Category: Enterprise software & integration (Page 1 of 39)

Tiny Technologies debuts TinyMCE AI

April 16, 2026 / NewsShark

Tiny Technologies announced the release and general availability of TinyMCE AI, a fully integrated AI writing environment built into the editor.

TinyMCE AI gives content teams everything they need to write, refine and review conversational AI, instant text transformations and automated quality checks without leaving the editor. This addition to the platform means that developers can meet user demand for robust AI content capabilities without adding a technical burden to application teams or imposing model lock-in.

With the new functionalities, developers can enable enterprise-grade AI features via a simple drop-in module. Content teams gain a collaborative writing partner that helps with research, understands the context of a full document, suggests changes through familiar editing markups, adapts to brand guidelines through custom prompts, and automatically catches quality issues.

Starting with version 8.4, key features include:

Conversational AI Chat: Enables multi-turn, natural-language conversations with awareness of the active document, and the ability to add additional context via web searches and file attachments.
Context-Aware Quick Actions: Applies rewriting, expansion, shortening and tone adjustments.
AI Review: Runs automated quality checks; delivers inline suggestions to improve clarity, consistency and accuracy.
Custom Prompts: Organizations can define and enforce brand voice, style guidelines, and content standards.

https://www.tiny.cloud/tinymce

Pantheon adds Next.js to WebOps platform

April 14, 2026 / NewsShark

Pantheon, a WebOps platform for running the web as one system, released managed Next.js. Changing how organizations deploy modern frameworks; moving from fragmented, multi-vendor stacks toward cohesive website operations where WordPress, Drupal, and Next.js sites are managed in one place.

With Next.js part of Pantheon.io’s WebOps platform, teams can move from fragmented workflows to a unified system that manages CMS and frontend under one dashboard, one workflow, and one contract.

Operational Velocity on a Single Stack: Eliminate the second vendor tax by unifying WordPress, Drupal, and Next.js on the same platform. A single Git workflow and the Terminus CLI allow developers to manage the CMS and frontend as one, using real-time GitHub build syncing to ship faster.
Enterprise Governance Without Bottlenecks: Automated CI/CD, Secrets Management, and Multidev environments ensure pull requests are tested before production. Standardized runtime controls provide enterprise-scale security without handoff delays.
Faster Publishing and Technical SEO: Move content in parallel with code. Content Publisher syncs Google Docs and Microsoft Word directly to your Next.js frontend — no dev ticket required. Integrated caching and a global CDN ensure sub-second load times, boosting user retention and AI/search authority signals.
Predictable Costs at Professional Scale: Contract-based pricing eliminates bandwidth overages and per-invocation charges.

https://pantheon.io/platform/nextjs

Box unveils the Box Agent

April 2, 2026 / NewsShark

Box, Inc., an Intelligent Content Management (ICM) platform, announced the general availability of the Box Agent, an AI-powered capability that takes natural language instructions to reason and complete complex tasks, allowing enterprises to work more effectively with unstructured data. Acting as a unified AI engine across Box, the Box Agent leverages the latest advanced reasoning models to securely search company files, analyze and synthesize critical data, and generate new content, while respecting Box’s enterprise-grade security, governance, and permissions controls. Box also announced enhancements to Box AI Studio, allowing admins to develop custom agents tailored to complex, business-specific use cases.

Leveraging AI capabilities from OpenAI, Anthropic, and Google, the Box Agent is able to autonomously understand a user’s intent based on their prompt, find the right content needed to execute that task, reflect on the work it needs to do, and iterate until it can successfully answer the user’s request. This all takes place within Box AI’s new conversational interface, which provides the ability to revisit previous sessions where users can iterate, refine, and return to work from where they left off.

Customers on the Enterprise Plus and Enterprise Advanced plans can start using the Box Agent today.

https://www.boxinvestorrelations.com/news-and-media/news/press-release-details/2026/Box-Unveils-the-Box-Agent-to-Transform-How-Enterprises-Work-With-Content/default.aspx

Adobe and NVIDIA announce strategic partnership

March 16, 2026 / NewsShark

Adobe and NVIDIA today announced a strategic partnership that will bring together Adobe’s creative and marketing workflows, models and technology and NVIDIA’s open models, libraries, research and accelerated computing to deliver the next generation of foundational Adobe Firefly models and creative, marketing and agentic workflows.

Firefly models will be built on NVIDIA’s computing technology and tap into NVIDIA CUDA-X, NVIDIA NeMo libraries, NVIDIA Cosmos open models, and NVIDIA Agent Toolkit software to enable interactive, high-quality creation.

Adobe and NVIDIA will also work together on NVIDIA NemoClaw— an open source stack that simplifies running OpenClaw always-on assistants more safely.

With NVIDIA, Adobe is launching a cloud-native, brand identity-preserving 3D digital twin solution (public beta). The solution creates virtual replicas of physical products that act as permanent digital identities for marketing and commerce experiences. Integrating NVIDIA Omniverse libraries into Adobe technologies, the collaboration expands support for 3D digital twin workflows built on OpenUSD for marketing content automation.

Adobe will also harness NVIDIA AI infrastructure, AI libraries, services and models to optimize its AI-powered tools across creativity, productivity and customer experience orchestration.

Adobe and NVIDIA Announce Strategic Partnership to Deliver the Next Generation of Firefly Models and Creative, Marketing and Agentic Workflows

Databricks launches Genie Code

March 11, 2026 / NewsShark

Databricks launched Genie Code, an autonomous AI agent that changes how data work gets done. Genie Code can carry out complex tasks such as building pipelines, debugging failures, shipping dashboards, and maintaining production systems. Just as agentic coding tools have transformed software engineering, moving developers from autocomplete-style assistance to agent-driven development, Genie Code brings the same paradigm shift to data engineering, data science, and analytics.

Genie Code is a new addition to Genie, which lets any knowledge worker chat with their data and get trusted answers instantly using the context and semantics captured by Unity Catalog. Genie Code extends this approach to data professionals, handling the complex engineering required to go from idea to production across all enterprise data.

Genie Code helps teams bridge the context gap to ensure the high levels of accuracy and governance required for production environments:

Handles full ML workflows end-to-end.
Accounts for differences between staging versus production environments, builds workflows for change data capture and applies data quality expectations.
Monitors Lakeflow pipelines and AI models to triage failures and investigate anomalies.
Integrated with Unity Catalog, enforces governance policies and access controls. It understands business semantics and audit requirements and federates enterprise data, including data from external platforms.

https://www.databricks.com/company/newsroom/press-releases/databricks-launches-genie-code-bringing-agentic-engineering-data

Graphwise announced the immediate availability of GraphRAG

February 17, 2026 / NewsShark

Graphwise announced the availability of Graphwise GraphRAG, a low-code AI-workflow engine designed to turn “Python prototypes” into production-grade systems instantly. It is based on a trusted semantic layer that reduces hallucinations and delivers precise and verifiable answers. GraphRAG unites LLMs, enterprise data, structured knowledge, and multiple search methods to deliver transparent, verifiable, enterprise-ready answers. Unlike standard RAG that “flattens” data into chunks leading to lost relationships and hallucinations, GraphRAG treats the knowledge graph as a trusted semantic backbone, ensuring AI responses are grounded in verifiable enterprise facts and complex relationships. Graphwise bridges the gap between complex enterprise data and functional AI agents. Features include:

Low-Code Visual Engine democratizes AI, enabling subject matter experts to adjust AI logic visually.
Out-of-the-Box Templates provide guardrails and support query expansion that deliver the fastest time-to-value.
Semantic Metadata Control Plane eliminates hallucinations and improves AI accuracy. AI responses are grounded in an organization’s “enterprise truth,” reducing risk.
Explainability and Provenance Panels support regulatory compliance. Built-in traceability affords transparency into how an AI response was produced.
Visual Debugging and Monitoring reduce maintenance costs by eliminating black box code.
SKOS-style Concept Enrichment harnesses domain-specific intelligence. This means AI understands company specific jargon, acronyms, and synonyms out-of-the-box.

https://graphwise.ai/news/new-graphrag-solution-moves-beyond-vector-only-rag-knowledge-graphs-provide-context-and-common-sense-to-ai

Snowflake makes enterprise data AI-ready with Snowflake Postgres

February 3, 2026 / NewsShark

Snowflake, an AI Data Cloud company, announced advancements that make data AI-ready by design, allowing enterprises to rely on data that is continuously available, usable, and governed as AI transitions from experimentation into production systems. With new enhancements to Snowflake Postgres, the database now runs natively in the AI Data Cloud so enterprises can consolidate their transactional, analytical, and AI use cases onto a single, secure platform. To help ensure AI systems are trusted at enterprise scale, Snowflake is embedding enhanced interoperability, governance, and resilience features into its platform.

Powered by pg_lake, a set of PostgreSQL extensions that allow Postgres to easily work within an organization’s open and interoperable lakehouse grounded in Apache Iceberg, enterprises can leverage Snowflake Postgres to directly query, manage, and write to Apache Iceberg tables using standard SQL. This capability is delivered within a Postgres environment, so enterprises can eliminate data movement between transactional and analytical systems.

Enterprises need data that remains open, governed, and resilient as it flows across engines, formats, and environments. Snowflake is expanding how customers access, share, and govern their data. Open Format Data Sharing extends Snowflake’s zero-ETL sharing model to include formats such as Apache Iceberg and Delta Lake.

https://www.snowflake.com/en/news/press-releases/snowflake-makes-enterprise-data-ai-ready-with-snowflake-postgres-and-advanced-innovations-for-open-data-interoperability

Elastic adds high-precision multilingual reranking to new Elastic Inference Service

February 3, 2026 / NewsShark

Elastic, a Search AI Company, made two Jina Rerankers available on Elastic Inference Service (EIS), a GPU-accelerated inference-as-a-service that makes it easy to run fast, high-quality inference without complex setup or hosting. These rerankers bring low-latency, high-precision multilingual reranking to the Elastic ecosystem.

Rerankers improve search quality by reordering results based on semantic relevance, helping surface the most accurate matches for a query. They improve relevance across aggregated, multi-query results, without reindexing or pipeline changes. This makes them valuable for hybrid search, RAG, and context-engineering workflows where better context boosts downstream accuracy. The two new Jina reranker models are optimized for different production needs:

Jina Reranker v2 (jina-reranker-v2-base-multilingual)
Built for scalable, agentic workflows.

Low-latency inference with strong multilingual performance.
Ability to select relevant SQL tables and external functions that best match user queries..
Scores documents independently to handle arbitrarily large candidate sets.

Jina Reranker v3 (jina-reranker-v3)
Optimized for high-precision shortlist reranking.

Optimized for low-latency inference and efficient deployment in production settings.
Strong multilingual performance; maintains stable top-k rankings under permutation.
Cost-efficient, cross-document reranking: v3 reranks up to 64 documents together in a single inference call, reasoning across the full candidate set to improve ordering when results are similar or overlapping.

https://ir.elastic.co/news/news-details/2026/Elastic-Adds-High-Precision-Multilingual-Reranking-to-Elastic-Inference-Service-with-Jina-Models/default.aspx

Category: Enterprise software & integration (Page 1 of 39)

Tiny Technologies debuts TinyMCE AI

Pantheon adds Next.js to WebOps platform

Box unveils the Box Agent

Adobe and NVIDIA announce strategic partnership

Databricks launches Genie Code

Graphwise announced the immediate availability of GraphRAG

Snowflake makes enterprise data AI-ready with Snowflake Postgres

Elastic adds high-precision multilingual reranking to new Elastic Inference Service

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