Arize AX vs Radicalbit AI Monitoring

Arize AX is a platform for improving AI agents by turning production behavior into investigations, evaluations, and experiments. Signal surfaces important issues, helps identify causes, and prepares fixes for review. Managed Agents can investigate failing traces, fix repository bugs, automate recurring checks, or be created from scratch. Swarm Observability tracks status and performance across an agent swarm in real time. Agent-as-a-Judge uses telemetry to produce scalable evaluations that can surface unknown failures, while end-to-end experiments help validate changes. Integrations include OpenAI, Anthropic, Google GenAI, Amazon Bedrock, LangChain, LangGraph, LlamaIndex, CrewAI, and Vercel AI SDK; tracing follows OpenInference conventions and OpenTelemetry. AX Free costs nothing and includes 10 Signal issues/month, 25k trace spans/month, 1 GB ingestion/month, and 15-day retention. AX Pro costs $50 a month, with 25 Signal issues/month, 50k trace spans/month, 10 GB ingestion/month, and 30-day retention. Enterprise pricing is custom. Self-hosted deployment keeps observability data, authentication, APIs, and UI within customer infrastructure; air-gapped deployment is available.

Radicalbit AI Monitoring is a free, self-hosted platform for monitoring production LLM and machine-learning model effectiveness and reliability. It checks numerical and categorical data for anomalies, missing values, and outliers, then tracks metrics over time. Available model measures include Precision, Accuracy, Recall, F1, MSE, MAE, Perplexity, and Probability. Drift detection offers Kolmogorov-Smirnov, PSI, Wasserstein, Jensen-Shannon, Chi-square, Kullback-Leibler, and Hellinger methods. Reference and current datasets can be compared for data quality, model quality, and drift. LLM tracing records requests, prompts, and tools and displays sessions, traces, and spans with hierarchy and metadata. Documentation for version 1.4.0 focuses on binary and multiclass classification and regression, with more model types planned. A web UI, Python SDK, and REST API are provided. Local deployment uses Docker Compose with K3s and MinIO or AWS S3.