Overview

Improve your AI application outcomes

Build and monitor reliable AI applications for consistent results:

• Monitor AI model performance in production
• Detect and resolve issues proactively
• Improve response quality through data-driven insights
• Reduce costs with optimized resource usage

Understanding LLM observability challenges

Why traditional monitoring fails LLM applications:

• Cannot track prompt and completion correlations
• Cannot monitor critical LLM metrics (token usage, model parameters, response quality)
• Struggles to process structured and unstructured data effectively
• Cannot trace reasoning or debug black-box LLM failures
• Fail to track complex workflows with RAG, tools, and multi-step reasoning
• Provide limited support for human feedback and preference models
• Lack subjective metric tracking for user ratings and A/B tests

Maxim's solution

Maxim platform leverages three core architectural principles:

1. Comprehensive distributed tracing

Track the complete request lifecycle, including LLM requests and responses. Debug precisely with end-to-end application flow visibility.

2. Zero-state SDK architecture

Maintain robust observability across functions, classes, and microservices without state management complexity.

3. Open source compatibility

Maxim logging is inspired by (and highly compatible with) open telemetry:

• Generate idempotent commit logs for every function call
• Support high concurrency and network instability
• Maintain accurate trace timelines regardless of log arrival order
• Production-proven reliability with over one billion indexed logs

Key Features

Real-time monitoring and alerting

Track GenAI metrics through distributed tracing and receive instant alerts via:

• Slack
• PagerDuty
• OpsGenie

Monitor critical thresholds for:

• Cost per trace
• Token usage
• User feedback patterns

Saved views

Find common search patterns instantly:

• Store common search patterns
• Create debugging shortcuts
• Speed up issue resolution

Online evaluation

Monitor application performance with:

• Custom filters and rules
• Automated reports
• Threshold-based alerts

Data curation

Transform logs into valuable datasets:

• Create datasets with one click
• Filter incoming logs
• Build targeted training data
• Update datasets for prompt improvements