About
Lunary is a comprehensive AI observability and prompt management platform designed to help engineering teams build, monitor, and improve LLM-based applications with confidence. At its core, Lunary captures every prompt, completion, and agent trace in production, giving developers deep visibility into how their AI systems behave in real-world conditions. The platform offers four main pillars: Observability (traces, error stack traces, instant search and filters), Prompt Management (collaborative templates, versioning, A/B testing), Evaluations (scoring LLM responses, feedback tracking, labeling data for fine-tuning), and Product Analytics (model usage, costs, topic classification, user satisfaction, custom dashboards). Lunary integrates seamlessly with any LLM or framework—including OpenAI, LangChain, and custom implementations—through lightweight SDKs available in Python and JavaScript. A single line of code is typically sufficient to start capturing data. For enterprise teams, Lunary provides RBAC, SSO, PII masking, and the ability to self-host in a private VPC using Kubernetes or Docker. The platform holds SOC 2 Type II and ISO 27001 certifications, making it suitable for regulated industries and companies handling sensitive data. Lunary is used across use cases including customer support chatbots, internal knowledge assistants, autonomous agents, and data analysis pipelines. It bridges the gap between technical and non-technical stakeholders by enabling product teams to collaborate on prompts without touching source code.
Key Features
- LLM Observability & Tracing: Capture every prompt, completion, and agent trace in production with full error stack traces, instant search, and filters to debug issues quickly.
- Prompt Management & Collaboration: Create reusable prompt templates with versioning and A/B testing, and allow non-technical teammates to iterate on prompts without touching source code.
- Cost & Performance Analytics: Track model usage and costs, analyze frequent topics, measure user satisfaction, and build custom dashboards to understand your AI product's health.
- Evaluations & Feedback Tracking: Score LLM responses, collect user feedback, and label data for fine-tuning to continuously improve model quality over time.
- Enterprise Security & Self-Hosting: Deploy in your own VPC via Kubernetes or Docker, with PII masking, RBAC, SSO, and SOC 2 Type II and ISO 27001 certifications.
Use Cases
- Monitoring the real-time performance and error rates of production LLM applications and AI agents.
- Iterating on and A/B testing prompt templates collaboratively across engineering and product teams.
- Tracking token consumption and inference costs across multiple models to optimize AI spending.
- Building and continuously improving customer support chatbots by analyzing conversation logs and user satisfaction signals.
- Labeling production data and tracking model feedback to create fine-tuning datasets and improve model quality over time.
Pros
- One-line SDK integration: Works with any LLM or framework (OpenAI, LangChain, and more) with minimal setup — just wrap your client and you're capturing data immediately.
- Self-hostable with enterprise compliance: Teams that need full data control can deploy Lunary in their own infrastructure while benefiting from SOC 2 and ISO 27001 certifications.
- End-to-end LLM lifecycle tooling: Covers observability, prompt iteration, evaluation, and analytics in a single platform, reducing tool sprawl for AI engineering teams.
- Cross-team collaboration: Enables both engineers and non-technical product teammates to collaborate on prompts and review AI interactions through chat replays.
Cons
- Self-hosting requires DevOps expertise: Setting up Lunary on your own Kubernetes or Docker infrastructure requires meaningful ops knowledge, which may be a barrier for smaller teams.
- Advanced features gated behind paid plans: Enterprise capabilities such as SSO, RBAC, and dedicated cloud deployments require upgrading beyond the free tier.
- Primarily developer-focused: While non-technical users can collaborate on prompts, the platform's full value is best unlocked by engineering teams familiar with LLM development.
Frequently Asked Questions
What is Lunary?
Lunary is an AI observability and evaluation platform that helps developers monitor, debug, and improve LLM-based applications. It provides tracing, prompt management, cost analytics, and evaluation tools in one place.
Does Lunary support self-hosting?
Yes. Lunary can be self-hosted in your own VPC using Kubernetes or Docker, giving you full control over your data and infrastructure.
Which LLM frameworks and providers does Lunary support?
Lunary integrates with any LLM or framework, including OpenAI, LangChain, and custom setups. SDKs are available for Python and JavaScript.
Is Lunary free to use?
Lunary offers a free tier to get started. Paid and enterprise plans are available for teams needing advanced features like SSO, RBAC, and dedicated cloud deployments.
What security certifications does Lunary hold?
Lunary is SOC 2 Type II and ISO 27001 certified. It also includes PII masking to help teams stay GDPR-compliant.
