AvanturinTaking on now
AI evaluation and monitoring
We measure AI quality and notice when it drops.
What it is
Test sets, automatic checks on every change, a log of answers, cost control and user feedback.
Typical problem
After updating a model or prompt, it is unclear whether things got better or worse.
What you get
- Test set and metrics
- Checks on changes
- Quality and cost dashboard
Who it is for
- Startups and founders
- Medium-sized businesses
- Large companies
- Agencies and IT companies
Related services
LLM integration via APIWe build a language model into your product or system.Operational monitoringA signal when an important process goes wrong.AI agents with toolsAI that not only answers but also takes actions in your systems.Multi-agent systemsSeveral specialized agents that solve a complex task together.RAG systemsModel answers based on your documents, with a link to the source.Model adaptation and fine-tuningTuning a model to your style and data when prompts are not enough.
Questions
Will the AI make mistakes?
Yes, any model sometimes gets things wrong. That is why we measure quality on your examples, show the sources of each answer and pass disputed cases to a person.
Where does our data go?
This is decided before work starts: an external API with suitable terms, a private cloud or a model on your own server. The choice depends on how sensitive the data is.
Which model do you use?
We choose for the task and budget, and build the architecture so the provider can be changed.
Tell us what needs to be built
We will tell you whether it can be done, how and roughly for how much. No obligation.