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Arango Recognized as a Strong Performer in Multimodel Data Platforms, Q2 2026 Evaluation

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Arango believes recognition highlights its native multimodel architecture, customer adoption, and contextual data foundation for trusted enterprise AI

SAN FRANCISCO, July 6, 2026 /PRNewswire/ — Arango, the company pioneering the live Contextual Data Layer for enterprise AI, today announced it has been named a Strong Performer in The Forrester Wave™: Multimodel Data Platforms, Q2 2026. According to the report, Arango is “well-suited to organizations seeking a contextual data foundation where multihop graph performance and verifiable reasoning are mission-critical for trusted AI.”

The recognition comes at a time when enterprises are increasingly focused on how to create and operationalize business context for AI. As organizations move beyond experimentation and into production deployments of AI agents, assistants, and applications, many are reevaluating architectures built from separate databases, vector stores, search engines, and integration layers in favor of platforms that simplify how business context is connected, governed, and made available to AI systems.

Arango believes the recognition reflects growing enterprise demand for a unified approach to multimodel data management. According to the evaluation, Arango received the highest possible scores in the criteria of adoption and unified multimodel architecture.

“As organizations move AI initiatives into production, many are discovering that the challenge is no longer simply connecting data. The challenge is creating trusted business context that AI systems can reason over consistently,” said Ravi Marwaha, Chief Operating Officer and Chief Product & Technology Officer, Arango. “Enterprises increasingly want a simpler way to build, govern, and operationalize business context across their data landscape. We believe this recognition reflects growing demand for unified platforms that help organizations create a trusted foundation for enterprise AI.”

Why It Matters

At scale, enterprise AI is fundamentally a trusted business context challenge. AI agents, assistants, and applications must understand how customers, products, policies, processes, and operational events relate to one another. Organizations are increasingly looking for ways to create this context once, govern it centrally, and make it available across AI initiatives rather than rebuilding it repeatedly.

Agentic AI systems increasingly require access to multiple forms of data, including relationships, documents, vectors, search results, and operational records. As a result, technology leaders are seeking platforms that can:

Unify graph, vector, document, key-value, and search capabilities within a single architectureReduce the need for multiple databases, synchronization pipelines, and query layersSupport governance, lineage, provenance, and explainability across connected dataScale transactional, analytical, and AI workloads with greater operational controlAccelerate the path from AI prototype to production deployment

Rather than managing separate systems for each workload, organizations are increasingly seeking a simpler foundation for intelligent applications, assistants, and AI agents.

Recognition for a Contextual Data Foundation

In its evaluation, Forrester cited Arango’s native multimodel architecture, which combines unified storage, execution, and schema propagation within a single engine. The report also noted Arango’s integrated AI capabilities, which combine graph, vector, and document data in a single retrieval path with source citations.

Arango believes these capabilities are increasingly important as organizations seek to build AI systems capable of reasoning across connected enterprise data while maintaining transparency, governance, explainablity and trust.

Built on a graph-native multimodel foundation, the Arango Contextual Data Platform unifies graph, vector, document, key-value, and search capabilities into a single distributed engine. The platform enables organizations to create a live Contextual Data Layer, a persistent, governed representation of business context that can be reused across AI systems across the enterprise.

Building Trusted AI Starts with Trusted Business Context

As enterprises expand AI initiatives across products, workflows, and business functions, data foundations must support more than performance. They must also provide explainability, governance, traceability, and operational scalability.

Arango believes multimodel data platforms play an increasingly important role in enabling organizations to build context once and reuse it across AI systems, helping reduce duplication, improve consistency, and accelerate deployment.

Resources

Get access to the Forrester WaveLearn about the Contextual Data PlatformJoin our upcoming webinar: Contextual Data Layer for Enterprise AI: 6 Requirements for Agentic AI Systems

Forrester does not endorse any company, product, brand, or service included in its research publications and does not advise any person to select the products or services of any company or brand based on the ratings included in such publications. Information is based on the best available resources. Opinions reflect judgment at the time and are subject to change. This report is part of a broader collection of Forrester resources, including interactive models, frameworks, tools, data, and access to analyst guidance. For more information, read about Forrester’s objectivity here.

About Arango
Arango is pioneering the live Contextual Data Layer for enterprise AI, helping organizations transform fragmented enterprise data into trusted, reusable business context that enables AI agents, assistants, and applications to reason, decide, and act with greater accuracy, explainability, and trust at scale.

Built on the Arango Contextual Data Platform—a graph-native multimodel data foundation that unifies graph, vector, document, key-value, and full-text search capabilities with ACID guarantees—the live Contextual Data Layer enables organizations to build context once and reuse it across AI initiatives.

The platform includes more than 20 built-in AI services for contextual modeling, retrieval, orchestration, and enterprise AI development. The result is more accurate decisions, greater explainability, end-to-end traceability, faster deployment, and increased trust in enterprise AI outcomes.

Organizations including NVIDIA, HPE, Zscaler, London Stock Exchange Group, Siemens, the U.S. Air Force, NIH, Articul8, and others rely on Arango to power enterprise AI. Learn more at arango.ai.

Company: Arango

Announcement: Named a Strong Performer in The Forrester Wave™: Multimodel Data Platforms, Q2 2026

Category: Multimodel Data Platforms (MMDPs)

Target Users: Chief Information Officers (CIOs), Chief Technology Officers (CTOs), Chief Data Officers (CDOs) Chief Data & AI Officers (CDAOs), Chief AI Officers, Enterprise Architecture Leaders and Data Management teams

Primary Use Case: Building trusted enterprise AI with a live Contextual Data Layer that connects enterprise data, relationships, governance, and operational context

Key Differentiator: Native multimodel architecture combining graph, vector, document, key-value and full-text search capabilities in a single platform

Platform Snapshot:

Live Contextual Data Layer for enterprise AI20+ built-in AI services, including Arango AutoGraph, Arango AutoRAG and Arango Deep Search

Recognition Highlights: Strong customer adoption, customer success, customer retention, multimodel utilization, unified architecture across graph, vector, document, key-value, and search workloads, and support for multihop graph performance and verifiable reasoning for trusted AI.

Why This Matters: Organizations need trusted business context to deploy AI agents, assistants, and applications reliably, explainably, and at enterprise scale, with the transparency and governance required for trusted AI.

Source: The Forrester Wave™: Multimodel Data Platforms, Q2 2026

Media Contact
press@arango.ai 

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Zelus Automation Platform and Woodforest National Bank Sign Agreement for SNAP Platform

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July 14, 2026

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Partnership brings Zelus’s SNAP automation platform to one of the nation’s largest community banks.

THE WOODLANDS, Texas, July 14, 2026 /PRNewswire/ — Zelus Automation Platform and Woodforest National Bank® today announced an agreement for Zelus’s SNAP platform. The partnership will deliver next-generation automation capabilities across Woodforest’s retail banking operations, supporting the bank’s nearly 740 branches in 17 states nationwide.

“At Woodforest, it’s always been about customers first, community always, and this venture with Zelus brings that commitment to life in new and powerful ways,” said Julie Mayrant, President and Chief Community Bank Officer Woodforest National Bank. “Our upcoming move to Jack Henry’s SilverLake System™ sets the stage for exactly this kind of decision. Zelus’ SNAP solution integrates seamlessly with SilverLake, so we’re able to automate processes without adding complexity to our tech stack. It was a natural fit — one that lets us build on our core investment rather than work around it.”

The agreement reflects both organizations’ commitment to a long-term partnership built on shared goals of operational excellence and customer service. SNAP will be deployed across Woodforest’s retail banking network, which spans Alabama, Florida, Georgia, Illinois, Indiana, Kentucky, Louisiana, Maryland, Mississippi, New York, North Carolina, Ohio, Pennsylvania, South Carolina, Texas, Virginia, and West Virginia.

“We are honored to partner with Woodforest National Bank, one of the nation’s most respected community banking institutions,” said Russell Bond, Chief Executive Officer of Zelus Automation Platform. “This agreement is a testament to the power of SNAP and our shared vision of transforming the way community banks operate and serve their customers.”

The implementation of SNAP across Woodforest’s operations is expected to begin in the coming months.

About Woodforest National Bank

Woodforest National Bank has successfully stood among the strongest community banks in the nation, proudly offering outstanding customer service since 1980. Headquartered in The Woodlands, Texas, Woodforest operates nearly 740 branches in 17 states and employs approximately 4,300 associates. As an employee-owned institution, Woodforest understands the importance of investing in its people and the communities it serves. Woodforest is an Outstanding CRA-rated institution. For more information, visit www.woodforest.com.

About Zelus Automation Platform

Zelus Automation Platform is a leading provider of intelligent automation solutions for the financial services industry. The company’s flagship SNAP platform enables banks and financial institutions to streamline operations, reduce costs, and improve the customer experience through advanced automation technology. For more information, visit www.zap-llc.com.

View original content:https://www.prnewswire.com/news-releases/zelus-automation-platform-and-woodforest-national-bank-sign-agreement-for-snap-platform-302825450.html

SOURCE Woodforest National Bank

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High Rye Seeding Rates Prove Effective for Weed Suppression

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July 14, 2026

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A new Weed Science Society of America research article shows a generously seeded cereal rye cover crop helps reduce weed pressure for organic no-till soybean production

WESTMINSTER, Colo., July 14, 2026 /PRNewswire/ — A Weed Science Society of America (WSSA) journal, Weed Science, recently published a research article showing that a cereal rye cover crop helps reduce weed pressure for organic no-till soybean production, particularly when seeded at higher rates. The two-year research study reviewed field experiments conducted during the 2021-2022 and 2022-2023 growing seasons near Rock Springs, Pennsylvania, at the Pennsylvania State University Russell E. Larson Agricultural Research Center.

“The aim of this study was to compare the magnitude of weed control and soybean yield under different cereal rye densities within the soybean phase of cover-crop based organic rotational no-till production,” states Laurel Wellman, a Ph.D. student in plant sciences at Pennsylvania State University, and the study’s corresponding author. “Our results indicated that all cereal rye seeding rates reduced weed biomass compared to the unseeded cereal rye control plots, and that the higher cereal rye seeding rates reduced weed biomass significantly more than the lower seeding rates.” 

In two experiments, the researchers evaluated rye cultural management strategies for rye biomass, weed suppression, and soybean yield. They tested: 

four rye seeding rates (0.5-3 bu. acre) and two sowing arrangements (grid vs. row sowing)fall-applied poultry litter (0, 1.5, 3 tons acre) with two soybean planting dates (planting green or standard planting). 

“Increasing cereal rye seeding rate did not lead to increased rye biomass but did increase weed suppression,” points out Wellman. “Soybean yield was unaffected by rye seeding rates, and sowing arrangement did not affect any response.” 

Interestingly, “while fall poultry litter significantly increased rye biomass, weed suppression was unaffected,” she adds.

During one of the two cropping seasons studied, planting green reduced soybean establishment and yield, note the researchers. However, they also state that “these results highlight the limitations of organic no-till soybean production within grain crop rotations in the Northeastern U.S. when using cereal rye as a stand-alone weed suppression method. Increasing cereal rye seeding rates or applying fall fertility could be effective cultural practices when integrated with other weed control tactics to supplement weed suppression by rye surface mulch.” 

Overall, and perhaps most importantly, notes Wellman, the study “indicates that higher cereal rye seeding rates improved weed suppression independently of cereal rye biomass.” 

More information about the study is available online in the article: “Cultural management of cereal rye for weed suppression in cover crop-based organic rotational no-till soybean.” The research article is among others recently featured in Weed Science, a Weed Science Society of America journal, published by Cambridge University Press. Wellman can be contacted about the study at lew5444@psu.edu.

About Weed Science 
Weed Science is a journal of the Weed Science Society of America, a nonprofit scientific society focused on weeds and their impact on the environment. The publication presents peer-reviewed, original research related to all aspects of weed science, including biology, ecology, physiology, management, and control of weeds. To learn more, visit www.wssa.net. 

Media Contact: 
Jo Skelton 
Cambridge University Press 
Senior Brand and Partner Communications Manager 
cupacademic@cambridge.org 
01223326165 

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SOURCE Weed Science Society of America

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Technology

ICW Holdings Provides Update on Its Flagship Strategic Equities Investment Strategy

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July 14, 2026

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BROOKLYN, N.Y., July 14, 2026 /PRNewswire/ — ICW Holdings, LLC (“ICW”), an investment management firm, today announced the formation and launch of its flagship fund, a private investment vehicle pursuing a global, long-biased equity strategy by combining bottom-up company research with macroeconomic regime analysis and portfolio risk management.

Managed by Mark Dinner, formerly with Bridgewater Associates, the strategy is designed to create a diversified, risk-balanced portfolio of high-quality businesses. With a focus on managing concentration risk and navigating a wide range of inflationary, deflationary, and policy-drive environments, the strategy’s multi-layered investment process integrates macro risk analysis, systematic portfolio construction, and selective tail-risk mitigation.

“ICW was founded on the belief that companies are the most fundamental drivers of long-term value creation and our investment approach combines rigorous bottom-up equity selection with a deep understanding of macroeconomic regimes,” said Dinner. “We believe the current environment continues to reward an active, differentiated investment approach that can adapt across cycles. The strategy is designed with that flexibility at its core and formalizes an investment approach we have been actively executing since our founding in 2021.”

ICW’s leadership team combines macro investing expertise, systematic portfolio construction experience, and institutional operational oversight. Collectively, the team brings over 100 years of cumulative experience across leading investment organizations.

About ICW Holdings, LLC

ICW is an investment management firm founded in 2020 by Mark Dinner, a former senior investor at Bridgewater Associates, to apply a disciplined understanding of macroeconomic regimes and portfolio balance to equity investing. The firm serves eligible investors seeking risk-aware equity exposure across market cycles. All statements regarding personnel background, firm history, and strategy should be reviewed for accuracy and substantiation before dissemination.

Important Notice: This press release is for general informational purposes only. It is not, and should not be construed as, an offer to sell, or the solicitation of an offer to buy, any securities or other investment interests, and it is not intended to condition the market for any securities offering. ICW is not using this announcement to market any securities. Any private offering, if made, would be conducted only through confidential offering materials and only in accordance with applicable law.

Media Contact

Matthew Della Croce
Clario Group
1-646-319-7487
matthew.dellacroce@clariogroup.com

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SOURCE ICW Holdings

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