Trusting your AI 
should not be hard

Baseline LLM-as-a-judge is expensive and unstable. In a comprehensive RAG eval run, we spent $1,000+ bill on GPT4 tokens. It's also a challenge to collect domain-specific datasets. Relari's synthetic dataset generation and deterministic evaluation make it easier to develop high-quality LLM experience.

Relari's custom generated synthetic dataset is the best real world representation we've seen! We use the data to stress test our enterprise search engine and guide key product decisions.

Relari has helped immensely by building a set of metrics and standards that we can use to quickly and automatically evaluate changes in our LLM pipeline.

Generative AI is critical to Vanta’s roadmap across multiple products. Relari plays an instrumental role in our LLM product lifecycle, helping us systematically improve AI performance through rapid experimentation with custom synthetic datasets and high-quality metrics.

We iterate much faster on our coding agents thanks to the granular metrics Relari offers! Through high-quality synthetic datasets, we can benchmark and validate our agent performance with ease.