Say Goodbye

to Guesswork

with a data-driven approach
to AI development

The only data-driven toolkit to evaluate and improve your LLM application

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thoropass logo
pwc logo
Shell logo
Vanta logo
danswer logo
wolfia logo
ellipsis logo
Abel logo
thoropass logo
pwc logo
Shell logo
Vanta logo
wolfia logo
ellipsis logo
danswer logo
Abel logo

Systematically improve your

RAG
Prompts
Chatbot
Fine-tuning
LLM agents

Go From Prototype to Production Faster

Move quickly and with confidence. Make your complex system more robust and reliable with custom, high-quality data.

Auto Prompt
Optimizer
Custom
Evaluators
Synthetic
Golden Dataset
Systematic
Fine-tuning
Runtime
Monitor
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Data-Driven Development

Trusted by AI pioneers

Noam Rubin
Noam Rubin
AI Engineer at
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Security Compliance AI

Before we had Relari, we relied on guesswork and instincts to select key parameters such as similarity threshold, chunk size, embedding models, and retrieval strategies. Using Relari’s synthetic golden datasets and tailored evaluation metrics, we were able to easily understand trade-offs among different parameters over large datasets, and make confident, informed decisions. This data-driven process significantly improved our iteration speed, allowing us to reach production-grade for multiple LLM products over a short period of time.

Read the case study
Jiang Chen
Head of Ecosystem and AI Platform

Baseline LLM-as-a-judge is expensive and unstable. In a comprehensive RAG eval run, e 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."

Enterprise RAG
Yuhong Sun
Co-founder

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.

Enterprise Search
Mike Sands
Senior Director of Product

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.

Compliance AI
Tina Ding
Engineering Manager, AI and Enterprise Products

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.

Security Compliance AI
Nick Bradford
CTO

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.

Coding Agent

Pricing

How to get started
Community
Starter
Team
Enterprise
*credits can be used towards dataset generation, evaluation runs, and prompt optimization runs

Got a question?

Why data-driven development?
What's a golden dataset?
Can I use my own datasets with Relari?
What do I need to provide to generate synthetic datasets?
How do I create custom evaluation metrics?
How does auto prompt optimizer work?
My application isn’t written in Python or TypeScript. Will Relari be helpful?
I can’t have data leave my environment. Can I self-host Relari?

Stop the Guesswork and Ship Faster!

Get started with Relari’s data-driven development platform to supercharge your LLM product