Platform Updates

Advanced Analytics Enhancements

• Introduced flexible analytics capabilities to slice and filter AI performance metrics across models, agents, datasets, and time intervals
• Added new Agent Span Count metric, enabling aggregation on agent level spans similar to existing tool span count metrics
• Improved persona specific visibility for Product, Engineering, Compliance, and Leadership stakeholders
• Enhanced metric exploration to support faster root cause analysis and performance monitoring

Navigation & Workflow Optimization

• Refined global navigation structure to improve discoverability of core workflows
• Maintained RBAC enforcement across updated navigation experiences
• Reduced friction between experimentation, tracing, analytics, and governance workflows

Trace Experience Upgrades

• Launched new Trace Overview dashboard with aggregated KPIs
• Added Trace KPI summary card for faster performance visibility
• Released redesigned Trace Viewer for improved debugging workflows
• Enhanced trace table with span status badges and token counts
• Surfaced cost metrics directly within trace workflows
• Introduced enhanced filtering mechanisms for:
  • Trace Viewer
  • CE management and results pages
• Introduced platform wide Dark Mode

Agent Discovery & Governance Enhancements

• Expanded Agent Discovery foundations with structured metadata support
• Added annotation analytics for improved agent oversight
• Strengthened governance workflows for increased transparency across teams

Arthur Engine & Toolkit

Agent Experiments & RAG Workflows

• Improved Agent Experiments UI for clearer experiment management
• Added reproducible session IDs for deterministic evaluation
• Enabled dataset overwrite support
• Introduced bulk editing capabilities
• Strengthened JSON validation for structured outputs
• Enhanced RAG notebooks and retrieval experiment workflows

Real Time Trace Ingestion Enhancements

• Introduced Agent Polling Mechanism to continuously poll GCP Cloud Run traces
• Enabled automatic population of Cloud Run traces directly into the Engine
• Reduced manual ingestion overhead for cloud native agent deployments

Expanded Model Provider Support

• Added support for Google Vertex AI
• Added support for AWS Bedrock
• Added support for vLLM
• Improved provider handling logic
• Implemented fixes and enhancements for Gemini integrations

Synthetic Data Generation

• Introduced built in synthetic dataset generators to support safe experimentation and evaluation workflows
• Added dataset generators for:
  • Binary classification: card fraud detection
  • Binary classification: credit application approval
  • Regression: loan amount prediction
  • Regression: housing price prediction

Deployment & Infrastructure Enhancements

• Added GCP model upload workflows with CI/CD integration
• Introduced OpenShift compatibility
• Enabled airgapped model loading support
• Improved model management controls and deployment flexibility

Data & Connector Improvements

• Expanded bucket based connectors with CSV file support
• Improved parquet handling performance
• Added Databricks integration
• Enhanced transform scalability
• Improved evaluation mapping workflows

Security, Stability & Performance

• Applied security patches and dependency upgrades
• Improved evaluation stability
• Enhanced reliability across experiments and trace workflows
• Delivered UX refinements to improve overall platform responsiveness and consistency