Operator · Fleet operator · Public sector

Air-Gapped AI Demo login

AI fault analysis for your charging network — on your own model, inside your own network. The logs never leave the building.

Evaluate in your own data center: Pipelet as a signed container bundle (Helm or single-node appliance), the AI model on an NVIDIA DGX Spark next to it. No outbound internet required — we support the setup, remotely if you wish.

☁ Cloud / Internet
no outbound · no cloud LLM
Customer network — air-gapped
Charge pointsOCPP 1.6 / 2.x
Broker / Serverlogs · sessions
Postgres+ pgvector · RAG
AI Co-operatorsnapshot · rules
NVIDIA DGX SparkGemma · Embeddings
likely_cause · severity · next_steps · sources[]

Other charging portals send your OCPP logs and operational data to a third-party cloud for fault analysis. Pipelet does the opposite: the **AI Co-operator** analyses right at the OCPP log and the database — and you decide **which model** does it.

In the independent variant everything runs **entirely inside your network**: charge points → broker/server → Postgres → AI Co-operator → a **self-hosted Gemma model on an NVIDIA DGX Spark**. No cloud vendor, no outbound internet, no data sharing — not even with Pipelet.

Still want the cloud? The same code uses the Claude API. Want no LLM at all? The deterministic rule catalog is enough. One code base, three providers — switchable per install via config.

For inspection bodies, public authorities, bus and truck depots and large fleets that won't negotiate on data sovereignty: that's exactly what Air-Gapped AI is built for.

What to expect

Swappable AI provider

One code base, three providers, chosen by config: **self-hosted Gemma** (your DGX Spark) · **Claude API** (cloud) · **rule catalog** (no LLM). No vendor lock-in to a single AI model.

Data stays in your network

OCPP logs, session data and support cases are analysed locally — no outbound internet, no transfer to a model vendor or to Pipelet. Data sovereignty for GDPR and public-sector requirements.

Learns from your own history

Instead of model training: RAG over your own wallbox and support history (pgvector, no new infra). Every diagnosis **cites** the matching past case — fresh, evidenced, trustworthy. Personalised without training.

Runs on your hardware

Pipelet as a signed container bundle (Helm or single-node appliance), the model on an **NVIDIA DGX Spark** next to it. From an edge-box depot to your own data center — same software, same AI.

Common scenarios

1

Inspection body / public authority

Data sovereignty is non-negotiable: no charging or operational data may leave the building. Air-Gapped AI still gives operators AI fault analysis — entirely local, auditable, cloud-free.

2

Bus & truck depot

The depot must charge 24/7, even when the WAN link drops. Fault analysis keeps running on the on-site DGX Spark — no cloud LLM that's unreachable at night blocks the fix.

3

Large fleet operator

Call-center co-pilot: for every incident the agent sees raw data, a cited likely-cause and one-click actions (Reset · TriggerMessage · Session-Stop). Faster first-fix, fewer technician dispatches.

How Air-Gapped AI fits into the suite

Frequently asked questions

Is Pipelet available as source code?
Yes. Every module is available as a source-access package — complete with Docker Compose, documentation and an SLA support channel. You can audit, customize and self-host.
Which OCPP versions are supported?
Full OCPP 1.6 and 2.0.1 including Security Profiles, Smart Charging, and ISO 15118 Plug & Charge.
Can I use individual modules only?
Yes. Every module is standalone — you can deploy e.g. just the OCPP Broker as infrastructure and build your own CPMS on top.
What does onboarding look like?
We start with a 30-minute call to scope requirements. After that you get a concrete proposal with modules, timeline and price. Pilot typically live in 4–8 weeks.

Sounds like a fit?

Evaluate in your own data center: Pipelet as a signed container bundle (Helm or single-node appliance), the AI model on an NVIDIA DGX Spark next to it. No outbound internet required — we support the setup, remotely if you wish.

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