PandoreThe AI-operated infrastructure OS
Run production AI infrastructure without scaling your Ops team.
Your team asks in plain language. Pandore reads your estate, writes a plan, checks it against your policies, and waits for approval before anything runs. Multi-cloud, GPU-native, EU-hosted.
- EU data residency
- No standing write access for the AI
- Human approval before execution
- GPU-native
- Air-gap ready (2027)
A real governed run
Built by the Avarinth team. EU-native by design. In early access with design partners.
- Multi-cloud
- GPU-native
- Policy and memory engine
- Air-gap ready
Why now
AI spend is exploding. The bottleneck is now operations.
worldwide AI spend in 2026 (Gartner)
of provisioned GPU capacity sits idle
of AI projects never reach production
sovereign AI infrastructure market by 2040, up from $24.8B in 2026
For mid-market and regulated companies, the question is no longer whether to adopt AI. It is whether the infrastructure can keep up.
The problem
A 6 to 11 M€ per year infrastructure stack that no single vendor can orchestrate
This is no longer an infrastructure budget. It is a multi-million operating surface spread across compute, tooling, contracts, policies, and scarce human expertise.
- GPU and AI compute
- 1 to 2 M€
- Baseline cloud (CPU, storage, network)
- 0.8 to 1.6 M€
- Technical capacity and consultants
- 4 to 6 M€
- Kubernetes orchestration
- 100 to 600 k€
- Monitoring and observability
- 150 to 500 k€
- Compliance, security, audit
- 250 to 600 k€
- GPU scheduling and optimization
- 50 to 300 k€
Fragmented infrastructure is one of the largest hidden costs, and one of the largest execution bottlenecks, of enterprise AI adoption.
How it works
One operating loop. The request changes, the loop stays the same.
Map our PostgreSQL clusters, flag versions past end of support and any single-replica primaries, then draft a remediation plan.
Context
Reads your estate live through read-only connections. It never invents infrastructure facts.
Pandore is not a point solution for GPU optimization. It is a governed execution layer for infrastructure operations.
The product
Not a dashboard. The execution workspace where teams ask, approve, run and audit.
The workspace where teams plan, approve, run and audit infrastructure. Here is what each step looks like.
A reasoned plan, not a chatbot reply
Pandore reads your live estate, then writes a typed plan with a goal, a diagnosis and steps you can inspect before anything runs.
Nothing runs until policy passes and a human approves
Every change is a decision card with the exact command, its blast radius and its risk class. Approve it, or deny with a reason.
Every action becomes hash-chained evidence
An append-only ledger records each step, attributed to the agent, the policy engine, a human or the executor. Verify the chain, export the proof.
Every cluster, host and GPU in one live view
Whole-GPU capacity, node health and compute cost, metered at a small percentage of what Pandore manages.
The operating layer
Pandore operates every generation of infrastructure
Existing estate
Physical servers, VMs, storage and networks. Databases, middleware and legacy apps. Scripts and undocumented dependencies.
Current operations
Multi-cloud, Kubernetes and managed services. Observability, FinOps, IaC and CI/CD. Hybrid environments with fragmented tooling.
High-value wedge
GPU and accelerator clusters. Model deployment, orchestration and optimization. Sovereignty, compliance and cost constraints.
Different generations. The same operational challenge: fragmented context, manual execution, scarce experts.
More than an agent
An agent talks. Pandore remembers, checks, executes and proves.
Persistent infra memory
Remembers state, actions, incidents and past decisions, so teams do not restart from zero.
Policy engine
Authorizes, constrains or blocks each step before it runs. Built for CIO, CISO and compliance.
Live infra graph
Maps resources, services, dependencies, costs and constraints. Execution is context-aware, not generic advice.
Model-agnostic
Switch or combine models with no LLM lock-in. Bring your own key. Protects cost, performance and sovereignty.
Execution runners
Applies approved changes across cloud, on-prem, CPU, GPU and air-gapped environments.
Audit journal
Generates logs, reports and evidence automatically. Accountability is built in, not reconstructed.
Curated expert knowledge
Grounds operations in proven infrastructure practices, not guesswork.
Proof
Pandore pays for itself
AI B2B SaaS
Payback under 2 months
Saved expert time and one deferred infrastructure hire.
Sovereign cloud provider
66% of value captured
AI workloads retained and new AI accounts enabled.
Large financial institution
+192% ROI
Coordination effort saved and use cases moved to production.
Value comes from saved expert time, faster onboarding, captured AI workloads, and AI projects that finally reach production.
The difference
Competitors cover a layer. Pandore coordinates the whole loop.
Compute only
CoreWeave, OVHcloud, Scaleway
Covered
- Compute
Orchestration point tools
Pulumi, Spacelift, Kubiya
Covered
- Orchestration
GPU schedulers
Run:ai, Cast AI
Covered
- GPU scheduling
Observability
Datadog, Grafana, Komodor
Covered
- Observability
Mono-cloud copilots
AWS, Azure, GCP
Covered
- Compute
- Orchestration
Pandore
AI-operated infrastructure OS: the full stack, EU-native, multi-cloud, GPU-native, air-gap, with a memory and policy engine.
Covered
- Compute
- Orchestration
- GPU scheduling
- Observability
- Ops / SRE
- Compliance
Every layer is necessary. No competitor coordinates them in a single loop.
Security and governance
Autonomy you can put in front of an auditor
The agent is read-only
It reads your infrastructure and proposes changes. It cannot apply them.
The AI never holds the keys
A separate executor holds every write credential and applies approved changes once, with an ephemeral single-use grant.
Policy runs before execution
Out-of-policy changes are blocked, not flagged after. Irreversible production changes can require two approvals.
Every action is evidence
Requests, checks, approvals and changes are written to an immutable audit log you can export.
EU by default
Runs in the EU. Choose EU-hosted or self-hosted models so your data stays in your boundary.
- EU residency: pass
- blocked: region outside EU residency scope
SOC 2 Type 1 and air-gapped deployment are on our 2027 roadmap. We will show you current status on a call rather than claim a certification we do not hold yet.
The team
Built by operators, for operators
Building the AI infrastructure OS for sovereign Europe and every organization that cannot scale AI through scarce human operators alone.
FAQ
Questions teams ask us
Does the AI change my infrastructure on its own?
No. The agent is read-only. It proposes a change, a human approves it, and a separate executor applies it. The AI never holds a write credential.
Which clouds do you support?
Multi-cloud by design, including OVHcloud, Scaleway, AWS, Azure and GCP, plus on-prem and air-gapped environments.
Am I locked into one model vendor?
No. Pandore is model-agnostic. Bring your own key, run EU-hosted or self-hosted models, switch or combine models without lock-in.
How does it stay compliant with EU rules?
EU data residency, an immutable audit trail, and a policy engine that can enforce residency and approval rules before any change runs.
What does it cost?
A base fee plus a small percentage of the compute Pandore manages. We size it to your estate on a call.
See Pandore plan a real change on your infrastructure
Then watch it wait for your approval. 30 minutes, on your clouds, your GPUs, your compliance constraints.
Request a demo