Making AI Quality Measurable and Continuously Improving It
Systematically Evaluated – From Model Selection to Operations
IntraFind answers this question with a systematic evaluation approach that extends from the initial model selection to ongoing operations – making the quality of search, generative answers and agents measurable, comparable and controllable.
Gold Standards
The foundation is customer-specific gold standards: curated sets of real queries and expert-validated target results.
What is measured:
- search relevance
- embedding models
- answer quality
- classification models
When it is measured: before rollout, when comparing models and after every relevant change.
Subject-matter experts in your organization define what a good answer is.
Reducing Hallucinations, Backing Up Answers
- Only from verified sources: Generative answers are generated exclusively from permission-checked passages and delivered with source citations.
- Continuously evaluated: Answer quality is continuously evaluated against the sources using the gold standards.
The risk of hallucinations is not just claimed to be reduced – it is measured.
Analytics for Operations
- Zero-result queries show where content or synonyms are missing.
- Click rates and user feedback show whether the most relevant hits are at the top.
- Usage analytics show which use cases create value.
Search quality becomes a continuous improvement process with clear metrics.
💡FAQ - Quality and Evaluation
Your subject-matter experts together with IntraFind – in a structured way, with templates and tooling.
Zero-result rate, click rates, user feedback, usage per use case, model and token usage.
Secure, Sovereign, Compliant
✔️EU AI Act - The Enterprise AI Platform complies with the AI Act (Regulation (EU) 2024/1689)
✔️Data protection - GDPR-compliant operation
✔️No model training - Your data is not used to train AI models
✔️Data residency - You decide where your data is processed and stored
We Look Forward to Hearing from You
Bring us a specific use case – a search that takes too long, a question you want a chatbot to answer, or a process an agent could take over.
We’ll show you how to build it on the platform – and what becomes possible next without starting over.
