A new declarative, intent-driven infrastructure that lets you deploy LLMs and regulate access to them. Create your own private LLM infrastructure with a provider-like feel, at a glance!
Access the alpha stage for free. Reach out to us at Show email or send me a direct message to request early access.
Running a medium/large enterprise and looking to move your agentic and/or vibe coding workload to an owned infrastructure with predictable, low costs? Under pressure about getting capped by daily token-window restrictions, or about costs getting out of control due to high API token prices?
Looking to keep a small subscription to proprietary frontier models for hard challenges only, while moving all the rest (95%) of your daily LLM workload to models like DeepSeek 4 (or 4.1) Flash to replace Sonnet 5 — but still having trouble with Chinese API endpoints and business rules, and you don't trust them?
Feel free to rely on rented GPU VMs/containers, turning them on and off only when demanded, or run your own private hardware (or both!).
Set up your scaling rules effortlessly.
Keep everything under control with a powerful telemetry system.
Block any data leak or security violation with a powerful DLP rule system.
Why LLM providers fall short, how Ventic works and what you get with a private LLM infrastructure.
Provider LLMs are perfect for very specific, personal tasks. Inadequate for agentic and business work.
Quota spent, work stopped. For a person it’s a wait; for a night agent it’s a failure you discover in the morning.
When the provider goes down, your product goes with it. No failover helps if the model only lives there.
The same prompts give different results over time. Silent updates, little transparency, no reproducibility.
On US frontier models the cost per token is high — and grows exactly as your product succeeds.
Cheap alternatives run on servers outside the EU. If your data must stay in the EU, that’s a dead end.
LLM usage is unpredictable by nature. Inside a company it becomes a line no one can close at budget time.
Either way you get the same: a private OpenAI- and Anthropic-compatible endpoint on a machine you can log into anytime.
You already have GPUs or prefer to buy them. We install the stack: compatibility check, inference engine tuned to your GPU (vLLM / SGLang), Ventic Agent, encrypted overlay, panel and observability.
E.g. 15 seats → €109.89/mo · 25 seats → €149.88/mo
Ventic Stack license only for BYOH: €69.90/month + VAT for 5 seats, €39.99 + VAT for each extra block of 10 seats. Volume discounts. Initial setup on request — you can also install yourself.
We find the right server at the right price in our catalogue, put it into production and invoice it with the service. All-in — hardware and license included.
You pay only for hours the server is on, license included. Never per token.
A complete solution to deliver LLMs to people and agents in a controlled way. Like an enterprise Kubernetes for LLMs: declare intent via GUI or CLI manifests, Ventic reconciles desired state — without touching drivers, kernels or inference engine flags.
The right machine sourced at the right price on your criteria. Purchased with an instant SEPA transfer.
PaaS onlyYour server configured in minutes. Or provisioned from catalogue, sized for the models and workload characteristics you need — LLM and embedding together on a tuned inference engine (vLLM, SGLang).
in minutesPrivate encrypted overlay that self-configures and traverses NAT. No public IP, no hand-rolled VPN, no ports open to the world.
zero exposureFair scheduling, auto-recovery after spot reclaim, shutdown in quiet hours, metrics and alerts. With support included.
continuousYour app talks to the proxy as if it were OpenAI. The proxy forwards over the encrypted overlay to Ventic Agent on the GPU node. The answer comes back the same way — no public hop.
OpenAI / Anthropic SDK unchanged. Only the endpoint URL changes.
Single endpoint. Authenticates, enforces RBAC and quotas, then forwards.
mTLS channel that traverses NAT. Nodes expose no ports.
Receives, queues fairly, feeds the inference engine.
Inference tuned for that model on that GPU (vLLM / SGLang). Replies to the proxy, proxy to you.
Like Kubernetes: describe the endpoint in a manifest, apply it from the CLI and get ready-to-use credentials — then actually use them, e.g. inside opencode.
apiVersion: ventic.io/v1kind: LLMEndpointmetadata: name: team-coding tenant: acmespec: model: qwen3.8-27b engine: vllm # TP=2, ottimizzato per la GPU replicas: 2 region: eu-south network: overlay: mTLS publicIP: none auth: rbac: [dev, agent] quota: 2M tokens/day scale: toZero: 15m # spegne quando nessuno lo usa maxReplicas: 4manifest valid — kind: LLMEndpoint / team-coding (tenant: acme)
→ intent sent to control plane…
✓ node gpu-node-03 attached via mTLS overlay · eu-south · no public IP
✓ weights qwen3.8-27b loaded · vLLM engine (TP=2) started
✓ endpoint READY in 3m 12s · replicas 2/2 · scale-to-zero 15m
credentials issued — tenant acme
export OPENAI_BASE_URL="https://llm.ventic.local/v1"export OPENAI_API_KEY="sk-vent-7f3a…9c2e"export ANTHROPIC_BASE_URL="https://llm.ventic.local/anthropic"export ANTHROPIC_AUTH_TOKEN="sk-vent-7f3a…9c2e"◆ opencode · model ventic/qwen3.8-27b via private proxy
◇ read src/billing.ts (212 lines) + 2 related files — context stays on overlay
◇ patch src/billing.ts + tests/billing.test.ts
✓ tests: 14 passed · diff ready to commit
✓ done via private LLM — 0 tokens billed by the public provider
Panel, proxy and observability run on your Docker infra — data stays with you. Only our agent runs on the GPU nodes. Between them, an encrypted overlay that self-configures and traverses NAT with no public IPs or VPN to maintain. An enterprise Kubernetes for LLMs: intent-based, manage everything from GUI or via CLI with manifest files — declare desired state, Ventic reconciles it.
Runs in your infra. Sees and manages only customer machines: powers them on/off per manifests. If absent, scaling is delegated to Ventic's Provisioner.
Runs on Ventic control plane. Acquires cloud GPUs (spot/dedicated, EU/US) and attaches them via overlay to your stack — even when you start on-prem and need to burst beyond your machines.
Will meter per-tenant usage for resale as subscription or per-token. Architecture ready — feature coming soon.
Ventic INP PaaS always exists and can supply even on-prem stacks — on-prem INP is optional and sees only your machines. Billing coming soon for subscription/token resale.
Adds a GPU replica to absorb the spike.
Removes a replica. You pay only for what you use.
Powers the node off. Wakes on the next call.
Agent reschedules to another provider with no hands on keyboard.
All automatic. No night ops.
Configures the coding agent your team already uses. No hand procedure, no endpoint to paste.
Users, roles, models, quotas and policy. The panel shown below.
One endpoint, OpenAI- and Anthropic-compatible. Existing clients stay as they are.
Logs, metrics and traces with Grafana in front. Usage data never leaves you.
Optional. Runs in your infra and sees only your machines: powers them on/off per manifests. If absent, scaling is delegated to Ventic's Provisioner.
Retrieval pipelines over your own documents.
Vector database backing the RAG collections.
Indexing served by the same inference stack.
Agentic harness, ready to wire to a model.
Alternative agentic harness, same wiring.
Native LangChain integration: your chains and tools call Ventic as OpenAI, with full OpenTelemetry tracing.
n8n workflow node for Ventic: internal no-code automations that stay inside your network, no data to external providers.
Every agent call traced in Grafana/LGTM: latency, tokens, errors and alerts on the channel you choose.
Routes traffic to hosts that expose nothing to the internet. Relay may be public; your nodes stay closed behind NAT.
Keeps the LLM up, exposes it over the overlay and shares it fairly. The only piece on the node.
Based on vLLM and SGLang, tuned for that model on that GPU, serving LLM and embedding together.
Always on, Ventic side. Receives intent from your stack, acquires cloud GPUs (spot/dedicated, EU/US) and attaches them via overlay — even when you start on-prem and need to burst beyond your machines.
Meters per-tenant usage and prepares resale as subscription or per-token. Architecture ready — feature coming soon.
Optional parts are switched on only if you need them: the minimum stack is agent, overlay and proxy. Ventic PaaS INP is always present and can supply even on-prem stacks; on-prem INP is optional and sees only your machines.
If the spot is reclaimed, Ventic reschedules and restores on its own — on another provider if needed.
One machine shared fairly: predictable context windows and exactly scheduled workload.
Encrypted overlay traverses NAT to reach the server even if it’s not exposed. Self-configuring: no fragile config.
GPU, CPU and OS in view, per-user token usage live, alerts on any channel you choose.
Panel to create, rotate and revoke users and keys. 2FA and external auth providers.
If nobody uses the LLM the instance powers off and wakes on the next request. No hours burned idle.
See how sessions are used and apply content restrictions per user or key.
For when commercial filters block the work: hardening, red teaming, bug bounty.
Same model across providers, in redundancy or failover: if one stops, the service doesn’t.
LangChain, n8n and OpenClaw/DeepSeek harnesses: your agents run all night on the private endpoint, with no provider windows or rate limits.
An n8n node that calls Ventic as if it were OpenAI: internal no-code pipelines with no webhooks to the outside and no data leaving your network.
OpenTelemetry traces on every agent call — latency, tokens and errors in Grafana/LGTM, with alerts on the channel you choose.
State of the art across three tiers of cost and intelligence. We choose the model with you, based on the job and the GPU in front of you.
| Model | Tier | Best for |
|---|---|---|
| Qwen 3.8 27B | Efficient | High volume and assisted coding, at the lowest cost per answer. |
| Qwen 3.8 Flash Next | Fast | Agents with many steps: where latency matters more than depth. |
| Deepseek v4 Flash 0731 | Balanced | The reference trade-off between code quality and throughput. |
| Kimi K3 | Frontier | The hardest agentic work, when you need the best open weights. |
VRAM, context window and inference engine settings are decided together during server analysis.
The best open weights are publicly available. Using them via external APIs means sending data to third-party servers — a non-starter for many companies.
With Ventic you download the weights and run them on your machine, where you chose to put it. The model is open; your data stays with you.
The model installed today is the same in six months, byte for byte. No silent updates: evals stay valid, prompts keep behaving the same.
We don’t bill per token. BYOH (Bring Your Own Hardware) pays per-seat license. PaaS pays by the hour, license included. How much the model writes doesn’t change the bill.
Comparison and per-user costE.g. 15 → €109.89 · 25 → €149.88
BYOH only: 5 seats included. Each extra block of 10 seats: €39.99 + VAT. Volume discounts. Setup on request, self-install possible.
Qwen 3.8 27B. 16 active users, up to 100 on roster. €160/month business hours, license included.
Deepseek v4 Flash 0731. 64 active users, up to 500 on roster. €960/month business hours, license included.
Launch pricing, VAT excluded · license only on BYOH: €69.90/month for 5 seats + €39.99 every 10 extra · business hours = 8 h × 20 days = 160 h/month · PaaS: hardware and license included in hourly rate · Prices indicated are reserved for early access alpha
We help you pick the right setup — BYOH with your servers or PaaS with ours — and start directly from the workload you want to put in production. Alpha stage, invite-only.