Equinix Inference Exchange combines NVIDIA Enterprise Reference Architectures, Together AI’s inference platform and Equinix’s global infrastructure to optimize deployment speed, flexibility and cost efficiency

REDWOOD CITY, Calif., Sept. 2, 2026 /PRNewswire/ — Equinix, Inc. (Nasdaq: EQIX), the world’s digital infrastructure company®, today announced a significant expansion of its longtime collaboration with NVIDIA to deliver Equinix® Inference Exchange, a distributed AI inference program for global enterprises, alongside a new collaboration with Together AI.

As AI scales across models, providers and geographies, where inference runs is a strategic imperative that determines performance, cost and governance. Equinix Inference Exchange will give enterprises a faster path from AI experimentation to production, with secure, low-latency connectivity to the data, users and ecosystem they depend on.

This collaboration brings together NVIDIA’s validated Enterprise Reference Architectures with Together AI’s inference platform, supporting more than 200 open-source models. Delivered through Equinix’s global data centers, it will provide connectivity to clouds, networks and AI providers through Equinix Fabric®.

The solution will be announced today at Equinix Horizon, the company’s inaugural customer and partner event, alongside Equinix® Fabric One™, which will make it easier for enterprises to connect across globally distributed AI environments.

“AI is transforming enterprise technology at extraordinary speed, and the infrastructure decisions enterprises make today will define their competitive position for years to come. Equinix is uniquely positioned to deliver what this moment demands based on our nearly three decades building the trusted exchange where the world’s enterprises run, connect and orchestrate their most critical workloads,” said Adaire Fox-Martin, Chief Executive Officer and President, Equinix. “Our longtime relationship with NVIDIA delivers the accelerated computing foundation at the heart of modern AI, while Together AI’s commitment to open ecosystems gives enterprises the flexibility to scale on their terms. Equinix Inference Exchange will enable architectures that are neutral by design, open by default and engineered for exceptional performance.”

“Equinix Inference Exchange turns the world’s leading digital interconnection platform into a global fabric for AI inference,” said Raj Mirpuri, vice president of global AI clouds and infrastructure ecosystem at NVIDIA. “As accelerated compute becomes a strategic asset class, combining NVIDIA’s infrastructure & technology with Together AI’s open-model inference platform and Equinix’s global reach gives enterprises a powerful, distributed foundation to bring intelligence closer to their data, applications and customers—accelerating the next generation of intelligent services.”

“Together AI was built on the conviction that open, accessible AI is what will define the industry moving forward, because enterprises shouldn’t have to choose between model performance and operational flexibility,” said Vipul Ved Prakash, co-founder and CEO, Together AI. “What we are building with Equinix and NVIDIA proves that model choice and performance are not trade-offs. They are the foundation of enterprise AI done right.”

Where Inference Runs Matters

The pace of enterprise AI adoption is outrunning the infrastructure needed to support it. As enterprise AI moves from experimentation to production, inference increasingly needs to run closer to the users, data and applications it serves across clouds, models, providers and geographies. This shift requires enterprises to determine not only how to deploy AI infrastructure, but where it should run and how it connects to the data, applications and workloads it depends on.

Managing these distributed inference deployments introduces significant operational complexity at precisely the moment enterprises need greater control and visibility.

“Performance, cost and governance have become strategic considerations as AI workloads grow more distributed across providers, data sources and environments,” said Nick Patience, Vice President & Practice Lead, AI Platforms, The Futurum Group. “Organizations are increasingly focused on where inference runs and how quickly it can be deployed into production. Solutions that simplify inference deployment while preserving flexibility will become increasingly important to achieve business outcomes.”

Equinix brings unmatched scale and ecosystem density to this challenge, with more than 280 data centers across 77 metros, 230 cloud on-ramps and over 10,500 businesses interconnected on its neutral exchange. Eight of the top 10 AI model providers and nine of the top 10 AI clouds are deployed with Equinix, underscoring the company’s position at the center of the AI ecosystem.

Built for Choice and Flexibility

Together AI is the latest addition to Equinix’s expansive AI ecosystem, bringing open-model flexibility and choice to enterprises deploying AI at scale. The solution combines three complementary layers designed to simplify distributed AI inference:

Equinix provides the infrastructure foundation, including power, advanced cooling and day-two operations, connected through Equinix Fabric to the clouds, networks and AI providers that inference depends on.NVIDIA anchors the build with its Enterprise Reference Architectures and AI infrastructure purpose-built to maximize AI factory throughput and minimize token cost.  Together AI runs the platform on top, supporting both multitenant deployments for shared efficiency and dedicated single-tenant environments for workloads that require dedicated capacity.

Built on Equinix Fabric, the solution will connect to inference providers across major metros worldwide, cutting time-to-first-token. It also will connect to an expansive ecosystem of clouds, networks and AI providers, reducing deployment complexity.

Designed for Modern Enterprise Inference

The solution aims to support a broad range of enterprise inference scenarios, including:

Metro edge inference: For organizations that need inference running closer to users and data, enabling lower-latency AI experiences while leveraging the security, operational scale and global reach of Equinix.Open model migration: For enterprises moving workloads from closed, proprietary models to open-source alternatives to control cost and avoid lock-in, the solution will provide a direct, low-friction path to run that migration in production, with Together AI’s open-model platform reachable over the same interconnected fabric enterprises already use to reach their other providers.Sovereign AI: For enterprises operating in regulated industries or specific geographies, the solution will enable AI workloads to run in locations that support data residency and sovereignty requirements, providing a simpler path to deploying AI at scale while maintaining control over where data and inference are processed.

Equinix Inference Exchange will be available starting in Q1 2027.

Additional Resources

Token Optimization Begins with Choice [Analyst Report]The Coordination Economy: How Enterprises Really Build AI Value [Blog]Equinix Inference Exchange [Product Page]Equinix Inference Exchange Product Release Note [Product Release Note]Equinix Horizon Event Page [Event Page]

About Equinix
Equinix, Inc. (Nasdaq: EQIX) shortens the path to boundless connectivity anywhere in the world. Its digital infrastructure, data center footprint and interconnected ecosystems empower innovations that enhance our work, life and planet. Equinix connects economies, countries, organizations and communities, delivering seamless digital experiences and cutting-edge AI—quickly, efficiently and everywhere.

Forward-Looking Statements

This press release contains forward-looking statements that involve risks and uncertainties. Actual results may differ materially from expectations discussed in such forward-looking statements. Factors that might cause such differences include, but are not limited to, risks to our business and operating results related to the current inflationary environment; foreign currency exchange rate fluctuations; stock price fluctuations; increased costs to procure power and the general volatility in the global energy market; the challenges of building and operating IBX® and xScale® data centers, including those related to sourcing suitable power and land, and any supply chain constraints or increased costs of supplies; the challenges of developing, deploying and delivering Equinix products and solutions; unanticipated costs or difficulties relating to the integration of companies we have acquired or will acquire into Equinix; a failure to receive significant revenues from customers in recently built out or acquired data centers; failure to complete any financing arrangements contemplated from time to time; competition from existing and new competitors; the ability to generate sufficient cash flow or otherwise obtain funds to repay new or outstanding indebtedness; the loss or decline in business from our key customers; risks related to our taxation as a REIT; risks related to regulatory inquiries or litigation; and other risks described from time to time in Equinix filings with the Securities and Exchange Commission. In particular, see recent and upcoming Equinix quarterly and annual reports filed with the Securities and Exchange Commission, copies of which are available upon request from Equinix. Equinix does not assume any obligation to update the forward-looking information contained in this press release.

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NEW YORK, Sept. 2, 2026 /PRNewswire/ — Today’s most ambitious manufacturers, particularly in defense, aerospace, and advanced industrial sectors, are racing to ramp production at software speed. Designs evolve weekly, products are increasingly modular and configurable, and the pressure to scale output without scaling headcount has never been greater.

Yet on most factory floors, the connective tissue between engineering intent and physical production still depends on static, manual, document-driven processes that were never designed to keep up. McKinsey finds that targeted improvements to existing defense industrial operations could cut production ramp-up times in half and double new capital efficiency. However, the industry continues to struggle with a younger, less experienced workforce where difficult skilled trades take significant time and training to master (read more).

The result is a coordination bottleneck. Engineering teams move quickly, but every design change ripples into hours or days of manual rework: reconciling CAD models, regenerating work instructions, updating routings in MES, and validating what is actually being built on the line. At scale, this consumes thousands of engineering hours per week that should be going into improving throughput, quality, and ramp speed. The downstream cost is staggering: Bain reports that aerospace and defense program cost overruns have surged to nearly $46 billion, while delivery timelines have stretched from 8 years to 11 years (read more).

A recent BCG global survey of nearly 1,800 manufacturing executives found that while 89% of companies plan to implement AI in their production networks, only 16% have achieved their AI-related targets (read more). To close that gap, Dirac and Amazon Web Services (AWS) are partnering to bring AI Process Design to advanced manufacturers. Through this partnership, Dirac’s BuildOS, the AI Process Design platform, is delivered on AWS infrastructure, including AWS GovCloud (US) for customers handling Controlled Unclassified Information (CUI), ITAR, and other export-controlled data.

In this post, we’ll share how Dirac’s BuildOS, hosted on AWS, helps manufacturers replace document-driven production with an automated, model-based system, as well as how customers like Anduril are already using it to compress work instruction authoring by nearly 90%.

Dirac is a manufacturing technology company building the AI-driven system of record for Process Design. Its mission is to rebuild the industrial capacity of the West by turning manufacturing facilities into context-aware, adaptive, dynamic environments.

The Manufacturing Coordination Bottleneck

In manufacturing, work instructions are the atomic unit of information on the factory floor. They are the step-by-step guidance that turns engineering intent into physical production: defining parts, tools, sequences, and fit. When products were stable and product lines changed slowly, static work instructions were workable. That world is gone.

Today, advanced manufacturers face a structurally different challenge:

Products are increasingly modular, configurable, and updated continuouslyDesign changes happen at software cadence, not annual release cadenceManufacturing engineers spend a significant portion of their time reconciling CAD, MES routings, and floor reality instead of improving the lineDocument drift between engineering and production introduces quality risk and slows ramp

Manufacturers facing this pattern are forced into a choice: slow design to protect manufacturing, or fundamentally rethink how the coordination layer works. For companies competing on speed, particularly in aerospace and defense, slowing down is not an option.

Snapshot of Dirac’s BuildOS

Rather than treating work instructions as static documents, Dirac’s BuildOS maintains a living, model-based representation of the product, the factory, and the relationship between the two. Geometry, structure, variants, physics, assembly logic, stations, tools, and material flow are represented in a single system. Work instructions are then derived automatically from this model, thus significantly reducing the need for manual authoring and re-authoring.

When the design changes, instructions update automatically. There is no painstaking re-authoring, no document drift, and no manual reconciliation between systems.

BuildOS is built on AI that deterministically reasons over structured manufacturing data by interpreting CAD geometry, inferring assembly steps, detecting dependencies, and propagating engineering changes through the Process Design. Beyond work instructions, BuildOS provides continuous Design-for-Manufacturability (DFM) feedback and earlier insight into cost, tooling, and throughput constraints.

AWS Powers and Secures Dirac BuildOS

Manufacturers, especially those operating in regulated environments, need production processes to be highly available, secure, and compliant from day one. That is why Dirac is powered by AWS.

Running on AWS gives Dirac and its customers:

Global, elastic infrastructure that scales with manufacturing demand without requiring customers to deploy or operate underlying infrastructure.AWS GovCloud (US) to support customers handling CUI, ITAR, and other export-controlled data, with FIPS-validated encryption.A mature security and compliance baseline, enabling Dirac to maintain SOC 2 Type II attestations, with controls aligned to NIST SP 800-171 and CMMC 2.0 Level 1 practices. (Dirac is not currently CMMC-certified; certification status will be updated as assessments are completed.)Defense-in-depth services — including identity, key management, network isolation, monitoring, and threat detection — so customers can deploy quickly while meeting their internal security requirements.

Dirac’s regulated environment is hosted in AWS GovCloud (US) and is used today by multiple defense contractors. CAD files, BOM data, factory models, and process designs are encrypted in transit and at rest, with keys managed through AWS-native key management services. This combination is what allows Dirac to stand up regulated environments in days rather than the months traditionally associated with bringing new tooling into a defense manufacturing program.

Eight Deployment Options, One Platform

Because manufacturers operate under widely different security, compliance, and IT requirements, Dirac on AWS offers eight supported deployment options. Each is built on AWS, and customers select the model that aligns with their data classification, compliance obligations, and internal infrastructure strategy.

This range matters because manufacturing customers do not all sit in the same place on the security and operations spectrum. A commercial industrial customer benefits from Dirac-managed SaaS on AWS Commercial. This offers fastest time-to-value and no infrastructure lift. A defense prime needing strict isolation, CUI support, and customer-owned operations can deploy Self-Hosted in their own AWS GovCloud (US) account. Every option in between exists for customers whose requirements fall in the middle.

For most regulated customers, Dirac typically recommends starting with SaaS on AWS GovCloud. It minimizes IT lift while meeting compliance requirements, and gets customers to production value quickly.

Business Benefits for Manufacturers

Manufacturers deploying BuildOS see impact across several critical dimensions:

Automated authoring: Work instruction authoring time is dramatically reduced, freeing manufacturing engineers from documentation work.Engineering changes propagate in minutes, not days: When a design update lands, the Process Design updates with it.Earlier DFM feedback: Cost, tooling, and throughput constraints are surfaced before production begins, reducing ramp risk.Scalable throughput without scalable coordination overhead: Production scales without proportional growth in engineering headcount.Production lines that adapt at the speed of design: The factory becomes responsive to engineering rather than a constraint on it.

Customer Spotlight: Anduril Selects Dirac to Power AI-Driven Work Instructions

In January 2026, Anduril selected Dirac as its core partner for AI-driven work instruction authoring in a multi-year deal, after evaluating incumbent enterprise tools and internal builds (read more). Before Dirac, more than 100 Anduril manufacturing engineers spent roughly half their time manually authoring and updating work instructions, equating to thousands of engineering hours per week.

[Embedded Video] Anduril COO Matt Grimm: “Dirac accelerates Anduril’s sales”

“Every serious manufacturer eventually hits the same wall: engineering moves fast, factories move carefully, and coordination becomes the true bottleneck. Dirac is the only team that understood this problem from first principles and how to solve it implicitly. Dirac’s BuildOS is becoming a core enabler of Arsenal OS, Anduril’s digital software ecosystem of manufacturing technologies. With Dirac, Anduril’s factories can be even more adaptive, dynamic, reconfigurable, and context-aware. AI-driven work instructions are the key.”

— Matt Grimm, Co-Founder and COO, Anduril

Deployed in an Anduril-hosted, ITAR-compliant AWS GovCloud environment, BuildOS was operational within days and delivered an 87.5% reduction in work instruction authoring time, therefore collapsing a 12-hour process into 90 minutes. Anduril is now rolling out Dirac enterprise-wide, standardizing BuildOS as core manufacturing infrastructure across the company.

[Embedded Video] Anduril COO Matt Grimm: “Since implementing BuildOS, we’ve seen wild, wild improvements” & 87.5% reduction in time to generate factory-ready work instructions from CAD

“The Dirac team understands manufacturing at a system level. Work instructions are the atomic unit of information in a factory, and Dirac’s BuildOS is the first platform we’ve evaluated that actually models that reality correctly. Just as importantly, they execute at an extremely high bar. From both a capabilities and execution standpoint, they were the obvious choice.”

— Cy Sack, Head of Business Systems, Anduril

Why This Partnership Matters

Advanced manufacturing is being redefined by speed, configurability, and the ability to adapt in real time. Achieving that requires automating the Process Design layer of the factory, where engineering intent meets physical production. Dirac is building that layer; AWS provides the secure, compliant, elastic foundation it runs on.

For manufacturers, the combined offering means:

Accelerated time to value: Regulated customers can be in production on AWS GovCloud in days, not months.Compliance-ready foundation: SOC 2 Type II attestations, controls aligned to NIST SP 800-171 and CMMC 2.0 Level 1 practices, and FIPS-validated encryption.Deployment flexibility: Eight supported deployment models on AWS so customers can match the platform to their security posture and operating model.Room to scale: from pilot to multi-site, multi-program production without re-architecting.

For Dirac, AWS is the foundation that makes serving the most demanding manufacturers in the country possible. For AWS, Dirac extends the platform into one of the highest-leverage layers of industrial operations: the system that decides, in real time, how things actually get built.

Conclusion

Dirac and AWS are partnering to give advanced manufacturers, from commercial industrials to defense primes, a path off document-driven manufacturing and onto a live, AI Process Design layer. With BuildOS deployed on AWS, manufacturers can collapse coordination overhead, propagate engineering changes through production in minutes, and scale output without scaling headcount.

To learn more about Dirac and how BuildOS can fit into your manufacturing stack, visit diracinc.com or contact the Dirac team at contact@diracinc.com.

Dirac Spotlight

Dirac is building the AI Process Design platform that replaces document-driven manufacturing with a dynamic system, helping advanced manufacturers run as fast as their engineering teams design.

Contributing Authors

Vedanth Srinivasan is Head of Solutions Engineering & Design and Go To Market (GTM) at Amazon Web Services, where he partners with technology companies building the future of advanced manufacturing.

This post was co-authored by the Dirac team in collaboration with AWS.

Media Contact: Gigi Schadrack, External Affairs, Dirac, Inc., gigi@diracinc.com, (929) 493-4722

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SOURCE Dirac, Inc.

F5, WitnessAI, Evoke Security and Mondoo Inc. join as new sponsors as community expands AI
security solutions guidance and surpasses 30,000 members

WILMINGTON, Del., Sept. 2, 2026 /PRNewswire/ — The OWASP GenAI Security Project, a global open-source community dedicated to advancing the security of generative AI and agentic systems, today announced a major expansion of its security resources, including the 2026 Top 10 for LLM Applications, a new Agent Control Standard for securing agentic AI systems, and expanded AI security solutions guidance. The resources coincide with the project surpassing 30,000 members worldwide and welcoming four new industry sponsors.

The OWASP GenAI Security Project’s Top 10 for LLM Applications 2026 is the latest edition of the project’s flagship guidance for identifying and mitigating the most critical security risks facing applications powered by large language models. The new edition surpassed 10,000 downloads within its first 48 hours, demonstrating the continued demand for practical, community-developed guidance as organizations move AI applications from experimentation into production.

The 2026 edition was developed with contributions from hundreds of AI security experts and incorporates updated rankings, expanded threat coverage and research drawn from thousands of real-world AI security incidents. It also expands mappings to other leading frameworks, including NIST, MITRE ATLAS, CWE and the OWASP GenAI Security Project’s Top 10 for Agentic Applications.

The OWASP GenAI LLM Top 10 2026 is available for download at https://genai.owasp.org/resource/owasp-genai-llm-top-10-2026/

The project also welcomed additional industry sponsors supporting its open-source research and community programs. New Gold Sponsors are F5 and WitnessAI. New Silver Sponsors are Evoke Security and Mondoo Inc.

Other key announcements include:

The project also unveiled its expanded AI Security Solutions Directory, an interactive resource that provides multiple lenses for understanding the rapidly evolving AI security market, including Generative AI Security, Agentic Security, and AI and Agentic Red Teaming.The Agent Control Standard (ACS) has been donated to the OWASP GenAI Security Project. The addition of ACS complements the project’s existing work on agentic AI risks, security controls, identity, governance and testing by extending that guidance toward practical runtime enforcement.The project also highlighted the new GenAI Security Industry Framework Crosswalk, an open resource designed to help organizations connect OWASP GenAI security guidance with established security, risk and compliance frameworks.The project has now surpassed 30,000 members on LinkedIn, bringing together security practitioners, AI developers, researchers, technology providers, government participants and other contributors from around the world.

Scott Clinton, chair and co-founder, OWASP GenAI Security Project, said: “Generative AI security has moved incredibly quickly from an emerging concern to an operational priority. What we saw at Black Hat and DEF CON this summer reinforces the need for open, practical guidance that security teams, developers and AI practitioners can put to work today. The growth of the project – and the breadth of contributions coming from across the industry – reflect how important community-driven standards and resources have become as AI and autonomous agents move into production.”

Steve Wilson, Top 10 for LLM founder and board member at OWASP GenAI Security project, and chief AI and product officer at Exabeam, said: “The 2025 Top 10 captured what practitioners were seeing as generative AI rapidly moved into the enterprise. In 2026, we’ve taken an important step forward, testing that community expertise against thousands of real-world incidents and using the evidence to sharpen how we prioritize risk. It also points to an important evolution ahead: AI is moving from models that generate content to agents that can act autonomously. Security must evolve with it—assuming AI will sometimes fail or be fooled and putting enforceable controls around what these systems can access, decide and do.”

Read the blog to hear what our new sponsors have to say about the project. 

About OWASP

The Open Worldwide Application Security Project (OWASP) is an online community that produces freely available articles, methodologies, documentation, tools and technologies in the fields of IoT, system software and web application security. Led by a non-profit called The OWASP Foundation, the OWASP provides free and open resources. The OWASP Top 10 – 2021 is the published result of recent research based on comprehensive data compiled from over 40 partner organizations. The OWASP Foundation, a 501(c)(3) non-profit organization in the U.S. established in 2004 in the U.S., supports the OWASP infrastructure and projects.

Media Contact

Jeff Alexander

Force4 Technology Communications 

Jeff.alexander@force4.co 

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SOURCE OWASP