llm request logging and tracing
Automatically captures and logs all LLM API calls, responses, and metadata in a centralized system. Creates detailed execution traces that show the complete flow of data through generative AI applications.
prompt version control and management
Maintains a version history of all prompts used in production, allowing teams to track changes, compare versions, and rollback to previous prompts. Enables systematic experimentation with different prompt formulations.
multi-model orchestration monitoring
Tracks and monitors applications that use multiple LLM models in sequence or parallel. Provides visibility into how requests flow through different models and where bottlenecks occur.
prompt optimization recommendations
Analyzes historical LLM request data to identify patterns and suggest improvements to prompts. May recommend changes based on quality metrics, cost, or latency optimization.
a/b testing and model comparison
Enables side-by-side testing of different LLM models, prompts, and configurations against the same inputs. Automatically tracks performance metrics and statistical significance to determine which variant performs better.
llm cost tracking and monitoring
Monitors and aggregates costs across all LLM API calls, breaking down expenses by model, prompt, user, or other dimensions. Provides visibility into spending patterns and cost optimization opportunities.
llm response quality evaluation
Assesses the quality of LLM outputs against defined criteria and metrics. Supports both automated evaluation (using rubrics or reference answers) and manual annotation workflows.
latency and performance monitoring
Tracks response times and performance metrics for LLM requests, identifying bottlenecks and performance degradation. Provides insights into which models, prompts, or configurations are slowest.
+4 more capabilities