DiscreteStack is a private AI operating system that enables enterprises to deploy, govern, and scale AI on their own infrastructure — at predictable cost, with full data sovereignty.
We provide a turnkey AI platform that runs entirely on-premise. Enterprises get production-grade AI capabilities without sending data to third-party clouds, without unpredictable token-based pricing, and without the complexity of building and maintaining AI infrastructure themselves.
DiscreteStack handles model compilation, runtime optimization, caching, routing, monitoring, access controls, and integrations — all packaged into a single execution node.
Building custom AI costs millions. Renting from Big Tech means unpredictable, opaque costs that grow with usage.
Businesses are forced to run core operations on systems owned, monitored, and monetized by someone else.
Integrating third-party AI into core business systems means navigating regulatory, legal, and reputational risks with limited control.
€50,000 per execution node per year.
One node supports approximately 50 power users. No token limits. No per-request charges. Unlimited agent workflows.
Hardware lease options are available starting at approximately €30,000 per node per year, so teams can get started without upfront capital expenditure.
For a team of 50 power users, hyperscaler API costs typically run €150K–€250K per year. One DiscreteStack node covers the same team for a fraction of that cost.
Compare costs in detail: Cost Comparison Calculator
We run the most powerful open models available — hundreds of billions to trillions of parameters. Models like Kimi, GLM, and Mistral among others in their most capable forms. Each model is compiled specifically for designated hardware for maximum performance.
We support the full range of enterprise NVIDIA GPU architectures: Ampere (A100), Hopper (H100/H200), and Blackwell (B100, B200, B300, RTX 5000/6000 Pro). We design the right configuration based on your team size, model requirements, and workload profile.
Start a free 30-day trial: Request Trial Access
What's included in a node?
Everything your team needs to run AI in production — hardware-native model builds, the intelligent runtime that handles routing, caching, and scaling, plus monitoring, access controls, and integrations. One node, one price, nothing extra.
What hardware do I need?
We support the full range of enterprise NVIDIA GPU architectures: Ampere (A100), Hopper (H100/200), Blackwell (B100, B200, B300, RTX 5000/6000 Pro). We design the right configuration based on your team size, model requirements, and workload profile.
Can you provide the hardware as well?
Yes. We can deliver a fully configured node — hardware and software — ready to deploy in your server room or data center. We also offer a hardware lease option, so you can get started without upfront capital expenditure.
Can I start with one node and scale later?
Yes. You can expand capacity horizontally (adding more machines) or vertically (replacing with more capable ones). Our GPUe model covers both.
How does this compare to what we're spending on OpenAI/Anthropic today?
For a team of 50 power users, hyperscaler API costs typically run €150K–€250K per year depending on usage. One DiscreteStack node covers that same team for €50K per year, plus approximately €30K for a hardware lease. Compare costs here.
What models do you run?
We run the most powerful open models available — hundreds of billions to trillions of parameters. Models like Kimi, GLM, and Mistral among others. Each one is compiled specifically for designated hardware for maximum performance.
Who handles updates and maintenance?
We do. New models and updates are evaluated and delivered quarterly. Runtime patches and security fixes are included in the license. Your team focuses on using AI, not operating it.
How fast can we actually be live?
24 hours for full platform access (in shared environment). On-premise with existing hardware, typically within a week. If we're sourcing the hardware, expect 4–8 weeks depending on configuration and availability.
Do you support compliance requirements like SOC 2 and GDPR?
The platform runs entirely on your infrastructure — your data never leaves your environment. That simplifies most compliance requirements by design.