Start with the work.
Not with hardware.
We identify the process to improve, who will use AI and what information they will need. We define a concrete objective for evaluating the first project.
How it works
From the first requirement.
To your infrastructure.
A clear path to bringing AI into everyday work. Four steps, with shared decisions and verifiable objectives.
Start with the work.
Define your
data boundaries.
We map data, access and integrations. We choose between private cloud and on-premises computing based on your requirements, expected volumes and management arrangements.
Configure.
Integrate. Verify.
The gateway or GPU server becomes part of your environment. Planned integrations are checked against the agreed use case before usage is expanded.
Grow with
real results.
We assess response quality, usage and working times. New processes or more resources enter the plan when there is a real need.
Where does
processing happen?
It is one of the first decisions to make. It changes where resources are located and how data reaches the model.
Simplia Base · hybrid architecture
Your businessData and applications
Local gatewayAccess to AI
Private AI cloudPay-per-use computing
Conceptual diagram. Configuration and flows are defined for each project.
Simplia Pro · on-premises architecture
Your businessData and applications
On-premises GPU serverLocal processing
AI applicationsIn your environment
Conceptual diagram. Configuration and flows are defined for each project.
Frequently asked questions
Let’s clarify
the choices.
Do I need to replace my software?
The project starts with your existing systems. Possible integrations depend on available interfaces, permissions and the use case. We check these before defining the solution.
Does Base keep all data on-site?
The gateway is local, but AI computing happens in the private cloud. Data required by the model may be sent to that environment. The project must define which information is transferred, where it is processed and how it is managed.
Can Pro work without external connections?
The server runs AI workloads on-site. Completely isolated operation depends on models, licences, integrations and maintenance arrangements. It is a requirement to verify and design for, not a feature to assume.
Can I start with Base and consider Pro later?
Yes, an evolution of the architecture can be considered. Model compatibility, data transfer, integrations and server sizing are assessed to define the path.
How much does it cost and how long does it take?
It depends on the use case, volumes and integrations. For Base, the private AI cloud component follows a pay-per-use model. Hardware, services, timelines and terms are specified in the proposal.
Your next AI.
On your terms.
We start with your processes, your data and your goals.