Graphwise, a provider of AI context platforms, today announced major updates to its AI Context Platform, Graphwise Platform, which include new Adobe integration, built-in evaluation tools, and broader workflow automation features. The new release optimizes the creation of a comprehensive context layer for enterprises, which accelerates the integration of AI into multilingual content and data. With its latest software release, Graphwise now supports its customers more efficiently when transitioning AI from experimental pilot projects to scalable production systems.

Key platform enhancements include:

• AI Trust & Rapid Onboarding: A new evaluation framework to measure, audit, and benchmark AI response accuracy, paired with automated unstructured data ingestion pipelines that convert raw enterprise documents into grounded context faster.
• Enterprise Multilingual Governance: Native Adobe Experience Manager (AEM) integration for automated multilingual content tagging and cross-channel taxonomy synchronization to guarantee term integrity globally.
• Unified Administration & Automation: A centralized administrative control center for enterprise user and license management, alongside a rebranded, n8n-powered workflow engine to simplify complex data pipelines and GraphRAG orchestration.
• Mission-Critical Reliability: Comprehensive core performance and stability enhancements across the underlying graph database architecture, built to support high-concurrency enterprise deployments.

https://graphwise.ai

WisdomAI announced its Agentic Analytics platform is now embedded natively in Teradata’s new agentic coworker for enterprise data work, Tera, available within Teradata’s Autonomous Knowledge Platform in the fall of 2026. The integration brings WisdomAI’s deterministic agentic analytics platform to Teradata’s enterprise customers, letting business users talk to their data in natural language, build live apps from a single prompt, and deploy proactive AI agents that monitor KPIs, surface root causes, and drive the next action across structured, semi-structured, and unstructured data alike.

WisdomAI was built for the architecture enterprises run: data that lives in many places, under many controls, and rarely moves. Its architecture reasons across structured warehouses, semi-structured logs, and unstructured documents in a single query without copying, re-pipelining, or exposing data to external models. Inside Tera, WisdomAI executes queries directly on Teradata’s governed data foundation, with security, lineage, and access controls intact, making agentic BI viable on regulated, high-performance workloads off-limits to AI-driven analytics.

The integration also brings WisdomAI together with Tera Context Engine, which gives agents governed business context including industry data models, canonical metrics, business logic, lineage, and policies. Pre-curated definitions and semantic context allow more work to move from probabilistic reasoning to deterministic execution.

https://www.wisdom.ai/partners/teradata ■ https://www.teradata.com

Fivetran + dbt Labs released dbt v2 and dbt State, delivering more speed and cost optimization, and introduced Fivetran Context Layer, new dbt Wizard experiences, dbt Charts, and an open lakehouse vision for greater flexibility across storage and compute.

dbt v2 is a Rust rewrite of the dbt engine built for the scale that teams run at today and for how agents write SQL. It parses a 10,000-model project faster and gives teams and agents real-time feedback, surfacing errors, column checks, and lineage before anything runs. With this release dbt is one engine with two versions: dbt Core v1, the python implementation, is dbt v1. Fusion, the Rust implementation, has become dbt v2. Both versions remain Apache 2.0-licensed and security-supported.

dbt State determines what has changed by checking warehouse metadata and model SQL, then builds, skips, clones or defers each run accordingly. This simplifies orchestration and allows engineers to iterate without complex development rituals, while reducing unnecessary warehouse compute.

Fivetran + dbt Labs’ vision for Open Data Infrastructure centers on a customer-owned data layer built on open formats, avoiding vendor lock-in for storage and compute so organizations can store data once and access it through different engines for different use cases.

https://www.getdbt.com/blog/fivetran-dbt-labs-announces-new-capabilities-to-make-enterprise-data-agent-ready-at-dbt-summit