Hanseatic Alliance for Networked Sovereign Architecture
H.A.N.S.A. Institute is an independent research institute building a sovereign, auditable AI inference network from hardware Europe already owns — so access to AI doesn't depend on a handful of hyperscale datacenters, and your data never leaves the jurisdiction you choose. Public benefit first.
The dominant paradigm is "bigger model, bigger datacenter." That concentrates cost, control, and energy in a few hands. We think the next decade of useful AI — chains of small, fast, specialized tasks — belongs on hardware people already own.
Access to AI runs through a small number of centralized providers. When one goes down, changes terms, or restricts a region, everyone downstream is stuck.
GDPR and the AI Act demand inference that is auditable and jurisdiction-bound. Our network enforces geographic boundaries at the routing layer — country, EU, or world, by design.
The "more datacenters" answer carries a real energy and hardware footprint — while billions of capable consumer GPUs sit idle most of the day. Using what exists is cheaper for everyone, too.
The institute exists to keep these commitments true as the network grows — even where they'd be inconvenient for a purely commercial operator.
One-command install. No accounts, no API keys, no usage bills. If you have a gaming PC or an Apple Silicon machine, you can run and serve real models today.
A network owned by its participants, not a platform. Earn contribution credit for the compute you share, spend it when you need more — geo-scoped to rules you choose.
Push inference to the edge — homes, labs, small operators — and study what becomes possible when compute is distributed instead of centralized.
Use hardware that already exists, run it cooler, and waste less. Lower energy per inference and longer hardware life are first-class goals, not afterthoughts.
The same swarm that shares compute can carry verified, signed security updates to homelabs and small operators — keeping edge AI safe as the field moves fast, without needing a corporate IT department behind you.
Most "is it safe?" confusion disappears once the deployment tier is named. We publish our threat model and never let marketing outrun the architecture.
| Tier | What it is | Confidentiality today |
|---|---|---|
| Local | One machine, fully offline. One command starts a private, OpenAI-compatible endpoint. | Full Exactly as private as your own machine — because it is your own machine. |
| Private swarm | Nodes owned by one organisation — yours or ours under contract — behind your own boundary. | High Determined by your physical and network control, as with any on-premise system. |
| Public swarm | Community nodes matched by the coordinator under each node's geo policy. | Anonymized & PII-stripped A privacy layer rolling out through the alpha: requests travel via relay (the serving node never learns who asked) and are stripped of names, credentials, and identifiers on your own machine before they leave it. Worst case with a malicious operator: an anonymous prompt with the sensitive parts already removed. Node validation and confidential execution follow on the funded roadmap. |
H.A.N.S.A. stands for Hanseatic Alliance for Networked Sovereign Architecture — and the medieval reference is deliberate.
From the 12th to the 17th century, the Hanseatic League — the Hansa — linked merchant cities across the North and Baltic seas: Lübeck, Hamburg, Gdańsk, Bergen, Riga and nearly two hundred more. It had no king, no capital, no state behind it. Every city kept its own laws and stayed fully sovereign — yet together they ran the most reliable trade network in Europe, built on shared routes, common rules, mutual protection, and reciprocity: you carried goods for the network, and the network carried for you.
That is the exact shape of the network we're building. Every node stays sovereign — your hardware, your rules, your geographic boundary. The coordinator is a rulebook, not a ruler: it matches compatible peers and enforces each node's policy, but is designed never to touch the inference traffic itself. What the Hansa proved with ships and kontors, we're rebuilding with GPUs and encrypted streams: coordination without central control.
Combining smaller models can rival or beat single large ones — Mixture of Agents, self-consistency, speculative ensembling. The research exists; what's missing is a real-world substrate to run it at scale. The institute builds and stewards that substrate.
For agentic workloads — many small, fast, specialized calls — a single monolithic model call is like using a freight train to deliver a letter. Intelligent routing of the right small model to the nearest capable node is both cheaper and a genuinely open research question with no public testbed today.
H.A.N.S.A. turns distributed nodes into a unified inference fabric and exposes the knobs researchers need: ensemble methods, task-aware dispatch, latency-aware peer ranking, and opt-in anonymized telemetry to study it all honestly.
During long agentic runs, local silicon accumulates heat. With funding, the network will monitor each node's GPU temperature in real time and shift tasks to cooler peers when a node runs hot — designed to lower sustained operating temperature, reduce electricity consumed per inference, and extend hardware lifespan by years. Participation pays back in hardware health, and the energy savings become a measurable public benefit.
The coordinator handles discovery and geo-policy only — it is designed to stay completely off the inference data path. Want the full technical walkthrough and the install? See the network page →
One command detects your GPU and starts a private, OpenAI-compatible endpoint. Works fully offline. No accounts.
Choose your geo scope — country, EU, or world. The coordinator matches you with compatible peers under your policy.
Offer idle compute, draw on the network when you need more. Designed so the coordinator never sees inference data.
The same batch-splitting primitive that distributes work also enables multi-model ensemble research at network scale.
MVP demo in weeks. Community alpha by Q3. Research program and seed by Q4.
Grant reviewers fund people. Here's the person behind H.A.N.S.A. — and what we'll build the team into with funding.
Founder. Four years at McKinsey & Company in internal technology, capped by taking a small data-automation project from pitch to working MVP. The real founder education came outside: stranded in Sri Lanka during the pandemic, he launched a distributed digital-fabrication startup to cut reliance on centralized imports — then, when travel reopened, passed its equipment to local young entrepreneurs so the work could carry on without him. A builder who ships, mostly alone, and says so plainly.
H.A.N.S.A. turns that same instinct on AI — replacing dependence on a handful of hyperscale datacenters with the compute people already own.
We're raising to take H.A.N.S.A. from a working MVP to a funded research program and a live community network. We're looking for foundations, public research programs, and mission-aligned partners who care about AI access, European digital sovereignty, and sustainable compute.
Aligned investors welcome too — if the mission fits your mandate, say hello.