Private AI setup
Your AI, built to your exact specs, direct to your infrastructure
We deploy a fully operational AI ecosystem directly into your cloud account or on-premise infrastructure, tailored to your requirements. You get complete control over the hardware, the software and the data footprint, direct from Ales.
What this turns on
Frontier models are becoming rapidly more capable, and most of them are reached over the internet. That is the difficulty. Confidential information, regulated records and commercially sensitive work cannot be sent to a service somebody else operates, under terms that can change. Cost is the second difficulty: metered inference is affordable in a pilot and becomes the largest line in the budget at production volume, because the bill scales with use rather than with value. The third development is the one that changes the answer. Open-weight models are now strong enough for most day-to-day work, and they are files you can download and run on your own machines. A private AI environment puts those models inside your boundary, keeps the largest external models available for the work that genuinely needs them, and leaves the choice of which goes where with you. What private deployment means and what a model gateway does.
The smallest version of this is one model, one gateway and one team, running inside your network with the source printed on every answer. Nothing about it has to be rebuilt to grow.
What we actually build
A gateway every request passes through
One place decides which model answers, applies your policy and keeps the record. Changing model later is a setting rather than a project. Model gateways.
Open-weight models, hosted by you
Deployed on your own hardware or on capacity inside your own account. The weights are a file you keep, and upgrades happen when you decide. Open-weight models.
Frontier models, through the same gateway
Reached under the same policy and the same record, for the tasks that benefit. Which tasks qualify is written down.
Your identity, your network, your keys
Your existing single sign-on and roles, private networking with no public route in, and encryption in transit and at rest. The environment inherits controls your security team has already approved.
Capacity sized on measured load
Model size, hardware class, concurrency and headroom are measured on your own work and written down with the reasoning, before anything is bought. Tokens, inference and why sizing matters.
Cost and usage in view
Every request is logged with who made it and which model answered, totalled by team and by task.
What you receive
A working environment, the connections into it, the models inside it, and the shape of the work it is set up to do.
Your private AI environment
A secure AI environment deployed in the cloud or on the infrastructure you choose, running under your own controls.
Your data, connected
The information your AI needs, from documents and databases to ERP, CRM and the rest of your systems. It works with what you already have.
The models you need
Open-weight models, frontier models, or both together. You choose the intelligence, and you change it as your needs change.
Ready for your work
Configured for the way you intend to use it: knowledge, analysis, assistants, automation and applications.
Scoped per environment. What decides the size of the work is how many people will use it, where your data is allowed to sit, and how quickly an answer has to come back. All three are measured before anything is bought.
What a private AI environment gives you
Choose your compute base and model tier
Select cloud or on-premise infrastructure, choose your model tier, and define your identity and security requirements.
Total supply chain transparency
Trace every single AI request, from source to response.
Model flexibility
Swap models easily through a single, self-hosted secure gateway, tailored per task.
Real-time visibility
See usage, cost and latency as they happen.
What we can build and run inside it
Enterprise Knowledge Synthesis AI
Convert legacy contracts, operation manuals and compliance procedures into immediate, single-sentence resolutions, delivered with absolute cryptographic lineage and direct source attribution.
Autonomous Workflow Optimization engine
Re-engineer high-frequency, repetitive business operations into high-velocity autonomous workflows, orchestrating advanced AI models, legacy systems and programmatic rules end to end.
Algorithmic Arbitrage and Model Optimization
An orchestration layer that audits and routes requests based on task complexity, offloading low-variance queries to hyper-efficient models and reserving premium frontier models for high-cognitive tasks.
Your AI should not become obsolete when the next model arrives
The model landscape is changing quickly. A model that is expensive today may be replaced by a cheaper open-weight model tomorrow, and a new frontier model may outperform the one you use now.
Your infrastructure should not have to start again each time. We separate the AI system from the model inside it.
Model A
Your AI system
Model C
Your AI system
Find out where AI fits in your organisation
Integrate the power of artificial intelligence into your workflows: securely, efficiently and privately.