Services · Strategy · Pilot · Implementation
AI projects first need clarity, then good systems.
Trixner digital solutions accompanies companies from initial assessment and preparation of their knowledge base to RAG pilot and productive internal AI solutions.
Evaluate and prioritize use cases.
Clarify channels, quality, and responsibility.
Test in real conditions and integrate cleanly.
Orientation
Not every problem needs AI. But every problem needs a clear decision.
Many companies start with tools before clarifying their data, process value and responsibilities. The result is usually a demo, not a dependable solution.
Our services follow a clear decision path: assess first, prepare data and knowledge next, then pilot and integrate.
Service Paths
Five starting points, depending on where your company is right now.
Decision support
The right approach depends on the level of maturity.
Some companies need a roadmap first, while others already know their RAG use case. The crucial factor is whether processes, knowledge sources, and responsibilities are mature enough for a pilot.
When many ideas are on the table, but priority, data, and benefit are still unclear.
If data channels, quality, rights, and responsibilities must first be systematically clarified.
If manual processes take time and a decision must be made on whether AI is even necessary.
When sources and responsibilities are sufficiently clarified and a focused area of knowledge can be practically tested.
Collaboration
This is how consulting leads to reliable implementation.
Assessment
Understand the starting situation, goals, systems, and data sources.
Database
Clarify channels, quality, rights, responsibilities, and preparation.
Pilot
Build a focused first solution with real questions, data, and processes.
Integration
Stabilize, document, and gradually expand results.
For decision-makers
Competence is shown not in the hype, but in the right order.
The services are designed to guide companies from an unclear AI idea to an actionable decision. This includes business processes, data quality, technical feasibility, and measurable benefits.
This way, isolated experiments are avoided, and digital solutions are created that relieve teams and fit into existing systems.
Next step
Let us find the right starting point.
A first conversation clarifies whether an AI audit, data & AI readiness assessment, automation check, RAG pilot, or direct implementation is advisable.