August 2026: EU AI Act enforcement begins for high-risk AI in manufacturing. The preparation window is now.
Sovereign Agentic Infrastructure

Industrial AI — compliant and
in control of your data

European manufacturers can now deploy AI agents directly on their machines — without surrendering production data to cloud providers, and fully aligned with the EU AI Act.

Get Started → See It Running
🎓 Robotics research, ETH Zürich
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🏭 35 years of industrial software engineering in DACH
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🤖 Cyber-physical proof of concept running today
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⚖️ Built for EU AI Act by architecture, not retrofit

Three forces your factory can't ignore

European manufacturers are caught between two unacceptable choices: adopt AI and lose control of your production data to US cloud providers — or stay cautious and fall behind. Meanwhile, a regulatory deadline arrives in August 2026 regardless of which choice you make. There is a third way.
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The Regulatory Wall

August 2026: EU AI Act enforcement begins. Autonomous AI on production machinery is classified as high-risk. Without audit trails, human oversight logs, and governance documentation, companies face fines up to €30M or 6% of global turnover. Cloud AI systems cannot produce these by design — they are black boxes.

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The Data Sovereignty Gap

Your production IP is your competitive edge. When AI runs in the cloud, machine parameters, process data, and supplier relationships leave your perimeter — often used to train models that serve your competitors. GDPR exposure is one incident away. Operational risk is continuous.

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The Coordination Bottleneck

Scaling from one AI agent to ten is where projects break. Without a coordination layer, agents diverge, repeat work, lose context, and produce inconsistent outputs. Most engineering teams have never built multi-agent systems — and the tooling to help them is only now emerging.

Three layers. One sovereign stack.

Everything runs inside your perimeter. Your data never leaves. Every action is logged and auditable.

In plain terms — what you get

🖥️

Software that runs on your existing server

No specialised hardware required. The Agentegra stack installs on a standard on-premise machine — the same kind your IT team already manages.

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Your data never leaves your building

The AI model runs locally. Production parameters, process data, and supplier information stay inside your network — no cloud call required for the AI to make a decision.

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An audit trail that satisfies the EU AI Act

Every agent action is logged with a timestamp, an input, an output, and a human reviewer. The compliance documentation generates itself — your quality team does not have to build it manually.

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A connection to the outside world — on your terms

When an external system needs to reach your machine — a procurement platform, an ERP, an AI agent from a supplier — it goes through a single controlled gateway. Your internal systems are never directly exposed.

Layer 1 — On-Premise Execution

The Local Machine

Where compliance is born

A standalone agent that runs entirely on your hardware — no cloud dependency, no external calls. It receives a task, executes it using a local AI model, logs every step with a timestamp and reviewer, and completes it independently. EU AI Act compliance is built into the architecture, not bolted on.

  • Local AI inference — Mistral or Apertus 7B (ETH/EPFL), no data leaves your network
  • Full audit trail: every action logged with timestamp and human reviewer
  • Governance documentation generated automatically
  • No per-task cloud approval required — operates autonomously within policy
  • Proven in production — running on Robot Ross today
Layer 2 — Connectivity

The Cloud Bridge

Connect to the world without opening your vault

A protocol-agnostic API that connects your on-premise fleet to any external system or agent network — without exposing internal data. It normalises orders from any agent commerce standard and routes them to your local execution layer. The outside world talks to the bridge; your data never crosses it.

  • Supports all emerging standards: Virtuals ACP, MCP, Google AP2, A2A
  • Human and AI requesters treated identically — same pipeline
  • Every transaction logged for EU AI Act compliance
  • Live now: api.robotross.art accepting orders
Layer 3 — Deployment & Continuity

Your Team Stays in Control

Your engineers know your machines, your tolerances, and your processes. They do not need to become AI specialists — they need the right tools to direct AI agents effectively. Flotilla is the coordination layer we deploy alongside the stack: it handles scheduling, agent communication, and compliance logging automatically, so your team focuses on the domain decisions only they can make.

  • No retraining required — your engineers direct agents in plain language; the system handles the orchestration
  • Always on — agents run 24/7 with a built-in heartbeat; no one needs to babysit the process
  • Human sign-off built in — decisions above a configurable risk threshold require human approval before execution
  • Audit trail automatic — every agent action attributed, reviewed, and timestamped without extra work from your team
  • Secrets never in code — credentials managed by Infisical (EU), zero exposure risk

What changes for your team

Engineer manually triggers each step Agent fleet executes in parallel, engineer reviews outcomes
Compliance docs written after the fact Audit trail generated automatically at every step
Process stops when no one is watching Continuous operation, alerts sent if human input needed
AI output trusted without verification Cross-check built in — agents review each other before acting
The practical result: Your engineers spend their time on the decisions only they can make — tolerances, exceptions, supplier relationships. The coordination, logging, and compliance documentation happen automatically underneath.

Robot Ross — the stack running live

Not a demo environment. A working cyber-physical system fulfilling real orders, on real hardware, with local AI.

Watch Robot Ross in action YouTube → @RobotRoss

A Huenit robot arm draws SVG artwork narrated by a local AI in Bob Ross's voice — using Mistral TTS / Kokomo voice synthesis, running entirely on-premise. Orders arrive from human buyers via Shopify and from AI agents via the Cloud Bridge API. The system is commerce-blind: same pipeline, same compliance log, regardless of who ordered.

11k+ views in 48h on r/MistralAI
458 GitHub commits — sustained effort
36★ GitHub stars, niche infra project
>40% European audience — sovereign AI resonates in DACH & France

Community Traction

"This is such a fun demo… different specialists that fetch from a vault — this is how multi-agent systems should be built." — r/MistralAI community, #1 all-time post for this project
View the r/MistralAI thread →

What this proves for industrial customers

  • Local AI inference on commodity hardware — no specialised GPU required
  • Voice-enabled agent narrating every action — human-readable audit in real time
  • Physical hardware control via agent API — the same pattern scales to CNC, conveyor, inspection
  • Sovereign by design: Shopify orders and agent orders go through the same local compliance layer
Robot Ross details GitHub →

Three ways to engage

Whether you are an investor, an industrial customer, or a potential partner — here is exactly what each engagement looks like.

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Factory Pilot

Entry via a consulting engagement (CHF 15–30k). At the end of the pilot you have a working agent deployed on one production process — with a full audit trail, a documented compliance record, and a clear picture of where to expand next. Your team runs it; we support it.

What 90 days looks like Weeks 1–3: map one target process, define scope and compliance requirements.
Weeks 4–8: deploy Local Machine on your hardware, integrate with one data source.
Weeks 9–12: run live with human oversight, generate first EU AI Act audit report.
Start a Pilot →
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System Integration Partnership

Industrial software vendors and system integrators with DACH customer relationships — let's discuss distribution. A commercial co-founder is also welcome: the first customers come from a 35-year DACH engineering network. The right partner scales what is already working.

Partnership Inquiry →