Parea AI

Parea AI is an experiment tracking, observability, and human annotation platform designed to help teams build and ship production-ready LLM applications. It provides end-to-end tooling to evaluate, debug, annotate, and deploy AI systems with integrated datasets, prompts, and monitoring across production and staging environments.

Key Capabilities

• Evaluation & Testing: Run online evaluations, compare samples, track regressions, and quantify improvements when updating models or prompts.
• Human Review: Collect and annotate feedback from end users, subject matter experts, and product teams to guide QA and fine-tuning.
• Prompt Playground & Deployment: Tinker with prompts on large datasets, test variations, and promote the best prompts into production.
• Observability: Log production and staging data, monitor cost, latency, and quality, and diagnose issues from a single dashboard.
• Datasets: Ingest logs from staging and production into test datasets to validate behavior and fine-tune models.
• SDKs & Integrations: Native Python & JavaScript/TypeScript SDKs, OpenAI, Anthropic, LangChain, and other major LLM providers and frameworks.
• Pricing & Plans: Flexible tiers for teams of all sizes, including free tiers and scalable enterprise options.

How It Works

• Integrate with your LLM workflow via Python or TypeScript/JavaScript SDKs.
• Use the evaluation and testing features to compare model and prompt performance on curated datasets.
• Collect human feedback through the Human Review module and attach it to specific samples or prompts for actionable insights.
• Run prompt experimentation in the Prompt Playground, then deploy top-performing prompts into production with traceability.
• Monitor production metrics (cost, latency, quality) and debug issues with integrated observability tools.

Core Features

• End-to-end experiment tracking and observability for LLM apps
• Human annotation and Q&A tooling for logs and prompts
• Prompt Playground for testing and deploying prompts
• Integrated datasets from staging/production for robust evaluation
• Python and JS/TS SDKs with auto-trace capabilities for LLM calls
• Native integrations with major LLM providers and frameworks
• Pricing tiers: Free tier, Team, and Enterprise with SSO and advanced security

Platforms & Integrations

• Python SDK: wraps OpenAI and other providers with optional auto-trace, supports experiment tracking and logging
• JavaScript/TypeScript SDK: similar capabilities for Node.js environments
• OpenAI, Anthropic, LangChain, Instructor, DSPy, and other major integrations

Why Teams Use Parea

• Confidence when shipping: track regressions, evaluate impact of changes, and surface actionable insights
• Collaboration: collect diverse feedback via Human Review and annotate logs for faster fine-tuning
• Production-readiness: unify evaluation, monitoring, and deployment workflows in one platform