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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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Axon Announces Body 5: Next-Generation Camera Built for the AI Era

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Axon Body 5 delivers 25x the AI processing power of earlier-generation cameras, with upgraded connectivity, audio and battery life to support real-time situational awareness in the field

SCOTTSDALE, Ariz., Oct. 24, 2026 /PRNewswire/ — Axon (Nasdaq: AXON), the global leader in public safety technology, today announced Axon Body 5, its newest body-worn camera designed to bring more powerful intelligence, connectivity and real-time support directly to officers in the field.

For years, Axon body cameras have helped agencies capture critical evidence and create greater transparency. Body 5 is built to help officers during the call, with information, assistance and backup on the spot.

“Officers shouldn’t have to choose between getting information and watching the scene. With Axon Body 5, they don’t,” said Rick Smith, Axon Founder and CEO. “They capture a license or document with the camera, keep their hands free and eyes up, and get information faster than writing it down and calling it in by radio. An officer fully engaged with the person in front of them, not down at a notepad, is a safer officer and a better-served community.”

Axon Body 5: Built for the AI Era

Built from the ground up for the AI era, Axon Body 5 delivers 25x the AI processing power than earlier generation Axon body cameras, alongside advancements in connectivity, audio, video and battery life. Together, these upgrades give the camera the physical power to run smarter AI features — both today and as new AI tools are developed in the future — while also making it more dependable for officers to use every day. 

For the first time, Axon is also introducing two versions of its latest flagship camera: Axon Body 5 and Axon Body 5 Pro.

Both models feature several key advancements, including:

25x more processing power for AI: A powerful new computing architecture creates the capacity to support current and future AI features directly on the body camera.Enhanced video: Improved video captures clearer evidence across challenging environments, including better low-light performance.Improved connectivity: Seamless connectivity in urban and remote environments – and more precise location capability – helps officers, cameras and remote support teams stay connected when timely information matters most.Longer battery life: 20% more battery life than the previous generation helps keep the camera ready and connected throughout an officer’s shift.

The Axon Body 5 Pro will continue to gain new AI capabilities as they become available, growing along with the AI Era Plan. Additionally, new hardware features include:

A near-focus camera: An additional dedicated camera lens lets officers scan driver’s licenses to check status and search for wants or warrants in seconds, without returning to the patrol vehicle, with relevant information sent to Axon Fusus to support real-time operations.Front-facing speakers: Four additional speakers project even more powerful audio toward the person an officer is speaking with, helping real-time translations from Axon Assistant carry more clearly over heavy traffic or crowd noise. Additional memory: Extra space lets the camera run several AI tools at once, helping officers stay better informed and work faster.

Bringing More of Axon’s AI Era Into the Field

Axon Body 5 helps officers get more out of the Axon AI Era Plan by bringing smart tools right to the scene. Axon’s portfolio already supports public safety professionals across a growing range of tasks. For example, Draft One helps officers turn body-camera audio into high-quality report drafts and Axon Assistant provides voice-based information access and real-time translation.

Increasingly, Axon is also bringing AI into real-time operations.

Axon Guardian is a new category of AI features within the AI Era Plan that was specifically created to work with an officer’s field-based devices – starting with body cameras and in-car cameras – to improve safety. Guardian is designed to flag potential risks as situations unfold and create alerts when additional attention may be needed. Two of the first features include:

Escalation Detection: When an Axon Body 4 or Axon Body 5 camera is activated and recording, Guardian has the ability to detect potential conflicts in real time and create an alert in Axon Fusus. A human reviews the livestream and decides if additional support or action is needed.Approach Alert: When active on Axon Fleet 3, Guardian can detect if the door of a stopped vehicle opens and alert the officer through the in-car display and their body-worn camera.

Combined, Axon Body 5 and the expanding AI Era portfolio demonstrate the importance of AI as a critical resource to assist public safety professionals before, during and after an incident — reducing administrative burden, improving situational awareness and helping protect more lives.

Innovating Responsibly

Axon’s Responsible Innovation framework guides the development of all of its products. Designed with this in mind, Axon Body 5 and Guardian prioritize human oversight and maintain agency control over data. As a key part of the responsible innovation process, Axon’s independent Ethics and Equity Advisory Council was created to help responsibly develop and deploy new technologies with transparency, while aligning with community expectations.

General availability dates for Axon Body 5 and Axon Guardian will be announced soon. Product features and capabilities vary by configuration. For more information on Axon’s current products and services: Axon Product Catalog – Axon.com.

About Axon
Axon (Nasdaq: AXON) is the global leader in public safety technology supporting state, local, federal and international public safety agencies with technology designed to Protect Life. Complementing its mission, Axon’s growing Enterprise market focuses on protecting critical infrastructure and frontline workers across multiple industries including corporate security, hospitality, retail and healthcare. Founder-led since 1993, Axon builds products with transparency and responsibility. From TASER energy devices to today’s connected network of hardware – including cameras, drones, and robotics – cloud software, sensors, and AI-tools, the Axon ecosystem helps seamlessly protect people and places when it matters most. To ensure these technologies align with community expectations, Axon’s independent Ethics & Equity Advisory Council guides the ethical, inclusive, and accountable design of its products and services. Learn more about the EEAC and Axon’s Responsible Innovation framework at Axon Responsibility. 

Non-Axon trademarks are the property of their respective owners. Axon, TASER and the Delta Logo are trademarks of Axon Enterprise, Inc., some of which are registered in the US and other countries. For more information, visit www.axon.com/legal. All rights reserved.

Please visit https://investor.axon.com and https://www.axon.com/newsroom for more information.

Media Contact:
Kate MacKinnon
Vice President, Communications
press@axon.com

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In HelloNation, Custom Fabrication Expert Mark Coyle Explains a Common Mistake in Custom Aluminum Design

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The article explains why smart geometry, not thicker walls, creates stronger, more efficient aluminum components.

ROCHESTER, N.Y., Oct. 24, 2026 /PRNewswire/ — What early design choice causes many custom aluminum projects to become heavier, costlier, or harder to manufacture? That question is addressed in a HelloNation article featuring insights from Custom Fabrication Expert Mark Coyle of American Custom Metals, Inc. in Rochester, New York, that outlines how misunderstanding aluminum behavior leads designers to rely on thick walls instead of stronger geometry.

The article begins by explaining that many people assume thicker walls automatically make aluminum parts stronger. It notes that aluminum does not respond to wall thickness the way steel does. Instead, its performance is shaped by how the metal flows through the extrusion die. The article states that custom aluminum design is more effective when profiles use ribs, chambers, and flanges to create stiffness without adding unnecessary weight. This guidance helps readers understand why adding material often increases cost without improving strength.

The article also highlights that thicker walls change how aluminum moves during extrusion. When heavy areas fill more slowly, the metal cools unevenly and can develop stress that only appears later. The HelloNation piece explains that well-balanced geometry keeps extrusion smooth and predictable. This consistency makes it easier to maintain dimensional accuracy across long production runs. By focusing on geometry, custom aluminum design avoids the problems that come with slow extrusion speeds and uneven cooling.

Another insight in the article centers on how ribs and internal supports influence stability. It describes how a thin wall supported by a properly placed rib often performs better than a thick wall with no reinforcement. This happens because the rib helps distribute load, improve stiffness, and guide the aluminum as it cools. The article explains that this structural approach makes custom aluminum design more efficient and gives designers more control over how the final part behaves under pressure.

The article also shows why early collaboration between designer and fabricator prevents costly changes. It states that a fabricator familiar with extrusion can catch potential issues before a die is built. Small adjustments to corners or transitions can remove weak points or improve metal flow. The article notes that this teamwork keeps the design aligned with real-world production. By working together early, both sides reduce the risk of redesigning the die after the first test run.

Machining is another area where the article explains how wall thickness affects performance. Features such as deep pockets or sharp internal angles may require slow feed rates or special tooling. When walls are thicker than needed, those areas can become difficult to machine cleanly. The article states that thoughtful custom aluminum design makes machining more predictable. Small changes, such as adding radiused edges or sizing features to match standard tools, help shorten cycle times and prevent tool wear.

Thermal behavior receives detailed attention as well. The article explains that aluminum retains heat differently depending on the mass of each section. Thicker walls hold heat longer, which increases the chance of distortion during extrusion, machining, or finishing. When a design uses geometry to create strength, the material cools more evenly. This reduces warping and helps long profiles stay aligned. The article notes that stable cooling is important for components that require a precise fit and consistent shape throughout an entire production run.

Cost is also a key topic in the article. It states that heavier profiles increase material use, extrusion time, and tooling needs. A custom aluminum design that relies on geometry instead of mass lowers material consumption and keeps the fabrication process efficient. The article explains that lighter parts are easier to handle, ship, and assemble. This saves money across multiple stages of production and supports long-term manufacturing efficiency.

The article also notes that smart custom aluminum design creates profiles that behave predictably during extrusion and machining. Smooth transitions, balanced wall dimensions, and structural features help reduce the chance of distortion or dimensional drift. These elements also lower scrap rates and support reliable performance. By using geometry instead of excess material, designers build parts that maintain strength without compromising manufacturability.

As the article concludes, it emphasizes that avoiding thick walls is one of the best ways to improve performance and lower cost. It states that the most dependable custom aluminum components come from designs that use structural features to strengthen the profile. When designers understand how aluminum behaves at each stage of extrusion and machining, they create parts that are strong, efficient, and consistent from batch to batch. This approach turns custom aluminum design into a predictable process rather than a series of uncertain adjustments.

A Common Mistake in Custom Aluminum Design features insights from Mark Coyle, Custom Fabrication Expert of Rochester, NY, in HelloNation.

About HelloNation
HelloNation is America’s Good News Network, a premier media platform built on the idea that good news travels faster when real people tell real stories. Through its community-focused publications and innovative “edvertising” approach, HelloNation delivers content that informs, inspires, and spotlights the leaders making a meaningful impact in their communities.

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World Young Scientist Summit 2026 Opens in Wenzhou, Zhejiang

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WENZHOU, China, Oct. 24, 2026 /PRNewswire/ — This is a report by China Daily:

On October 24, the World Young Scientist Summit 2026 opened in Wenzhou, Zhejiang. The event is hosted by the China Association for Science and Technology (CAST), the Zhejiang Provincial People’s Government, and the World Association of Young Scientists. Nearly 800 representatives, including scientists, educators, and entrepreneurs from more than 60 countries and regions, are attending the summit.

He Junke, Vice President of CAST in charge of daily work and First Secretary of its Secretariat; Lian Yimin, Chairman and Party Group Secretary of the Zhejiang Provincial Committee of the Chinese People’s Political Consultative Conference; Marcelo Knobel, Executive Director of The World Academy of Sciences; and Zhang Zhenfeng, Member of the Standing Committee of the CPC Zhejiang Provincial Committee and Secretary of the CPC Wenzhou Municipal Committee, attended the summit and delivered remarks. Yao Gaoyuan, Vice Governor of the Zhejiang Provincial People’s Government, presided over the first segment of the plenary session.

With the theme “Gathering Talents Worldwide to Create a Better Future,” the summit’s annual agenda is “Global Youth Action in the AI Era: Building a Sustainable Future.” It aims to draw on the insights of young people around the world, deepen international sci-tech cooperation, and jointly address questions about young people, science, the world and the future.

Efim Zelmanov, Fields Medalist and Foreign Member of the Chinese Academy of Sciences; Chen Yunji, Deputy Director of the Institute of Computing Technology, CAS, and Director of the National Key Laboratory of Processor Chips; Mary Garson, President of the International Union of Pure and Applied Chemistry; and Lu Chaoyang, Member of the Standing Committee of CAST, Executive Dean of the Shanghai Institute of Advanced Study, University of Science and Technology of China, and Chairman of the Council of the World Association of Young Scientists, delivered keynote speeches respectively on education reform in the AI era, AI and processor chips, young women scientists’ participation in science, and quantum computing. They explored new opportunities for scientific research, talent cultivation, and international cooperation in the AI era.

This year’s summit placed greater emphasis on the growth needs of young scientists, with young talents under the age of 45 accounting for 88 percent of participants. It aimed to build a cluster of international journals, bring together young scientific talent, facilitate a batch of international collaborative projects and advance the application and commercialization of scientific and technological achievements. The summit released the Report on the Distribution and Mobility of Young Scientists in the Field of Embodied Intelligence, launched the World Young Scientist Summit Partner Journal Program and the 2026 World Young Scientist Innovation and Entrepreneurship Growth Support Program. It also published the “Young Scientist Pioneers 2035” list and announced the 2026 Sustainable Development Young Scientist Award. The awards were presented to four Chinese and foreign scientists.

Chen Tianrun, Founder of Hangzhou Moxin Technology Co., Ltd.; Yuan Yang, Assistant to the Dean of the Institute for Interdisciplinary Information Sciences at Tsinghua University; and two of the 2026 Sustainable Development Young Scientist Award winners, César de la Fuente and Nicola Segata, among other Chinese and foreign young scientist representatives, spoke at the flash-talk session to share their research practices and reflections.

In addition, the conference focused on fields such as future manufacturing, quantum information, embodied intelligence, brain-computer intelligence, environmental science, deep-sea resources, and life and health, and held 12 parallel forums. It also included the “Gravitation π” Future Technology and Concept Products Exhibition and Exchange, local thematic side events, and sci-tech and humanities study visits, further building an interdisciplinary, cross-regional and cross-sector platform for youth sci-tech exchange and cooperation.

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