SAN FRANCISCO, CA – October 7, 2025 —TrustGraph, the pioneering open-source agentic AI platform built for enterprise demands, today announces the release of version 1.4.22, delivering groundbreaking advancements in flow configurability, structured data processing, and collection management. This major update empowers enterprises to achieve unprecedented flexibility and control over their AI workflows while maintaining the platform's hallmark transparency and scalability.

Transforming AI Workflow Management with Dynamic Flow Configuration
The centerpiece of version 1.4.22 introduces Flow Configurable Parameters, a revolutionary system that enables dynamic workflow configuration without requiring system rebuilds. This breakthrough allows enterprises to adapt their AI pipelines in real-time, adjusting Large Language Model (LLM) settings, temperature parameters, and processing configurations on-demand.

"Version 1.4.22 represents a fundamental shift toward truly dynamic AI infrastructure," said Daniel Davis, Co-Founder of TrustGraph. "Our new flow configuration system eliminates the traditional barriers between AI system design and operational deployment. Enterprises can now adapt their AI workflows as quickly as their business requirements change, without sacrificing the robust foundation they depend on for mission-critical operations."

The new flow parameter system introduces sophisticated **Advanced Parameter Mode** with controlled-by relationships, enabling complex interdependencies between workflow components. Organizations can now deploy LLM dynamic settings using llm-model and llm-rag-model parameters, while the new tg-show-parameter-types CLI tool provides comprehensive visibility into available configuration options.

Enhanced Intelligence Through Structured Data Diagnosis
Version 1.4.22 significantly expands TrustGraph's data processing capabilities with the introduction of the Structured Data Diagnosis Service. This powerful new component provides automatic detection and classification of XML, JSON, and CSV data formats, enabling TrustGraph's knowledge graph construction to work seamlessly across diverse enterprise data ecosystems.

The integrated Type Detector with schema selection capabilities ensures that structured data is properly understood and processed according to enterprise-specific requirements. This advancement bridges the gap between TrustGraph's renowned unstructured document processing and the structured data that forms the backbone of most enterprise operations.

Revolutionary Collection Management for Enterprise Scale
Addressing the complex requirements of large-scale enterprise deployments, version 1.4.22 introduces comprehensive Collection Management capabilities that provide granular control over data organization and access patterns. The enhanced system delivers Collection metadata management and deletion capabilities, integrated Librarian services, and sophisticated Collection tracking across all processors.

A critical advancement for enterprise security and compliance, the new User/Collection Isolation feature provides User/Collection Separation and User/Collection Processing, ensuring that sensitive data remains properly segregated across different organizational contexts and access levels.

Mark Adams, Co-Founder of TrustGraph, emphasized the significance of these enhancements: "Enterprise AI requires enterprise-grade data management. Our enhanced collection management system provides the governance and isolation capabilities that large organizations need while maintaining the flexibility that makes TrustGraph so powerful for innovation."

Performance Optimizations and Infrastructure Enhancements
Version 1.4.22 delivers substantial performance improvements across the platform's core infrastructure. The Cassandra Performance enhancements include a refactored knowledge graph implementation optimized for single-table operations, multi-table implementation for enhanced performance, and the addition of a dedicated Cassandra collection table.

GraphRAG Optimizations have been implemented throughout the system, providing faster query processing and more efficient relationship traversal. The Vector Store Enhancements now include automatic collection creation on query, streamlining deployment and reducing operational overhead.

The platform's robust Apache Pulsar foundation receives additional strengthening through Build System improvements that enable parallel container builds, significantly reducing deployment times for large-scale enterprise implementations.

About TrustGraph's Enterprise Mission
Since its release in 2024, TrustGraph has emerged as the definitive open-source platform for enterprise agentic AI, combining data streaming with knowledge graphs, structured data, VectorDBs, and MCP interoperability in a single containerized platform. TrustGraph’s mission centers on providing enterprises with reduced hallucinations and higher accuracy by grounding AI with contextually rich intelligence built from enterprise data.

TrustGraph's commitment to full stack sovereignty enables organizations to deploy the entire platform—including sensitive Knowledge Cores—wherever they choose: on-premises, private cloud, public cloud, or bare metal infrastructure. This approach ensures enterprises maintain ultimate control over their data and AI stack while escaping the "black box" limitations of proprietary systems.

Availability and Getting Started
TrustGraph version 1.4.22 is immediately available through the project's GitHub repository and comprehensive documentation portal. The platform's Configuration Builder provides guided setup for enterprise deployments, while the Workbench offers interactive development capabilities for AI engineers and data scientists.

Community Resources
- Documentation: https://docs.trustgraph.ai/
- GitHub Repository: https://github.com/trustgraph-ai/trustgraph
- Configuration Builder: https://config-ui.demo.trustgraph.ai/
- Discord Community: https://discord.gg/sQMwkRz5GX