This is engineering evidence, not certification.
The Reference Thesis: A Full-System research architecture in a Safety-Relevant Domain
Most discussion of agentic AI lives in isolated demos and benchmarks. Auralink is different in a narrower, verifiable way: it is a Hyperion-authored research reference for EV-charging infrastructure, evaluated in simulation and bounded environments and documented within a controlled research boundary. That makes it useful for inspecting architecture decisions while keeping its evidence boundary explicit.
The thesis of this page is narrow and deliberate. Auralink is presented as a reference architecture — a worked example of how to architect Physical AI for a standards-governed physical domain — and as safety and architecture evidence. It is not presented as a speed story, a velocity metric, a customer case study or evidence of private repository scale.
Two properties make the reference credible. First, sovereignty: Auralink runs on infrastructure the operator owns, with no mandatory external cloud dependency in the control path. Second, edge-first operation: it is designed to keep working when connectivity is degraded or absent. In a physical domain, both are safety-relevant architectural choices, not deployment conveniences.
One honesty note, stated up front and again below: Auralink is a Hyperion-authored research reference. It is used here to inspect architecture and safety decisions. It is not an external client engagement, and no external client names or results are claimed anywhere on this page.
What Makes Auralink a Useful Reference
Physical AI research reference system
An implemented architecture for physical charging infrastructure, evaluated in simulation and bounded environments and documented within a controlled research boundary.
Standards-governed domain
EV charging is safety-relevant and governed by ISO 15118-20 and OCPP.
Sovereign infrastructure
Runs on infrastructure the operator owns; no mandatory external cloud in the control path.
Edge-first / offline-capable
Designed to keep operating under degraded or absent connectivity.
Architecture: Edge-First, First-Party Services, Agents
Auralink's architecture is a fan-out of small, independently deployable units running at the edge, with an agentic layer that reasons over them inside a bounded envelope. The descriptions below explain architectural surface area and depth without publishing private inventory.
On the agentic layer: the agents assist operation — they sense, reason, and arbitrate actions within bounded authority. The engineering team designs, reviews, and owns the system. The agents do not unilaterally build or ship it; they act inside an envelope the architecture defines.
Implemented research architecture
Implementation statusThe reference implements edge-first decomposition, explicit interfaces and an enforced separation between agent reasoning and deterministic controls. Private repository inventory is deliberately excluded from this public evidence.
First-Party Services
Architecture patternThe system is decomposed into first-party services. This is a fan-out architecture: small, independently deployable units with narrow responsibilities, communicating over well-defined contracts. The service boundary is what makes the system observable, individually testable, and recoverable at the unit level.
Autonomous AI Agents
Agentic layerAI agents operate within Auralink. The agents assist operation — sensing, reasoning over telemetry, proposing and arbitrating actions within bounded authority. They do not unilaterally build or ship the system; the engineering team designs, reviews, and owns it. The agents act inside an envelope that the architecture, not the agent, defines.
Edge-First, Offline-Capable Operation
Edge-firstAuralink is edge-deployed: it runs at or near the charging infrastructure it governs, and it is designed to keep operating when external connectivity is degraded or absent. Edge-first is not a deployment convenience — in a standards-governed physical domain it is a safety and continuity property. The system does not depend on a round-trip to a distant cloud to make local decisions.
Mapping to the Physical AI system architecture: Sense → Orchestrate
Hyperion frames Physical AI as six verbs: Sense · Connect · Compute · Reason · Act · Orchestrate. Auralink maps cleanly onto each layer — which is precisely why it works as a reference. The mapping below shows how an edge-first, agentic system for a standards-governed domain populates the stack.
Sense
Telemetry from charging hardware, power electronics, session state, and environmental signals is acquired at the edge. In a standards-governed domain, the sensing layer is also where conformance-relevant signals (session negotiation state, fault flags) are captured for downstream reasoning and audit.
Connect
Devices and services interoperate over open protocols. Auralink's charger OS is aligned to OCPP (Open Charge Point Protocol) for charge-point communication and to ISO 15118-20 for vehicle-to-infrastructure session negotiation. Connectivity is built around the open standards the domain mandates, not a proprietary bus.
Compute
Computation runs on infrastructure the operator owns, at the edge. The decomposition into first-party services is the compute substrate: workloads are placed close to the hardware they serve, with no mandatory dependency on an external cloud control plane to execute local logic.
Reason
The agentic layer reasons over sensed state — diagnosing conditions, proposing actions, and arbitrating between competing objectives within bounded authority. Reasoning is constrained by explicit policy; the agents operate inside an envelope defined by the system architecture and the relevant standards, not outside it.
Act
Actions reach physical charging infrastructure through controlled interfaces. As with any safety-relevant physical system, the actuation path is where bounding and enforcement matter most: action authority is scoped, and protocol-level constraints (ISO 15118-20 / OCPP) frame what the system is permitted to command.
Orchestrate
Across edge sites, services and agents, an orchestration layer coordinates lifecycle, deployment, versioning and recovery. Orchestration turns distributed units into a coherent, operable system that can be reasoned about, updated and rolled back as a whole.
Standards & Safety: ISO 15118-20, OCPP, and an Enforced Envelope
EV charging is a standards-governed domain. Auralink's charger OS is aligned to ISO 15118-20 and OCPP, and the agentic layer operates inside a bounded envelope defined by the architecture and those standards. Building on open, documented contracts is what makes a system in this domain auditable — and what makes a later safety argument tractable.
Important boundary: a notified body assigns any safety rating. The material on this page is engineering evidence describing how the system is architected for a standards-governed domain — it is not a certification, and it does not assert one. For the engagement that assembles a safety argument, see Hyperion's Safety-Case & Certification.
ISO 15118-20
Road vehicles — Vehicle to grid communication interface — Part 20
ISO 15118-20 specifies the second-generation application and presentation layer for communication between an electric vehicle and the charging infrastructure, including session negotiation, secure communication, and bidirectional power transfer scenarios. It is the standard that governs how a charger and a vehicle establish and run a charging session.
In Auralink
Auralink's charger OS is aligned to ISO 15118-20 at the session layer. For a reference architecture, the relevant point is structural: the system is designed so that vehicle-to-infrastructure negotiation conforms to the governing standard rather than to an ad-hoc protocol.
OCPP
Open Charge Point Protocol
OCPP is the open, vendor-neutral protocol for communication between charge points and a central management system. It is the de facto interoperability standard for EV-charging networks, covering transactions, configuration, firmware management, and diagnostics across heterogeneous hardware.
In Auralink
Auralink's charger OS is aligned to OCPP. Building on OCPP keeps the architecture interoperable and auditable: the management-plane behaviour follows a documented open contract, which is a precondition for any later conformance or safety-case work.
How an Edge-Agentic System Is Architected for a Standards-Governed Domain
Autonomy Operates Inside an Enforced Envelope
The agentic layer reasons and proposes within bounded authority. The boundaries — what the system is permitted to command, under which conditions — are defined by the architecture and the governing standards, not by the agents themselves. This separation is the architectural pattern that makes an agentic system defensible in a safety-relevant domain.
Open Standards as the Conformance Substrate
Aligning the charger OS to ISO 15118-20 and OCPP means the externally observable behaviour follows documented, auditable contracts. A safety case is far easier to construct on top of standard-conforming interfaces than on top of proprietary, undocumented ones.
Edge-First for Continuity and Local Determinism
Because Auralink runs at the edge and is offline-capable, local decisions do not depend on a distant cloud round-trip. In a physical domain, the ability to keep operating safely under degraded connectivity is itself a safety-relevant architectural property.
Sovereign Infrastructure: the Operator Owns the Substrate
Auralink runs on infrastructure the operator owns. There is no mandatory external cloud dependency in the control path. Sovereignty here is not a marketing posture — it is an architecture choice that keeps the operator in control of the system that governs their physical assets.
Evidence
The evidence below is presented honestly and in context. The research result comes from a public technical preprint and a controlled-environment evaluation, not a field deployment or refereed paper. The remaining evidence concerns implemented architecture, not private inventory or build speed.
Controlled-environment research preprint 2603.08736, "Autonomous Edge-Deployed AI Agents for EV Charging Infrastructure" (February 2026). This is a preprint — neither refereed nor formally published.
Autonomous Incident-Resolution Research — from the arXiv Preprint (2603.08736)
The founder's public technical preprint arXiv 2603.08736, "Autonomous Edge-Deployed AI Agents for EV Charging Infrastructure" (February 2026), reports an autonomous incident-resolution evaluation in a controlled environment. This is a preprint — not a refereed or formally published paper — and the result is not field or commercial evidence.
Implemented Architecture Patterns
The reference shows that the patterns described on this page — edge-first decomposition, an agentic layer inside an enforced envelope and standard-aligned interfaces — are implemented in a research system. This does not establish deployment, performance, private repository scale or delivery speed.
A Standards-Governed Domain, by Construction
EV-charging infrastructure is a safety-relevant, standards-governed domain. The relevant evidence is not a single benchmark but the fact that the architecture was built to operate inside that domain's constraints — ISO 15118-20 and OCPP alignment, edge-first operation, and bounded agent authority — rather than retrofitted to them.
What This Is — and What It Is Not
Auralink is a Hyperion-authored Physical AI research reference. On this page it is used as architecture and safety evidence for a standards-governed, safety-relevant domain. It is evaluated in simulation and bounded environments and is documented within a controlled research boundary.
It is not an external client engagement, and no external client names, logos or results are claimed anywhere on this page. The bounded research described here comes from a controlled-environment evaluation reported in arXiv preprint 2603.08736; private inventory is not published.
The reported result is from a preprint, not a refereed publication. And to restate the standards boundary: a notified body assigns any safety rating — the material here is engineering evidence, not certification.
Frequently Asked Questions
Is Auralink an external client project?
No. Auralink is Hyperion-authored, documented research. It is presented as an architecture and safety reference evaluated in simulation and bounded environments within a controlled research boundary. It is not an external client engagement, and no external client names or results are claimed here.
What standards apply to Auralink?
Auralink operates in EV-charging infrastructure, a standards-governed domain. Its charger OS is aligned to ISO 15118-20 (vehicle-to-infrastructure communication, including session negotiation) and to OCPP (Open Charge Point Protocol, the open charge-point management protocol). These open standards are the interoperability and conformance substrate the architecture is built on.
Can you build this for my safety-critical system?
The relevant Hyperion engagements are Physical AI Deployment (edge-first architecture, agentic layers, and integration for physical systems) and Safety-Case & Certification support (assembling the engineering evidence a safety argument requires). The right starting point is a conversation about your domain, its governing standards, and where an edge-deployed system fits. See /services/physical-ai-deployment and /services/safety-case-certification.
Is the reported research result peer-reviewed?
No. The autonomous incident-resolution research comes from a controlled-environment evaluation reported in the founder's public technical preprint arXiv 2603.08736, "Autonomous Edge-Deployed AI Agents for EV Charging Infrastructure" (February 2026). It is not a refereed paper, field result or commercial outcome.
Sources and References
Cherifi, M. (2026). "Autonomous Edge-Deployed AI Agents for EV Charging Infrastructure." https://arxiv.org/abs/2603.08736
Context: Public technical preprint arXiv 2603.08736 (February 2026). The founder's preprint reports autonomous incident-resolution research in a controlled-environment evaluation; it is not refereed, field evidence or a commercial outcome.
ISO (2022). "ISO 15118-20: Road vehicles — Vehicle to grid communication interface — Part 20."
Context: International standard specifying the second-generation application and presentation layer for EV-to-infrastructure communication, including session negotiation, secure communication, and bidirectional power transfer.
Open Charge Alliance (2024). "OCPP — Open Charge Point Protocol."
Context: Open, vendor-neutral protocol for communication between EV charge points and a central management system. The de facto interoperability standard for EV-charging networks.
Discuss Your Safety-Critical System
If you are building Physical AI for a safety-relevant, standards-governed domain — and you want the architecture to stand up to scrutiny — start with a conversation. Hyperion brings research architecture and evaluation experience from Auralink, alongside the founder's production engineering career, and works with your team on deployment decisions and the evidence a safety case requires.
Fractional CPO and Interim Head of Product
Mohammed Cherifi is the founder of Hyperion Consulting and the founder of Auralink, an edge-deployed agentic system for EV-charging infrastructure. With long-standing experience in automotive and embedded systems engineering, he specialises in Physical AI deployment for safety-relevant, standards-governed domains.
Related Resources
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