Release Notes – Version 1.1.2

Enhanced User Experience

Sorting for Guardrails and Applications lists: Quickly organize items in both views.
Fullscreen Application Configuration Modal: Normalized to fullscreen for consistency with Guardrail configuration.

Import/Export Applications (from UI): Export an application configuration and import it into another workspace directly from the UI.

Increased Timeout: Extended Playground timeout to better support longer-running experiments.

Kafka Topic Creation Flow: Adjusted creation process to avoid topic creation bootstrapping issues.
Kafka Image Update: Switched to the Apache-maintained image due to Bitnami deprecation.

Speech-to-Text Inputs for Textareas: Add microphone-powered STT to textareas across the UI for faster, hands-free input.

RAG-Based Pipeline for Policy → Rule Extraction: New retrieval-augmented option for converting policy documents into structured rules.

Support for GPT-5: Configure and run guardrails, workflows, and playground experiments with GPT-5.

Bug Fixes & UI/Usability Improvements: General stability enhancements and minor UI polish.

Auto-DAG Generation from Policy Documents: Revolutionary feature that uses Large Language Models to automatically analyze policy documents, extract compliance topics, and generate complete DAG structures. Simply paste your compliance document and let AI create comprehensive verification workflows.
Intelligent Topic Extraction: Advanced LLM-powered analysis that identifies 3-5 key compliance themes from any policy document, providing the foundation for systematic verification coverage.

Application-Scoped DAG Workflows: Create sophisticated verification pipelines by orchestrating multiple guardrails with Directed Acyclic Graphs (DAGs). Configure complex workflows that combine parallel execution, sequential dependencies, and custom aggregation logic within application containers.
Visual DAG Editor: Intuitive drag-and-drop interface for building DAG workflows with real-time visualization, node property configuration, and seamless switching between visual and JSON editing modes.
Interactive Playground: Enhanced testing environment with dual-view capabilities (Table View and JSON View) for comprehensive guardrail and application testing without code deployment.
Batch Processing: Enhanced Python client with support for batch request processing, enabling efficient bulk verification operations.

Real-Time Validation System: Comprehensive status indicators (green/yellow/red) that provide instant feedback on DAG and guardrail readiness, with detailed tooltips explaining any configuration issues.
Smart Button States: Context-aware interface that intelligently enables/disables functionality based on current configuration, with helpful hover messages explaining requirements.
Interactive Tooltips: Detailed guidance when hovering over disabled elements, showing exactly what needs to be configured (e.g., "Please select: Main LLM, Utility LLM, Embedding Model").

Pre-Flight Validation: Jaxon client now validates target applications and guardrails before execution, preventing wasted resources on invalid configurations.
Graceful Error Handling: Descriptive error messages for red status targets, with specific details about what needs to be fixed.
Enhanced Batch Processing: Improved batch operations that continue processing valid items while clearly identifying and logging validation failures.

Comprehensive DAG Validation: Deep validation of DAG structures including node configuration, guardrail references, connectivity, and dependency integrity.
LLM Requirement Enforcement: Systematic validation of required LLM models for different operations, preventing runtime failures due to missing configurations.
Expanded LLM Support: Additional LLM provider integrations and model support for increased flexibility in guardrail configurations.

Kubernetes Support: Full Kubernetes deployment support with Helm charts for production-scale orchestration and container management.
Enhanced UI/UX: Comprehensive admin interface improvements including application management, improved navigation, and streamlined workflow configuration.
Advanced Documentation: Restructured documentation with dedicated sections for Applications, Playground, and comprehensive DAG workflow guides.

Application API: New application-scoped API endpoints for managing complex verification workflows and DAG configurations.
Enhanced Python Client: Improved client library with batch processing capabilities and application workflow execution support.

Guardrails: Verify LLM outputs with Agentic, Policy Rules (Neurosymbolic), and Manual (Human Review) guardrails.
Integrated Logging & Dashboard: Real-time dashboards for monitoring inference.
LLM Generalization LLM proxy for decoupled usage of major LLM providers.

Python Client: Installable python client for direct integration into customer applications.