GROENLO, The Netherlands, April 21, 2026 /PRNewswire/ — Nedap (AMS:NEDAP), a leader in item-level inventory visibility, today announced a partnership with VF Corporation (NYSE: VFC), a global leader in apparel, footwear and equipment whose portfolio of iconic active and outdoor lifestyle brands includes The North Face®, Vans® and Timberland®. As part of the collaboration, VF Corporation will deploy the Nedap Inventory Engine across its brand portfolio and 1,500+ stores, creating a stronger foundation for end-to-end inventory visibility and more seamless, data-driven retail operations.

The deployment starts in Q2-2026 with The North Face and will expand to additional VF brands over time. With brands rooted in performance, elevated design and innovation, VF serves consumers worldwide across outdoor, active and workwear lifestyles.

Building a Unified View of Stock
The partnership supports VF’s ambition to create a single view of stock, built on a single, trusted view on inventory across its operations. With the Nedap Inventory Engine, VF aims to enhance stock accuracy, improve product availability and strengthen omnichannel performance across all regions.

In addition to the store rollout, VF has expanded the initiative into its distribution channels, enhancing visibility and supporting efforts to address grey-market activities and strengthen brand protection.

“Our consumers expect the same level of product availability and service whether they shop online, in-store or through any of our brand touchpoints,’ says Carsten Trenz, VP of Digital at VF Corporation. “Unified visibility across our operations allows us to deliver that consistency and build long term customer loyalty.”

Hope Waldron, VP of Supply Chain Strategy, VF Corporation adds: “Extending our RFID program beyond stores to include distribution centers and vendor partners at the source gives us greater transparency across our entire supply chain. That visibility improves our ability to ensure product availability, strengthen brand protection, and deliver a more consistent consumer experience.”

Why VF Chose Nedap
VF selected Nedap following a successful pilot using an alternative solution, after which the company reassessed its long-term requirements for scalability, architecture and global support. Nedap was chosen based on:

The most robust, innovative and future-proof platform architectureA proven track record of guiding and advising organizations through complex rollouts at scaleA user community that drives continuous improvement and shared innovation across leading retailers

“In today’s retail landscape, unified commerce only works when brands can rely on one consistent source of truth for their inventory,” says Hilbert Dijkstra, Managing Director Retail at Nedap. “VF’s decision to invest in end-to-end visibility reflects a clear vision for the future: the ability to serve consumers seamlessly across any channel. Through ongoing innovation of our platform, we help VF operate with confidence, agility and precision.”

Nedap in Retail
Nedap empowers retailers to turn inventory movement into real-time insight and real-world results. Our Inventory Engine connects item movement across stores, distribution centers, and factories, creating one reliable view of inventory for the entire retail chain. Built on open global standards and trusted by the world’s leading brands, it delivers actionable intelligence that increases availability, improves efficiency, and prevents losses. With tens of thousands of stores live, Nedap provides the real-time backbone that keeps unified commerce moving.

About Nedap N.V.
Nedap is a leader in Digital Twin Technology, bridging the physical and digital worlds in Healthcare, Livestock, Retail and Security. Through our Technology for Life philosophy, we create sustainable, forward-thinking solutions that help people and organizations succeed in an ever-changing world.

Nedap has a workforce of over 1,000 employees and operates on a global scale. The company was founded in 1929 and has been listed on Euronext Amsterdam since 1947. Its headquarters is located in Groenlo, the Netherlands.

About VF Corporation
VF Corporation is a portfolio of leading outdoor and active brands, including The North Face®, Vans® and Timberland®. VF is committed to providing consumers with innovative products that are rooted in performance and elevated design, while delivering sustainable and long-term value for its employees, communities, and shareholders. For more information, please visit vfc.com.

For more information, please contact: 
Ilse Protsman
Marketing Communication Manager
Nedap

+31 6 55 41 51 67
www.linkedin.com/in/ilse-protsman/
ilse.protsman@nedap.com
www.nedap-retail.com

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LINKÖPING, Sweden, April 21, 2026 /PRNewswire/ — International medical imaging IT and cybersecurity company Sectra (STO: SECT B) has signed a contract to deliver its enterprise imaging solution as a fully managed cloud service, Sectra One Cloud, to six NHS Trusts within the north central area of London, which provides care to approximately 1.4 million people.

The six Trusts, four of which already use Sectra’s solution, form the collaborative initiative ImageWise. By consolidating seven separate systems into a single cloud environment, they now create a shared and secure foundation that supports coordinated imaging services for Trusts and care pathways across London.

Sectra One Cloud is fully managed by Sectra, which means Sectra is responsible for all system operation, maintenance, and support. This includes continuous monitoring, optimization, and upgrades, which helps reduce operational risk and supports high availability. The solution is also scalable and can be adapted to increasing imaging volumes, with the flexibility to expand and include additional imaging specialties as needs evolve.

“It’s inspiring to see these hospitals take this important step toward a more secure and connected imaging service. When multiple hospital Trusts move together into a shared cloud environment, it strengthens regional resilience and supports secure collaboration across organizational boundaries, helping improve patient care across London,” says Jane Rendall, Managing Director for Sectra UK and Ireland.

The five-year contract was signed in the third quarter of Sectra’s 2025/2026 fiscal year. The total order value amounts to GBP 15.6 million, all of which is guaranteed. The Trusts will initially utilize the modules for radiology and breast imaging, with the option to expand to additional specialties as needs evolve.

Sectra’s enterprise imaging solution provides a unified strategy for all imaging needs while lowering operational costs. The scalable and modular solution, with a VNA at its core, allows healthcare providers to grow from ology to ology and from enterprise to enterprise. Visit Sectra’s website to read more about Sectra and why it’s top-ranked in “Best in KLAS”.

For further information, please contact: Dr. Torbjörn Kronander, CEO and President Sectra AB, 46 (0) 705 23 52 27
Marie Ekström Trägårdh, Executive Vice President Sectra AB and President Sectra Imaging IT Solutions, 46 (0)708 23 56 10

This information was brought to you by Cision http://news.cision.com.

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Pioneer turns language model development and fine-tuning from a months-long, expert-driven workflow into a single prompt and introduces adaptive inference, a new category in model serving where deployed models continuously improve on live production data, without human intervention.

PALO ALTO, Calif., Apr. 21, 2026 /PRNewswire/ — Fastino Labs, the applied AI research lab behind the widely adopted open source GLiNER model family, today announced the launch of Pioneer, a state-of-the-art language model fine-tuning agent and adaptive inference platform for open source small language models. With Pioneer, any developer can fine-tune and deploy production-ready models like Qwen, Gemma, Llama, Nemotron, and GLiNER with a single prompt.

Pioneer is the first platform to bring adaptive inference to production: a new approach to model serving in which deployed models are continuously and autonomously retrained on their own live inference data, with improved checkpoints automatically validated and promoted over time. The era of “deploy and forget” for language models has arrived.

“We believe that the future will not just be a few large models, but billions of small models working together. However, in reality, building language models today is extremely difficult,” said Ash Lewis, CEO and co-founder of Fastino. “Pioneer collapses that into a prompt. And once your model is deployed, it keeps getting better on its own. For the first time, the model you ship on day one is the worst model you’ll ever use.”

“Frontier model token costs haven’t dropped as expected, making accurate, task-specifc open source models the most important tools in the AI stack.”

Small models, built agentically

Frontier large language models have pushed the boundaries of AI, but most production workloads only need a fraction of their parameters and compute. Fine-tuned small language models consistently match or exceed frontier model accuracy on specific tasks at a fraction of the latency and cost. Fastino believes specialized small models will be the primary building blocks of agentic AI, and that the tooling to build them should be accessible to every developer.

Pioneer delivers this through two agentic modes:

Agent Mode lets users fine-tune and deploy a model in minutes through a simple chat interface. The agent handles synthetic data generation, hyperparameter selection, evaluation, and deployment with no code required.

Deep Research Mode is a fully autonomous fine-tuning agent with web browsing access. Given only a natural-language task description, it discovers training data, runs multiple experiments in parallel, recovers from failed runs, and iteratively improves the model until it reaches an optimal configuration.

Introducing adaptive inference

Pioneer is also the first platform to offer adaptive inference for all deployed models. Pioneer’s agent continuously monitors deployed models through their inference traces, identifies failure patterns, and automatically trains and deploys improved checkpoints.

Across seven benchmark scenarios designed to simulate real-world deployment drift, Pioneer maintained monotonic improvement while naive retraining approaches degraded, with final performance gaps of up to 43 percentage points. To support this research, Fastino is also introducing AdaptFT-Bench, a new benchmark for evaluating autonomous model improvement under realistic production conditions.

“Adaptive inference will soon be a standard feature in model serving,” said George Hurn-Maloney, COO and co-founder of Fastino. “Your production data is the most valuable training signal you have. Pioneer is the first tool actually using it to make your models better, automatically.”

Breakthrough Benchmark Results & Technical Report

Alongside the Pioneer launch, Fastino is publishing a detailed technical report documenting the unprecedented performance gains achieved by its fine-tuning agent, results that redefine what is possible in automated model development. Across a wide range of academic benchmarks, Pioneer’s Research Mode improved accuracy by as much as 83.8 percentage points over base models, with end-to-end runs completing in a matter of hours at a cost measured in tens of dollars. The report also covers the methodology behind the platform’s fine-tuning and adaptive inference systems, and introduces AdaptFT-Bench, a new benchmark for evaluating autonomous model improvement under realistic production conditions.

On a wide variety of academic benchmarks, Pioneer delivered substantial accuracy gains across every base model tested, including a 19.0 percentage point improvement on IFEval with NVIDIA-Nemotron-3B, a 21.4 percentage point improvement on HumanEval with Qwen 8B, a 67.3 percentage point improvement on ARC-Challenge with Llama 3.2-3B, and an 83.8 percentage point improvement on SMS Spam with GLiNER2. End-to-end agent runs completed in an average of 6 hours at a cost of around $35, a fraction of what a senior machine learning engineer would spend on the same workflow.

Backed by leading investors

Pioneer is the latest product from Fastino Labs, which has raised $25 million in total funding across its pre-seed and seed rounds, led by Khosla Ventures and Insight Partners, with participation from M12 (Microsoft’s venture fund), NEA, Valor Equity Partners, and angels including GitHub CEO Thomas Dohmke, former Docker CEO Scott Johnston, and Weights & Biases CEO Lukas Biewald.

Fastino’s open source GLiNER model family has been downloaded more than 6 million times and is used in production by teams at leading Fortune 500 companies.

Availability

Pioneer is available to developers starting today. To learn more or start fine-tuning a model from a single prompt, visit pioneer.ai.

Fastino Labs is an applied AI research lab building small open source models and the infrastructure to make them continuously better in production. Founded in 2024 and based in Palo Alto, California, Fastino is the creator of the GLiNER open source model family and Pioneer, the first agentic fine-tuning and adaptive inference platform. The company is backed by Khosla Ventures, Insight Partners, M12, NEA, and others. Learn more at fastino.ai.

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SOURCE Fastino Labs