TrustGraph 2.8 is here

Async Infrastructure, Hybrid Retrieval, Structured Output, and a Plugin-Based Workbench

Author

Daniel Davis
September 08, 2026

TrustGraph 2.8 is available now, with a major upgrade to the platform foundation for enterprise knowledge and AI systems.

This release focuses on a practical problem: AI applications must remain reliable when they grow beyond a single demo, a single document library, or a small number of workspaces. That means scalable messaging, dependable retrieval, typed model outputs, observable services, auditable decisions, and an interface that can adapt to different domains.

Async pub/sub: removing a scaling bottleneck

TrustGraph has completed its migration from thread-per-consumer pub/sub to an asynchronous architecture.

In the previous model, a deployment with many workspaces and flows could consume hundreds of threads. TrustGraph 2.8 replaces that design with configurable async receive and send pools.

Async support now covers:

  • Apache Pulsar through pulsar.asyncio.Client

  • RabbitMQ through aio-pika

  • Kafka through aiokafka

  • The API gateway and reverse gateway

For operators, this means a much stronger basis for multi-workspace deployments. For custom processor developers, it also means migrating extensions to the async model.

Hybrid retrieval for Document RAG

Document RAG now combines two complementary retrieval strategies:

  1. Vector similarity for conceptual relevance.

  2. BM25 keyword retrieval for exact terms, names, identifiers, and domain-specific phrases.

TrustGraph merges the results with Reciprocal Rank Fusion (RRF).

The first keyword-index implementation uses SQLite FTS5 and scopes indexes by workspace and collection. If keyword retrieval is unavailable, TrustGraph degrades gracefully rather than blocking retrieval entirely.

Hybrid retrieval is especially useful for enterprise content, where a user might search semantically in one query and need an exact product code, legal term, technical error, or named entity in the next.

Native structured LLM output

TrustGraph 2.8 carries JSON schemas from prompt definitions through the completion layer into provider-native structured-output APIs.

This reduces the need to parse loose natural-language responses after generation. A runtime compatibility checker determines whether a prompt can use schema-enforced output with the selected backend.

Supported providers include OpenAI, vLLM, Ollama, Claude, Mistral, Azure OpenAI, Vertex AI Gemini, Google AI Studio, Bedrock, TGI, Llamafile, and LM Studio.

For agent builders, this enables more dependable workflows such as:

  • Data extraction into a validated schema.

  • Typed tool inputs.

  • Machine-readable report sections.

  • UI-ready generated data.

  • Controlled outputs for downstream automation.

Multimodal and document ingestion

TrustGraph now includes a pluggable image-to-text service with an OpenAI vision backend, gateway support, REST and WebSocket clients, IAM integration, and the tg-describe-image CLI.

The release also introduces a Docling-powered document decoder. The trustgraph-docling package supports PDF, DOCX, XLSX, PPTX, HTML, Markdown, and CSV, with page and hybrid chunking modes.

These services widen the kinds of enterprise information that can enter a knowledge pipeline.

Auditability and observability

TrustGraph 2.8 adds structured audit events for gateway activity and IAM decisions. Events include request and client-IP correlation, and they can be consumed into organization-managed storage and retention systems.

Metrics coverage now spans the platform from infrastructure services through embeddings, reranking, query paths, agent orchestration, gateway authentication, knowledge extraction, and IAM.

All platform metrics now use the tg_ prefix. The release also reduces metric-cardinality risk by removing workspace and flow labels from infrastructure histograms.

Extending the platform

A generic gateway passthrough mechanism now supports enterprise services outside the core TrustGraph platform. It uses opaque JSON request and response payloads with dynamic service lookup.

This makes it possible to attach organization-specific services, such as attestation engines, without modifying TrustGraph core code.

TrustGraph also continues to improve RDF support:

  • Language tags and XSD datatypes are preserved.

  • FILTER(LANG()) SPARQL patterns are supported.

  • Unicode-aware normalization preserves non-English entity names.

  • Cassandra now indexes literal RDF objects for graph querying by object value.

Workbench 2.0.3

TrustGraph 2.8 includes Workbench 2.0.3, which moves the UI to a manifest-driven plugin architecture.

Explorers can now be dynamically loaded as plugin packages. Teams can use remote plugins, multi-component bundles, and customer-specific plugins.json configurations.

Other Workbench additions include:

  • Five runtime themes: Dark, Midnight, Light, High Contrast, and Warm.

  • A shared themed component library.

  • 3D graph visualization through GraphCanvas3D.

  • A Threat Explorer for OCSF insider-threat investigations.

  • Incremental explorer data loading and search-result highlighting.

  • Automatic prompt-template discovery using the template. configuration prefix.

Upgrade notes

TrustGraph 2.8 contains important breaking changes:

  • The synchronous pub/sub layer is removed; custom processors must use async producer and registration APIs.

  • The default API port is now 8888, replacing 8088.

  • Vertex AI defaults to the global region rather than us-central1.

  • Existing RDF data that depends on language tags, datatypes, or literal-object lookup should be re-ingested.

  • The system-health CLI no longer accepts --api-url or --pulsar-url.

Get started

TrustGraph 2.8 is open source and available now: