LLMonitor is an open-source observability platform designed for AI developers, allowing comprehensive tracking of costs, tokens, and performance metrics for AI applications.
LLMonitor is an open-source observability platform designed for AI developers, allowing comprehensive tracking of costs, tokens, and performance metrics for AI applications.
LLMonitor is a powerful open-source toolkit designed to provide comprehensive observability and evaluation for AI applications. It helps developers track and analyze costs, tokens, latency, user interactions, and more. By logging prompts, outputs, and user feedback, LLMonitor ensures detailed accountability and continuous improvement of AI models, making the development and debugging process more efficient and informed.
Who will use LLMonitor?
AI Developers
Data Scientists
Machine Learning Engineers
Chatbot Developers
How to use the LLMonitor?
Step1: Register on the LLMonitor website to get an app ID.
Step2: Integrate the LLMonitor SDK into your AI application.
Step3: Configure the SDK settings to start tracking desired metrics.
Step4: Deploy your application with the integrated monitoring tool.
Step5: Access the LLMonitor dashboard to view logs, performance metrics, and user interactions.
Step6: Analyze the collected data to refine and improve your AI model.
Platform
web
LLMonitor's Core Features & Benefits
The Core Features
Cost and token tracking
Latency analysis
User interaction logging
Prompt and output logging
Real-time performance monitoring
The Benefits
Enhanced observability and debugging
Improved AI model performance
Informed optimization decisions
Efficient user feedback integration
Holistic performance insights
LLMonitor's Main Use Cases & Applications
Monitoring and evaluating AI app performance
Logging and analyzing user interactions
Tracking and optimizing AI application costs
Debugging and improving chatbot responses
LLMonitor's Pros & Cons
The Pros
Comprehensive chatbot analytics and real-time monitoring of LLM interactions
Supports autonomous agents for automating complex tasks
Open-source with self-hosting options for maximum control and security
Enterprise-ready with SOC 2 Type II and ISO 27001 certification
Advanced privacy features like PII masking for GDPR compliance
Provides SDKs that integrate with multiple LLM frameworks and platforms
Prompt templates and collaboration tools for iterative improvement
The Cons
No publicly listed mobile app or browser extension support
May require technical expertise to set up self-hosted environments
Limited information about pricing tiers and cost-effectiveness beyond pricing page
Focuses heavily on chatbot and LLM monitoring; may not cover all AI agent use cases