Contact hvilkenAI
hvilkenAI is run by Erik Rundhaug. We evaluate over 350 AI models daily and present the strongest choices for Norwegian, Swedish and Danish users.
If you have questions about benchmark data, subscriptions, API access or editorial assessments, you can contact us directly.
What you can contact us about
- questions about which AI fits a specific task
- errors in model names, prices or provider information
- access to data, reports or API services
- business use, internal testing or custom comparisons
- privacy, terms or data deletion
How we handle messages
We prioritise concrete questions where we can give a verifiable answer: errors in public data, suggestions for clearer explanations, subscription questions or requests for access to benchmark data. If you report an error, please include the URL, a screenshot and the model or page involved.
Editorial input is reviewed against the same principle as the benchmark: recommendations should be independent, practical and understandable for users in the Nordic market. We do not change recommendations in exchange for payment from providers.
Independence
hvilkenAI has no commercial ties to the AI providers we test. We have no affiliate agreements, sponsors or paid placements from model providers. Recommendations are based on our own benchmark data and editorial quality control.
Before you email
Please include the country, language and use case your question relates to. That helps us answer more precisely, especially when the question concerns Norwegian, Swedish or Danish language quality in AI models.
See also privacy, terms and methodology.
What we do not do
We do not sell ranking placements, and we do not change benchmark results on request from providers. If a provider believes data is wrong, we ask for documentation and review the issue editorially. The same applies to user suggestions: concrete errors and useful improvements are prioritised over general marketing requests.
For companies and editors
If you are evaluating AI for a team, describe the workflow, language and risk level. We can then point you to the relevant benchmark, privacy page or data-access option. We do not provide legal advice, but we can help separate model quality, price, privacy and practical use.
How to get a better answer
If you ask which AI you should use, describe the task rather than only the tool you are considering. Include the language you work in, whether you need a free or paid option, how sensitive the information is and whether the answer is for private use, work or a product. That makes it easier to point you to the right benchmark, guide or test.
For error reports, concrete details matter most. Send the URL, model name, time and what seems wrong. We can then check whether the issue comes from model naming, price data, provider changes, translation or how the page presents the result.
How to use this page in practice
This page is written to help you make a concrete decision, not just read general AI information. Start by clarifying the task, the risk and how much you are willing to pay. Then compare the recommendation with today’s benchmark, the AI test and any relevant privacy or data requirements.
For personal use, it is often enough to try a free or low-cost option first. For work, customer content, documents or sensitive information, place more weight on control, source handling, language quality, stability and who processes the information. A good AI model is not only the one that scores highly on one day, but the one that gives reliable answers in your workflow.
HvilkenAI evaluates over 350 AI models and presents the most important signals without sponsored placements or affiliate ranking. Use the page as a starting point: test two or three options on the same task, check how much editing remains and choose only when you see which model actually saves time.
When to be extra careful
Be especially careful when the AI answer will be used in client work, hiring, finance, health, legal assessment or other work where mistakes can have consequences. In those cases, do not look only at price or top score; also consider control, data sharing, internal approval and how easy it is to explain why the tool was chosen.
A good choice is often the one with the lowest total risk: strong enough quality, clear limitations, reasonable cost and a workflow where humans still quality-check the result.