FAQ from Pi Labs
What is Pi Labs?
Pi Labs is an AI-native evaluation platform that empowers engineering, product, and ML teams to build, deploy, and iterate custom LLM and agent scoring systems—without writing eval code or managing model endpoints. It transforms subjective feedback into objective, measurable, and actionable metrics across the entire AI development and deployment pipeline.
How accurate is Pi Scorer compared to other models?
In controlled evaluation benchmarks—including TruthfulQA, MT-Bench, and domain-specific scoring tasks—Pi Scorer achieves >92% agreement with human expert raters, outperforming GPT-4.1 and Deepseek-R1 by 11–17% in consistency and calibration. Its architecture prioritizes interpretability and metric fidelity over generative fluency—making it purpose-built for judgment, not conversation.
Which tools and frameworks does Pi Labs integrate with?
Pi Labs supports seamless integration via SDKs, REST APIs, and native plugins for PromptFoo, CrewAI, GRPO, LangChain, LlamaIndex, Google Sheets, Notion, and common CI/CD pipelines. It also offers lightweight webhook-based ingestion for custom logging systems and observability platforms.
Is there a free plan for early adopters?
Yes—Pi Labs offers a generous free tier with $10 in monthly credits (equivalent to ~25 million tokens), unlimited custom scorer creation, full API access, and priority onboarding support. No credit card required.
Does Pi Scorer support images, audio, or structured data yet?
Today, Pi Scorer is optimized for rich text evaluation—including long-context documents, multi-turn chats, and code-heavy outputs. Multimodal evaluation (vision-language, speech-text, tabular reasoning) is actively in beta and expected to launch in Q3 2024.