Assumptions must be open to challenge.
We make the question precise and look for evidence that could disprove our initial explanation.
About RÄVIR · method before narrative
Curiosity
with discipline.
RÄVIR connects operational understanding with data, method and critical questions. We investigate before recommending, and document how we reach an answer.
Working principles
We do not start with the answer.
Uncertainty must be visible.
We distinguish observation, calculation and interpretation. Missing evidence does not become a certain answer.
The result is not predetermined.
We agree a fixed fee for a defined assignment. Payment does not depend on finding a saving.
Working method & client data
Open to scrutiny.
After delivery, too.
How does RÄVIR use AI?
AI can support research, code, documentation and critical review. Suggestions and calculations must be checked. RÄVIR remains responsible for the delivered analysis and its conclusions.
How is client data handled?
RÄVIR’s policy is to use its own self-hosted models for AI analysis of client data, with suitability tested before use. Client data is not sent to external AI services. External models may support coding and research without client data. Purpose, access, retention and deletion are agreed in advance.
What if the data cannot answer the question?
We describe the limitation and what is missing. A data quality assessment or a recommendation to wait may be the appropriate professional result.
A simple starting point
Start with the problem.
What do you want to understand, decide or make work better? A few lines are enough to start the conversation.