A modernization is on the horizon, but there is no clear vision for what the end result should look like.
The existing system creates a burden, but the scope, priorities, and direction of a migration are not yet clear.
Consulting & Diagnostics
Get things straight before a technical problem turns into a major project.
A platform needs to be modernized. The data is scattered across multiple systems. An AI initiative can’t seem to move beyond the pilot phase. Or the existing architecture is causing increasing overhead, without it being clear where the actual root cause lies.
We analyze the status quo, identify relevant dependencies, and determine what actually needs to be changed. This creates a solid foundation for architecture, investment, and implementation.
When symptoms become apparent, the cause often lies deeper.
Technical decisions can become costly if the actual bottleneck isn't clear.
Technical landscapes evolve over the years. New systems are added, processes change, interfaces are created under time pressure, and responsibilities shift.
The consequences become apparent gradually: releases take longer. Data must be merged manually. Multiple systems perform similar tasks. Individual components can hardly be modified without causing repercussions elsewhere.
Then, discussions about technologies often begin too soon. However, a new CMS, a new data platform, or a new AI solution will have little impact as long as it’s not clear which dependencies are actually limiting operations.
That’s why we start with the system behind the visible problem.
When a system analysis is appropriate.
This approach is particularly useful when the technical direction is not yet clear or when several problems arise at the same time.
Several systems have become intertwined over time.
Changes in one place have repercussions elsewhere. Responsibilities, data flows, and system boundaries are no longer clear.
A data or AI initiative isn't making progress.
The problem lies less with the model than with data access, data quality, integration, or a lack of structures for production operations.
An important technology decision is coming up.
Several platforms or architectures are under consideration, but there are no reliable criteria for selecting them.
Technical debt is becoming a business problem.
Releases take longer, operating costs rise, or new requirements can only be met through custom solutions.
We analyze only what is relevant to the decision.
The goal is not to provide a complete documentation of the entire IT landscape. We focus on the components and dependencies that affect the specific problem.
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System Architecture
We examine applications, components, technical dependencies, and system limitations. This reveals which parts function reliably and which changes are causing bottlenecks.
In the end, it must be possible to make a decision.
The result is a solid foundation for the next steps.
For us, an analysis is not an end in itself. It must be specific enough to serve as a basis for investment and implementation.
Depending on the initial situation, the results include a clear description of the actual bottleneck, relevant technical and organizational dependencies, a target vision for architecture and operations, prioritized changes, and a sensible sequence for migration or implementation.
The subsequent implementation can be carried out by Valanor, an internal team, or existing technology partners. Regardless of the approach, the basis for decision-making must be sound.
From the Status Quo to a Sound Decision
1. Assess the current situation
We analyze the relevant systems, data flows, interfaces, and processes. We reconstruct any missing documentation where it is necessary for decision-making.
2. Identify bottlenecks
We distinguish symptoms from causes and identify the interdependencies that actually prevent change.
3. Develop a Vision
We define how systems, data, interfaces, and responsibilities should be structured in the future.
4. Prioritize the transition
We determine which changes should be made first and which ones should be implemented later—or not at all.
5. Back Up Your Decision
Technical options are evaluated based on specific requirements: operations, integrations, security, costs, adaptability, and existing expertise.
Next Step
You don't have to know the solution yet.
To get started, all you need is a specific problem: a platform that’s holding back change, a data process that involves too much manual work, an unclear migration, or an AI initiative that lacks a clear path to production.
We analyze the root cause and determine the next logical step.
Aleksandar Basara
Managing Director
