Lunary

Lunary is an observability and prompt management platform built for LLM-based applications, AI agents, and conversational chatbots. It is delivered as a cloud service or a self-hosted deployment option running in a VPC via Kubernetes or Docker. The platform helps development and product teams track model usages and costs, analyze real-time user interactions, debug agent traces, and manage prompt templates collaboratively.

• Prompt templates with versioning, A/B testing, and collaboration tools for non-technical teammates
• Agent tracing and error stack traces with instant search and filters
• Model usage and cost analytics with custom dashboards and topic classification
• Human reviews to judge and score LLM responses
• PII masking and role-based access control with SSO support
• Multi-modal support covering text, audio, and images, along with an alerts system
• Open-source tokenizer tools including Mistral, Anthropic, OpenAI, Llama, and Deepseek tokenizers

Pros

• Strong security and compliance features including SOC 2 Type II certification, ISO 27001 certification, and PII masking for GDPR compliance
• Flexible deployment models supporting both cloud hosting and self-hosting in private infrastructure using Kubernetes or Docker
• Granular analytics providing insights into model costs, user satisfaction, frequent topics, and language usage
• Collaborative prompt management allowing non-technical teammates to test, version, and iterate on prompts

Cons

• The free tier caps log retention at 30 days and restricts users to 3 projects and 10,000 events per month
• Accounts that exceed event limits for two consecutive days face restrictions until upgrading or staying below limits for three consecutive days
• Advanced governance features such as SSO, granular access control, and data warehouse connectors require custom enterprise plans or self-hosting setups

Lunary fits engineering, product, and customer support teams building generative AI applications, autonomous agents, internal knowledge bases, and customer-facing chatbots. It is well-suited for organizations requiring strict data privacy compliance, self-hosting capabilities, and collaborative prompt iteration between developers and non-technical stakeholders. It is a poor fit for projects without LLM integrations or teams seeking an entirely free, unconstrained observability platform with unlimited long-term log retention.

Lunary uses a freemium pricing model comprising three main tiers. The Free tier costs $0 per month for personal projects, including 10k events per month, 3 projects, 30 days of log retention, and 1,000 AI playground queries per month. The Team tier costs $20 per user per month, providing 50k events per month, 1 year of history, unlimited projects, full API access, priority support, and additional playground queries charged at $0.05 per query after the included allowance. The Enterprise tier provides custom pricing for larger teams and includes self-hosting capabilities, SSO, granular access control, PII masking, SLAs, data warehouse connectors, and a dedicated technical account manager. Additionally, agency-specific plans start at $400 per month.

Unlike generic application monitoring tools, Lunary is specifically engineered around large language models and autonomous agents with native prompt versioning, A/B testing, and AI playground experimentation. It differentiates itself by combining traditional software metrics with specialized LLM evaluations like human response scoring, topic classification, and chat replays. Furthermore, it supports flexible self-hosted deployments in a private VPC alongside zero-friction SDK integrations for any LLM or framework.

Lunary integrates with OpenAI, LangChain, Python, CSV, JSONL exports, and various data warehouse connectors.

Lunary is worth trying for teams building production-ready LLM applications who need robust observability, prompt management, and cost tracking. The free tier offers an accessible entry point for personal projects, while the Team and Enterprise plans accommodate scaling requirements and strict security needs. Teams that require self-hosting, strict compliance certifications, or multi-modal tracking will find its feature set comprehensive. However, teams with zero budget that exceed 10k events per month will need to manage strict usage caps.