Conversation and access
We find out what the solution should do, what is not working and what access is available.
If your AI chatbot gives wrong answers, an agent behaves unpredictably, an integration stops or costs grow faster than results, we take over the solution, find the causes and put it in order. We work with solutions built by another developer, an in-house team or a no-code tool.
We find out what the solution should do, what is not working and what access is available.
We test the solution with real user questions and tasks and note where it goes wrong.
We sort out data, instructions, integrations and model choice, starting with what causes the most trouble.
After every change we test the solution against the same set of questions and compare the results.
We agree on maintenance, quality checks and further development.
Is your AI solution not working as promised?
We reply within one working day.
A chatbot makes up answers because it is not connected to company data or the data is out of date. An agent takes actions without checkpoints. An integration stops after an API change and nobody notices. Costs grow because the most expensive model is used for every question. All of these can be fixed without starting from scratch.
If a solution is built on a tool that does not let you control the data or the costs, we will say so plainly and compare improving it with a new solution by cost and risk.
The most common reasons are outdated or contradictory sources, a changed model version, instructions that have piled up over time without testing, or new kinds of questions. With a set of test questions we find where the answers have got worse and fix the cause.
Often, yes. Costs can be reduced by choosing a model that fits the task, shortening unnecessarily long instructions and context, using caching and limiting repeated requests. Before making changes, we measure how they affect the quality of the answers.