Teams building AI products need to understand how well their product is working: Where are the gaps between AI-generated lessons and national learning standards? Is the AI capturing the necessary patient history in clinical notes? Are AI-generated risk assessments accounting for the right market factors?
But evaluating AI is genuinely difficult. Unlike traditional software, you can't just write unit tests and call it done. You need experimentation, careful methodology, and judgment from people who actually understand what "good" looks like in your AI product's domain.
That domain expert is often outside the evaluation process entirely. They give feedback to engineers who try to translate it into automated evaluations. It falls short. The cycle repeats. Weeks pass. Nuance gets lost.
The result is millions in costs, missed deadlines, and unreliable AI products.
We built Goodeye Labs so you can evaluate AI without PhD-level expertise or expensive consultants.
Goodeye Labs closes the gap between domain expertise and technical implementation for AI evaluations.
We put domain experts who know what "good" looks like in the driver's seat. A teacher can evaluate whether AI-generated curriculum covers the right learning standards. A healthcare professional can assess whether AI clinical notes capture the necessary patient history. A financial analyst can verify whether AI risk assessments account for the right market factors.
If you can grade a paper, you can use our product.
We handle the technical complexity around converting that judgment into automated evaluations. Engineers and data scientists easily access this judgment to improve the AI product. What used to take weeks of back and forth between experts, engineers, and data scientists now takes minutes with automated evaluations.
Expert insights on LLM evaluation and AI quality assessment
In 2025, we discovered we'd been measuring memorization, not intelligence. Models scored 80-90% on static benchmarks but dropped to 60-70% on truly novel problems. This comprehensive review explores the contamination crisis, the great decoupling, and what organizations need to build in 2026.
Read full article →
Co-Founder & CEO
Co-Founder & CTO
Join AI teams and domain experts building reliable AI products. Read our latest insights on LLM evaluation or get early access to new features and product updates by joining our waitlist.
