AI infrastructure built around your company's needs and rules
We design the technical environment in which your company can run AI with data protection, required performance, costs, and availability in mind. We use your existing infrastructure wherever possible and propose additions based on specific requirements. Everyday tasks can use public AI services; for data that must not leave a defined environment, we design suitable infrastructure of your own or rented capacity.
Leaders in automotive, banking, and telecommunications rely on our solutions
When you need your own AI infrastructure
Not every use of AI requires your own servers. The right environment depends mainly on requirements for data processing, performance, availability, and operations.
What we assess when designing AI infrastructure
The right infrastructure depends on which AI solutions you want to use, what data they will work with, and what their operation requires. We assess six areas during design.
Data protection and placement
We determine where each type of data may be processed and which security and legal requirements apply. We take into account company rules and the specific reasons why some data must not leave a defined environment.
Costs
We assess the costs of compute hardware, licenses, required capacity, and operations. The way operations are provided is therefore part of the decision, not just the purchase price of the technology.
Compute capacity
The required performance depends on the AI models used, the type of processing, and data requirements. We size it based on actual consumption measured during validation or in operation, so capacity is not set by estimate alone.
Availability and recovery
Depending on how important the solution is to the business, we define requirements for backup, recovery, and operation during outages. For critical systems, we also assess protection against the outage of an entire site.
Management and operations
Already during design, we address who will maintain, monitor, and manage the infrastructure. We design the environment around the capabilities of your IT staff and the way your company runs its existing operations.
Time to deployment
In planning, we take into account the availability and delivery times of compute hardware. If data protection requirements allow, the time until your own capacity arrives can be used to validate the solution in a rented environment.
Public AI services and your own infrastructure
Not all AI tasks need the same technical environment. Everyday use can run on public services, while processing data with stricter requirements may need your own or specifically rented infrastructure.
Public AI services without your own servers
For tasks whose data may be processed in public services, there is usually no need to wait until your own compute capacity is built. Your company can start using available AI tools and a work environment while infrastructure for more sensitive tasks is being prepared. Public AI tools →
Your own or rented environment for sensitive data
If data cannot be processed in public AI services, we assess processing it in your own or rented infrastructure. A rented environment must meet the same requirements for data protection and placement that apply to the task. For some types of data, renting may therefore not be permitted, and you need to plan for your own environment.
If the conditions allow renting, the solution can first be validated on rented capacity. We then use the measured consumption to design your own infrastructure.
Moving to your own capacity without unnecessary duplication
We design the infrastructure with a later change of environment in mind. Parts of the solution, such as access to AI models, model testing, input checks, or search across company materials, are prepared so that they can be reused where technical conditions allow. When moving to your own capacity, not every part has to be built from scratch, and the established way people work can stay the same as far as the new environment allows. Tools for work →
How we design and prepare AI infrastructure
We start from your existing systems
First, we assess your network, storage, security solutions, backup, and other parts of your IT infrastructure. Whatever can meet the new requirements is used for AI solutions as well; we mainly add what the existing environment does not provide.
We determine where each type of data may be processed
Together with your company, we assess the rules for each data category, placement requirements, and the conditions for transfers between environments. The company defines which rules and restrictions apply; we design the infrastructure so it can support them technically and, where possible, enforce them. Data →
We create a shared technical foundation for AI solutions
Individual AI solutions do not need their own separately managed infrastructure. Where appropriate, they use shared technical services and access AI models through one interface, which unifies access management, usage monitoring, and the application of shared rules.
We design a separate environment for the most sensitive processing
Based on security and legal requirements, we determine whether separation at the software level is sufficient or whether physical separation of infrastructure is needed. If content must be inaccessible even to the administrators of the technical environment, we design and verify the corresponding technical measures.
We plan for future changes to the infrastructure
Solutions are designed so that, where technical conditions allow, their location can change or they can be integrated into wider company infrastructure. If your company is preparing a central AI platform, purpose-built infrastructure can run on its own, and its later integration is assessed as part of the design.
We work with your IT team
Deployment requires the involvement of the people who manage the company's network, security, backup, and monitoring. We plan their involvement as part of the project.
We prepare the environment for handover and operation
Documentation, handover, and staff training are part of the delivery, so your company understands how the infrastructure works and can run it with its own staff or through a vendor of its choice.
Technical components of AI infrastructure
We deliver the technical foundation under the name AI Infrastructure & Trust. The specific scope is designed around the company's needs and the capabilities of its existing infrastructure.
Shared access to AI models
One interface lets solutions use both public AI models and models running in your own environment. It simplifies access management, usage monitoring, and replacing models without having to modify each solution separately.
Search across company documents and data
AI solutions can use information from internal documents and other company sources. Answers can include references to the sources used and respect users' permissions for individual data.
Input and data transfer checks
Technical checks help apply the rules on which data may be sent to which AI services. Depending on the solution, they can classify inputs, block disallowed transfers, and record the checks performed.
Access management and activity records
Access to data and functions follows the configured permissions, and it is possible to trace who used which services and what operations they performed. For sensitive data, selected information can be masked before it is sent to an AI model, where technically possible.
Compute capacity and an environment for models
Your own or rented compute capacity sized to the requirements of specific AI models and measured consumption. For processing the most sensitive data, we assess the need for a separate environment.
Management of models and their settings
Version records for AI models and prompts, testing of changes, and quality checks before deployment. Changes can be rolled out gradually to reduce the risk of disrupting existing operations.
Environment for deploying AI applications
Shared technical procedures and settings that help teams deploy solutions consistently, including the process for validating solutions and moving them into operation.
Monitoring and operations support
Monitoring of consumption, capacity, limits, and answer quality. Depending on the solution, also backup, recovery testing, and outage procedures. Documentation and training are part of the handover.
What you get
AI for sensitive business data, too
We design the infrastructure according to the requirements for protecting and placing that data.
Public AI services while your own capacity is being prepared
Tasks that the rules allow do not have to wait for your own infrastructure to be finished.
Compute capacity based on actual consumption
Measurement supports decisions on performance, scope, and costs of further deployment.
Reuse of technical solutions already prepared
In the design, we consider their portability between suitable environments.
Less dependence on a single vendor
When choosing technologies, we consider the option to replace models, environments, and the way operations are run.
Infrastructure ready to be managed by your IT team
Documentation, handover, and training are part of the delivery.
Established ways of working stay when infrastructure changes
We design the environment so that a change does not require unnecessary adjustments to people's work.
What AI infrastructure does not include
A replacement for a company-wide AI platform
We design infrastructure for specific AI solutions and their operation. If your company is preparing its own central AI platform, our solution does not replace its design or management.
Processing the most sensitive data in any environment
Not all data may be processed on rented infrastructure. Whether an environment is suitable depends on the specific legal and security requirements.
Developing our own language model
We use existing AI models and design the technical conditions for running them according to the company's needs.
Automatically ensured legal compliance
We assess regulatory compliance and data protection for each specific deployment. Your company approves decisions on data processing, risk assessments, and the relevant regulatory obligations; we provide the necessary technical input.
Preparing and managing the company's content itself
The infrastructure provides the technical conditions for processing data. Its sources, accuracy, currency, and usage rights are handled through data management and the relevant company systems. Data →
A fixed date and price without assessing requirements
Required capacity, licenses, hardware availability, and operating costs depend on the specific solution. We therefore set scope and schedule based on identified requirements and measurements.
How to get started
In the first meeting, we can focus on a specific AI solution or business agenda where you need to resolve the technical environment, data protection, or insufficient capacity.
We assess what infrastructure you already have, what can be used, and which requirements need further work. We also decide whether it makes sense to start with public AI services, rented capacity, or preparing your own environment. Overview of all areas AI adoption →
Pick one piece of work that slows you down
One specific task is enough for the first meeting. No commitment.