Google Cloud and ��ѻ��ý brought together more than 1,800 innovators from around the globe for the Google Cloud Agentic AI Hackathon 

With 93 percent of business leaders  believing that scaling AI agents in the next 12 months will provide a competitive edge, according to the ��ѻ��ý Research Institute, it was paramount for ��ѻ��ý and Google Cloud to come together to help customers harness the promise of multi-agents systems and provide a pragmatic way to deploy them at scale  

In this context, by conducting our proven Google Cloud Hackathon for three years in a row, our motivation was higher than ever to develop a suite of repeatable agents capable of solving real-world business challenges.   

The event used Google Cloud’s latest agentic AI tools available in Vertex AI to deploy multi-agent systems with AgentSpace, Agent Development Kit (ADK), and Agent Engine to build solutions for 23 real-life use cases submitted by ��ѻ��ý clients, following the newly released Agent-to-Agent (A2A) standard. 

Over three weeks, hackers explored how intelligent agents can reason, act autonomously, and adapt to complex environments and how they can be applied to real-world business challenges. 

This was a proving ground for how companies can move from experimentation to execution with agentic AI, while fostering a culture of learning and human-AI collaboration.   

A strategic collaboration for innovation 

The hackathon represented our partnership in action. It leveraged Google Cloud’s advanced AI technologies and ��ѻ��ý’s deep industry expertise to co-create solutions that are not only technically robust but also business ready. 

Our original goal was to develop more than 200 agents on Google’s latest agentic AI platforms. The response exceeded expectations:  256 teams from 39 countries, created more than 320 unique agents during the event. Forty-nine mentors and judges were mobilized to select standout, customer-ready innovations.  

Breakthrough solutions with real-world potential  

The use cases included advanced solutions from a wide range of industries and were judged on innovation, feasibility, and alignment with business needs. 

Here are the nine standout projects from the final round. 

• Aerospace: An agentic AI-powered multi-agent system orchestrates the end-to-end requirement validation process by extracting key data from PDFs and IBM DOORS. It then refines and curates requirement statements, analyzing gaps and inconsistencies, and generates comprehensive, actionable validation reports.
• Consumer products and retail: AI agents optimize procurement, reduce waste, and manage inventory to meet sustainability goals. 
• Automotive and manufacturing: An AI system that automates supply chain and manufacturing to cut delays and costs with proactive decision-making. 
• Consumer products and retail: A retail analytics system examines sales data, advising on new promotion strategies and putting together new marketing material. 
• Banking and insurance: A contact center tool that fetches customers data, suggests live actions, and recommends next steps. 
• Public service: An assistant that simplifies public service access with easy sign-up and step-by-step help. 
• Telecommunications: The AI system detects service issues, recommends fixes, and sends alerts for faster support.
• Banking and insurance: An IT assistant that automates ServiceNow tasks like password resets and triaging to reduce help desk load. 
• Public service: This health tool personalizes check-ins and surveys to monitor patient well-being and trigger alerts. 

Several projects are now advancing to MVP piloting and client co-innovation tracks. The list of agents will also be made available to ��ѻ��ý clients through our Group AI Agents gallery as part of our RAISE (Reliable AI Solution Engineering) agent accelerator. 

Learning through doing 

More than 96 percent of participants completed the Google Agentic AI learning path. The hackathon became a live learning lab, combining structured enablement with hands-on experimentation. 

Bootcamps, workshops, and mentorship from ��ѻ��ý and Google Cloud SMEs ensured that every team had the support they needed, setting ��ѻ��ý as one of the largest Google Agentic enabled partners ready to meet the pressing market demand. 

Unlocking AI at scale  

AI can reimagine business but organizations need to scale to really unlock the full potential and uncover real business benefits. Hackathons are one pathway to AI readiness, by providing training and the opportunity to experiment with the technology as well as build working agents. Implementing agentic AI requires a high level of AI readiness, while creating the right human-AI chemistry to ensure lasting adoption.  

The Resonance AI Framework by ��ѻ��ý helps leaders envision AI’s potential, embed it into the foundation of their operations, and enable human-AI chemistry. It is designed to allow effective interaction between people and intelligent systems, and creates the trust, understanding, and collaboration needed for human and AI agents to build reliability over time, ensuring hybrid teams thrive. This democratization of AI empowers businesses to embed AI into the fabric of everyday operations.����

A culture of collaboration and intrapreneurship 

The hackathon fostered experimentation and cross-functional collaboration. Teams were assembled from different business lines, geographies, and technical backgrounds. This diversity of thought was a key driver of success. 

The hackathon was structured in four phases: 

1. Onboarding, use case definition, and account selection 
2. Client onboarding and business and technical scoping 
3. Training and hackathon program execution 
4. In-production workshops. 

This framework enabled creativity to flourish within clear guardrails and ensured that promising ideas could transition into actionable prototypes. 

Watch the highlights

See the energy, creativity, and impact firsthand

This video features highlights from the live sessions, interviews with participants, and demos of the winning solutions.  

Customizing hackathons: What this means for the enterprise

A hackathon is not only a fantastic innovation hub, it’s also an opportunity to engage our employees from around the world. It provides insights into real-life use cases as well as upskilling knowledge and building culture, and shows how to stay ahead of the competition with new ideas. 

With our breadth of experience, ��ѻ��ý can work with clients looking to explore their own internal hackathon, helping define and prioritize agentic use cases specific to their needs, and upskill employees with challenge-based learning to accelerate skill development and adoption of emerging technologies, empowering teams to experiment and collaborate fosters long-term transformation. 

We can also help explore the possibilities and partner with Google Cloud for strategic collaboration to accelerate business outcomes. 

Looking ahead 

This competition brought together developers, designers, business analysts, and others to deliver multiple points of value: 

• Upskilled ��ѻ��ý talent with hands-on learning and certifications on the latest Google Cloud technologies 
• Expanded our AI agent gallery available to clients 
• Supported AI at scale as part of our Resonance Framework. 

Our goal is now to empower clients to accelerate transformation through intelligent, autonomous systems grounded in human-AI collaboration. A hackathon is just one of the many tools we have available to enable AI-powered enterprises. 

To explore how agentic AI and Google Cloud’s generative capabilities can accelerate innovation in your organization, reach out to our Google Cloud experts. Whether you’re looking to pilot a solution, scale a use case, organize a hackathon, or build a roadmap for transformation, we’re here to help you take the next step, wherever you are in the journey.  

The market reality 

Mobile networks are integral to society. Yet communications service providers (CSPs) face enduring challenges in unlocking the full potential of their infrastructure.  

Despite rapid data growth and geographic expansion, traditional pricing models no longer align with the evolving needs of the industry. To remain competitive, CSPs need innovative ways to monetize their networks and offer differentiated services.  

This calls for new business models that allow for a more dynamic use of network resources, enabling developers to create enhanced applications that leverage advanced network capabilities by decoupling existing stacks. 

The business opportunity 

The next wave of digitalization offers a significant business opportunity by enabling developers and enterprises to access the advanced capabilities of mobile networks through application programming interfaces (APIs). By making high-performing, programmable networks accessible, developers can create applications that enable CSPs to differentiate their offerings, evolve their business models, and generate new revenue streams.  

This shift toward API-driven services empowers developers to dynamically request network resources such as throughput, latency, quality of service (QoS), location, and device and service information which are critical for building innovative high-value applications. 

The market potential for network APIs is immense. As telecom providers expose their network capabilities through APIs, developers will be able to create better applications tailored to specific consumer and industry needs. This will lead to a surge in demand for network services. Research from Omdia predicts that from $161 millon in 2023 to $8.7 billion by 2029. 

For this opportunity to be fully realized, an aggregator platform is essential to ensure global availability and scalability. Integrating network capabilities from individual CSPs has traditionally been a challenge, and a global platform will make network features accessible across various regions and networks. By providing developers the access to on-demand network resources, a global aggregator platform will make it easier for developers to innovate and deliver value-added services to enterprises, regardless of their location or the network they use. 

This new business model creates a win-win-win situation for CSPs, developers, and enterprises. By exposing advanced network capabilities via APIs, CSPs will open new avenues for monetization that will boost the return on their infrastructure investments. Meanwhile, developers gain the flexibility to create applications without needing a deep understanding of 5G networks, driving innovation and accelerating the pace at which new services are brought to market. As the telecom industry embraces this new era of programmability and network differentiation, the opportunity for growth and prosperity is vast, benefiting both industries and society. 

Accelerate the power of network APIs across industries 

As mobile networks become more programmable and open, a massive opportunity is emerging—not just for telecom providers, but for the entire digital ecosystem.  

Network APIs are changing the game in designing real best of quality end-to-end solutions, giving developers and enterprises real-time access to powerful network functions like adaptation of quality of service (QoS), verifying and using location, and device intelligence. But, to truly make these capabilities usable and valuable at scale, domain experts play a critical role in igniting industry innovation—leveraging underlying network capabilities as powerful sources of data and value to drive better use cases and solutions.  

On the other side, CSPs have invested heavily in their infrastructure which can now be made accessible via secured and standardized APIs. With deep experience in working across both IT and NT domains, domain experts can help CSPs standardize and expose network APIs, while also stitching them into end-to-end business solutions across different industries. 

What really drives impact is when these APIs are not just exposed, but also meaningfully integrated into real-world use cases and extend or even simplify daily operations. Take financial services, for example. Fraud prevention APIs that tap into network intelligence can be embedded into banking systems to stop fraud in real time by verifying the device or even the subscriber by using the intelligence from CSPs. It is a way to turn network data into real business value, without requiring banks to become telecom experts. 

In other sectors, like manufacturing, healthcare, or media, network APIs can improve automation, enhance capabilities in remote monitoring, and provide even better immersive experiences by providing adaptable frameworks to change latency and reliability exactly when and where it is needed. 

What’s next: Key takeaways for CSPs to tap the potential of network APIs

1. Standardize and scale API exposure. Standardize and securely expose network APIs across regions to create a consistent developer experience and accelerate adoption. 
2. Invest in aggregator platforms. Establish a global aggregator platform to make network capabilities and data accessible, scalable, and usable across different networks. 
3. Monetize programmability, not just infrastructure. Unlock new revenue streams from programmable services, recurring business models, and value-added API integrations. 
4. Fuel developer innovation with telecom intelligence. Provide developers with access to on-demand network features (e.g., QoS, latency, location, device info) to drive the creation of high-value, next-gen applications. 
5. Empower industry use cases in partnership with domain leaders. Collaborate with domain experts to leverage underlying network capabilities and data to create high-impact industry use cases and solutions. 

Take the leap in network APIs with ��ѻ��ý and Ericsson 

Ultimately, domain experts serve as the bridge between telecom capabilities and industry-specific innovation. By packaging network APIs into practical solutions, they help CSPs to monetize their networks while enabling enterprises or even full industries to move faster, reduce risk, and deliver better services. This new layer of programmability is not just a technical upgrade, but the very foundation of the next wave of mobile innovation. 

Ready to unlock the full potential of network APIs?  

Thanks to its deep telecom expertise and its leadership in all the global industries (telecom, financial services, manufacturing, healthcare, media, retail, and more), ��ѻ��ý supports both CSPs and enterprises design innovative use cases delivering value in the industry-specific context and deploysthem with end-to-end integration, and ecosystem enablement.  

Learn how we can help you accelerate innovation and monetization. 

Telco��ѻ��ý is a series of posts about the latest trends and opportunities in the telecommunications industry – powered by a community of global industry experts and thought leaders

Gen Garage is redefining innovation by harnessing AI to build real-world solutions in areas such as disaster management, sustainable farming, and environmental risk mitigation

By fostering talent transformation and embracing cutting-edge technologies, we empower tomorrow’s professionals to shape the future through hands-on impact. Step into Gen Garage, ��ѻ��ý’s ��ѻ��ý & Data innovation hub — where visionary minds, guided by expert mentors, craft transformative AI-driven solutions at the intersection of talent and technology. Fueled by generative AI, machine learning, and automation, Gen Garage accelerates operational excellence and delivers innovations that drive efficiency, inclusivity, and sustainability. As businesses lean into data-powered insights, our solutions stay aligned with evolving needs — helping organizations stay future-ready, while making a difference today.

DisasterX: AI-Powered Faster and Smarter Response for Disaster Management

DisasterX is a cutting-edge AI-powered application designed to revolutionize disaster response by enabling real-time, adaptive decision-making in high-pressure environments. Leveraging agentic AI, DisasterX overcomes the challenge of delayed responses by autonomously analysing vast amounts of real-time data from multiple sources. This allows for optimized rescue efforts, efficient resource allocation, and enhanced recovery strategies. By continuously learning from past disaster scenarios, DisasterX improves prediction accuracy, minimizes human error, and accelerates response times—ultimately saving lives and reducing economic and environmental impact. Its autonomous capabilities ensure scalability and resilience, seamlessly adapting to both local and large-scale emergencies. As the rise of agentic AI reshapes automation, DisasterX stands at the forefront of intelligent, proactive disaster management, delivering greater efficiency and reliability in crisis situations.

Picture 1 : An AI agent (Image credit – Pixabay)

KisanGPT: AI-Driven ��ѻ��ý for Smarter, Sustainable Farming

KisanGPT is an AI-powered platform designed to revolutionize farming by providing real-time insights on crop health, weather forecasts, and sustainable agricultural practices. Using advanced language models, satellite data, and weather analytics, it offers personalized recommendations to help farmers optimize yields, conserve resources, and tackle climate challenges. The platform supports multilingual access and speech recognition, ensuring inclusivity for farmers across diverse regions. By integrating market trends, government policy updates, and best farming practices, KisanGPT enhances decision-making, boosts profitability, and promotes eco-friendly agriculture. This AI-driven solution not only improves efficiency but also fosters a more resilient and sustainable farming ecosystem.

The Green Horizon: AI-Powered Vegetation Hazard Management

The Green Horizon is an AI-powered solution that detects and manages vegetation hazards near power lines, preventing wildfires, outages, and safety risks. Using satellite imagery, machine learning, and weather forecasting, it provides real-time monitoring, predictive insights, and proactive risk mitigation. With an intuitive chatbot and geospatial analytics, it empowers organizations to optimize resources, reduce costs, and ensure safer, more sustainable infrastructure. By automating hazard detection and integrating user feedback, it enhances decision-making for utility companies and environmental agencies. This innovative approach not only improves operational efficiency but also supports long-term sustainability and infrastructure resilience.

Market Trends / Key Opportunities and Developments:

Gen Garage strategically aligns its initiatives with prevailing market trends to address pressing societal and business needs.

The increasing investment in AI for disaster management presents a significant market opportunity for DisasterX to deliver innovative and data-driven solutions. With the rise of smart cities and the widespread adoption of IoT sensors in disaster-prone areas, vast amounts of real-time data can be leveraged for predictive analytics and rapid response. Gen Garage is at the forefront of this transformation, utilizing AI to enhance disaster preparedness and resilience. As climate change intensifies the frequency of natural disasters, the demand for intelligent, automated response systems continues to grow, positioning DisasterX as a key player in optimizing disaster mitigation and emergency management strategies.

KisanGPT taps into the growing demand for AI-driven agricultural solutions. By leveraging real-time analytics and precision farming techniques, Gen Garage maximizes market opportunities, helping farmers and agribusinesses adopt smarter, data-driven strategies. With advancements in AI and increasing support for sustainable farming practices, the platform positions itself as a game-changer in modern agriculture, driving innovation and long-term growth in the sector.

The Green Horizon initiative taps into the growing need for AI-driven environmental risk management. By integrating geospatial intelligence and predictive analytics, Gen Garage maximizes market opportunities, enabling utility companies and agencies to adopt smarter, data-driven strategies for sustainability and infrastructure resilience.

Gen Garage is where innovation gets hands-on — and where emerging talent learns by doing. By combining mentorship with real-world problem-solving, we’re helping young professionals grow into AI changemakers while delivering solutions that matter. From climate-smart farming to disaster response, the Garage proves that AI for good isn’t just a concept — it’s a daily practice. The challenges may be big, but with the right mix of curiosity, code, and collaboration, we’re building something that lasts. Stay tuned in the next edition of the Data-powered Innovation Review for more recent cases!

Start innovating now –

Empower Future Talent

Get involved in innovation projects that enhance AI skills and leadership capabilities, preparing young professionals for real-world challenges.

Leverage AI for Social Impact

Adopt AI solutions to drive sustainability, inclusivity, and efficiency across industries, from disaster management to smart farming.

Stay Ahead of Market Trends

Engage with cutting-edge technology and AI-driven insights to maintain a competitive edge in an evolving digital landscape.

Interesting read? ��ѻ��ý’s Innovation publication, Data-powered Innovation Review – Wave 10 features more such captivating innovation articles with contributions from leading experts from ��ѻ��ý. Explore the transformative potential of generative AI, data platforms, and sustainability-driven tech. Find all previous Waves here.  Find all previous Waves here.

SaaS management is now a business problem – not only an IT issue

Today’s global economic landscape has made cost pressure concerns a significant topic in the agendas of most businesses, especially CFOs. At the same time, the costs of technologies and their associated supply chains are also rising – in particular for Software-as-a-Service (SaaS) and SaaS software management.

SaaS consumption is special in the sense that decision making is primarily in the hands of business lines and not only for IT organizations.  In fact, only 26.1% of SaaS applications are controlled by the IT organization, while around 70.1% are purchased by lines of businesses.¹ This means that, in reality, everyone is a buyer when it comes to SaaS. 

Considering that SaaS totals 60% of the average software spend budget for many organizations, prioritizing proactive SaaS management to protect operating expenses (OpEx) must now become a standard practice.² 

Going further, this is more than just cost savings and unlocking new value. It’s about addressing potential security and compliance risks that come with unused licenses, which may contribute to sensitive data leakage. It reinforces cybersecurity, while also optimizing management over SaaS tools, apps, and contracts. 

To put it simply: SaaS technologies and services are maturing, but their ways of management remain quite basic in most organizations, compared to what is invested.

The drivers of SaaS cost

SaaS costs are evolving due to several factors occurring side-by-side. The convergence of vendor price hikes, AI-enabled SaaS features, growing popularity in decentralized purchasing, and ongoing license complexity are increasing costs and consumption.

Take a proactive SaaS management approach

This is the moment where a SaaS management solution will facilitate the management of those drivers. Technologies constantly evolve, meaning it’s not enough to conduct cost-out on SaaS as a one-off activity – continuous SaaS optimization is critical to success. It’s imperative that organizations develop an active understanding of the inventory, licenses, and renewals, while keeping a vigilant watch on how these services are impacting costs. 

It’s also important to consider the functional overlaps between SaaS, as well as the limitations linked to a lack of SaaS integration where overlaps do occur. To be specific, where are SaaS applications covering similar business processes and are these teams sharing data to avoid siloes, data duplication, and inconsistencies?  

It requires an understanding down to the level of license type deployed to users, and what business metrics are tied to the value of these licenses by the purchasing department. Additionally, understanding how collaborative models work, so that they can discourage isolated purchasing behaviors.

However, this is only part of the story.

Take a pragmatic SaaS approach

It’s vital to analyze SaaS management needs from a business perspective. There is a critical need for executive sponsorship to understand the waste incurred by ineffective SaaS management.  

A practical first step for SaaS software management that any company can make is a “first-in, first-out” approach. In this case, it means examining the top SaaS contracts by proximity to their renewal, aggregated costs, and determining the volume of unused licenses. It can be tempting to look at the biggest contracts first, but our experience has shown that their complexity and length of negotiation can often degrade significant value from lower tier ones. 

That is why contracts near their renewal dates should be prioritized for review. This helps companies determine if a particular SaaS contract is being used to its fullest potential and if it is worth renewing or adjusting. It helps ease the process as well, given the abundance of SaaS contracts a company may have, which may mean dealing with a handful of renewals every week.

The case for a unified SaaS management strategy

This requires a complete analysis not only of the costs involved, but of the total value that a SaaS application is bringing to the business. If a SaaS app does have overlap between business processes, what is the total value it’s delivering for them?  

For example, if two separate business processes are leveraging a SaaS application, is this building greater value and efficiency for the company, and will the impact of reducing access to the SaaS application negatively impact that value? Will it lead to teams being locked out, unable to access the SaaS application at a critical moment to support another team? These kinds of questions need to be deeply considered during the analysis process. 

But this kind of approach, while highly rewarding, also requires specialized skills that may not be present within an organization or that are not readily available in the market. The best solution is to leverage an ecosystem of partners who can unlock value quickly, while also actively supporting and building additional SaaS management capabilities. 

Start your on-demand SaaS management evolution

Overall, re-thinking SaaS management is one part of a wider challenge in addressing all on-demand technologies, such as Cloud, Gen AI, AI infrastructure, and, of course, SaaS. It’s imperative to re-think this through a business lens to help control cost, consumption, security, and overall usage.

Capital expenditure governance systems are not structured in a way that can optimally navigate these continually evolving technologies. This is an era where everyone is a buyer, and every click is a micro-cost that can (and will) result in large costs later if left unchecked.

We’re ready to discuss how to drive greater value from your SaaS portfolio. We can support you with stronger insights and agile, proactive SaaS management advisory.

It’s time to stop asking, “What’s the cost of a click?”.

It’s time to know the cost of a click.

Reference: _{1. SaaS Management Index, 2025; 2. IDC Spending Guide, 2024}

What festival crowds can teach us about the future of telecoms and the transformation CSPs must embrace. Welcome to part one of our “Engineering Smart Networks & Operations” mini-series.

Imagine you’re at a large music festival with 175,000 other people, wristband blinking as you weave through the main-stage crowd: your phone pings with a route that steers you round a bottleneck, past a freshly stocked water point, and straight to the spot where your friends’ tents glow on the app’s augmented reality overlay.

A tap of the same screen settles your bar tab in seconds. No patchy signal, no queue as card machines need to be reset. The set you’re watching is instantly livestreamed from your handset to your followers, thanks to a creator-grade uplink slice of the network, humming in the background.

Minutes later, a safety alert nudges you aside as security teams, guided by real-time drone feeds on their own event emergency slice, ease a crowd surge. Backstage, VIPs glide through a different digital lane altogether, enjoying 8K video streams and concierge chatbots that never buffer.

These may be presented to the customer as separate perks, but cashless payments, immersive navigation, glitch-free streaming, and iron-clad safety are all threads from one fabric: a single, software-defined network, sliced and stitched on demand to cater for a vast array of personalized services, that people consume eagerly with ease.

Rethinking services 

This hybrid of telecoms and digital technology turns the operator’s infrastructure into an array of different services. Each is tuned to a precise need, yet orchestrated from the same intelligent core, proving that the future of connectivity is less about bandwidth bars and more about the seamless experiences this bandwidth weaves together.

This is certainly not what revellers at the world’s most famous performing arts festival experienced last month. Yet, it may not be long until they can. This example might be theoretical, but it is certainly indicative of what customers want, and therefore what Communication Service Providers (CSPs) want to offer.

This is not just about meeting customer demands to retain revenue streams. It’s more about finding new ones. The raft of new services enabled by 3G and 4G connectivity has not been mirrored by 5G’s arrival. So, whilst the telecommunications industry has had to spend big on networks to provide customers with 5G bandwidth, it has struggled to use that as a springboard to bring brand new services to market that help recoup its investment.

CSPs have realized they must generate revenue in unfamiliar ways if they want to maintain relevance and growth.

Rethinking revenue

We are starting to see what that revenue model looks like in practice. There is already a focus on moving from broad services designed for everyone to access, to bespoke ones for smaller groups with specific requirements. There is a broader move from CSPs dictating what services are available to a responsive agile network that bends to the customer’s whims.

Telecommunications would not be the first infrastructure industry to do this. Energy companies have embraced digital transformation to upend traditional approaches to making money from electricity and gas.

Smart metering and real-time data have enabled personalized tariffs and dynamic pricing. Apps and platforms now help customers monitor their own energy use, allowing providers to offer new service tiers, like home automation integration or carbon offset features. These companies are also supporting customer microgrid participation (so they can charge for grid balancing) or offering buyback schemes to monetize excess generation.

Many of these companies are also expanding beyond energy offerings, providing customers with additional consumer services, like electric vehicles or financial products. 

As it has in energy, doing this in telecommunications brings with it technical consequences for the owners of the existing infrastructure. The technology to enable everything from intelligent network slicing to automated personalization is varied and advanced, but it must somehow become seamlessly integrated into legacy networks.

From data management and cloud services to artificial intelligence and advanced cybersecurity – together these additional technologies represent the single biggest digital transformation in this sector since mobile telephony went mainstream in the 1980s.

How to tackle telecoms digital transformation

Digital transformation won’t be easy. Identifying the right technologies is only part of the challenge. While CSPs are experts in the telecommunications equipment that powers their networks, they often lack the cloud, data and AI expertise as well as experience in agile and DevOps methodologies, needed to effectively splice broader digital technologies into their existing infrastructure. As a result, the industry must find a way to bridge these gaps if it is to navigate this transformation successfully.

That is where working with an ecosystem of partners that understands both sides makes a difference. Organizations that bring in experts who can ‘talk their language’ whilst simultaneously translating others they need to learn pays dividends – cutting the time it takes to transform and optimize. To succeed as the boundaries between telecoms and digital technology become thinner requires CSPs to find partners with practical experience in both worlds.

Over the course of the following articles, we will delve into the most important areas where this transformation needs to be swift, smooth and successful. We believe that CSPs approaching this pivotal transformation should seek guidance from partners with deep expertise in telecommunications, digital technologies, and large-scale digital change – partners who can offer proven digital and engineering methodologies and strategic insight.  

With the right partners, CSPs can unlock the full potential of network transformation – leveraging it to deliver seamless client experiences, reduced costs, and the development of secure, AI-enabled operations.  

We hope this series will help CSPs stay focused on what matters most, by clearly defining core versus contextual priorities.

From infrastructure providers to orchestrators of seamless digital experiences

The music festival example may be theoretical, but the expectation it reflects is very real. Customers no longer measure their experience in megabits per second – they measure it in moments: seamless, personalized, secure, and shareable.

Meeting these expectations requires CSPs to evolve from infrastructure providers into orchestrators of digital experiences. That evolution demands not only bold investment, but the right blend of technical insight and strategic vision.

To��learn��more about how we engineer smart networks and networks operations, contact us at��engineering@capgemini.com

When a car breaks down on a railway crossing, every second counts. A fast-moving freight train might need over a mile to stop, and even a few seconds ’delay in alerting the driver could mean the difference between a safe rescue and a catastrophic collision.

To reduce that risk, ��ѻ��ý Engineering teamed up with Qualcomm Technologies, Inc. to explore how artificial intelligence (AI) can help. The result is a smarter way to monitor rail crossings – using powerful, low-power AI chips embedded at the edge of the railway network.

The rail crossing safety problem – AI to the rescue

Railway operators are under constant pressure to make crossings safer. In the United States alone, incidents at . These incidents are not only dangerous – over 40% involve injuries or fatalities – but expensive, disruptive, and difficult to prevent.

Traditionally, detecting a vehicle stuck on the tracks has involved bulky, centralized systems that rely on cloud computing. They’re often slow to process alerts, rely on constant connectivity, and can be expensive to scale or update.

Working with an American Class-1 freight railroad client, ��ѻ��ý set out to change that. We developed and trained an AI-powered visual monitoring system that uses cameras and machine learning to spot potential dangers in real-time. But to make the system faster, more efficient, and widely deployable, we needed smart hardware.

Enter Qualcomm’s chips – turning AI models into physical, scalable products

That’s where the AI enabled Qualcomm processor comes in. Part of the broader Dragonwing^TM portfolio, it advances intelligence at the edge—delivering efficient, high-performance compute and on-device AI processing with advanced connectivity to transform industrial systems.

��ѻ��ý integrated its AI software into the Inventec , a compact edge AI device powered by the Qualcomm processor.

This brought several improvements.

First, it dramatically reduced the system’s reliance on the cloud. Instead of constantly sending video footage to distant servers for analysis, the AI now runs directly on the device, right at the crossing. That means faster detection, quicker alerts, and fewer chances for network lag to interfere.

Second, the chip’s built-in AI processor – a neural processing unit, or NPU – makes the whole system more efficient. AI analysis that once taxed the device’s memory and slowed performance now runs smoothly, using 33% less memory and 5% less CPU power, all while making AI decisions in just 18 milliseconds per video frame.

Third, the solution can scale. Thanks to support for up to five simultaneous camera feeds, the same system can be adapted for different safety scenarios – not just crossings, but stations, tunnels, and even inside trains.

All of this required some customization of ��ѻ��ý’s original AI model to take full advantage of Qualcomm’s dedicated AI hardware. There was no need to retrain the model, but deep technical work was required to convert it into a format optimized for the Qualcomm NPU, and then to fine-tune it for the new setup.

Why edge AI matters for rail

For rail operators, this kind of edge AI is a practical solution to a longstanding problem that centralized IT systems never quite solved. It’s cheaper, because it reduces cloud usage. It’s faster, because it processes information locally. And it’s more versatile, with the ability to scale and evolve to different scenarios.

��ѻ��ý estimates that performing the video analytics on the edge AI device reduces the total cost of the solution by 30% vs a cloud based alternative.

Perhaps most importantly, it opens the door to rapid innovation. Once we had integrated our initial rail crossing model, ��ѻ��ý was able to build and deploy new applications into the model – including the detection of weapons and violent behavior – in just a few days.

For industries like transportation, logistics, and infrastructure, this shift to the edge is transformational. It allows organizations to respond to real-time events, manage operations more efficiently, and improve safety without relying on massive data centers or always-on internet connections.

What’s next?

��ѻ��ý is now preparing to roll out its Qualcomm-powered monitoring system in live rail environments.

The technology is expected to be deployed in crossings, stations, and other high-risk areas, creating a smarter, more responsive safety net across the rail network. And with scalable platforms like Qualcomm’s Dragonwing, the journey from prototype to production is faster and more seamless than ever.

For more information

Contact ��ѻ��ý Engineering to learn more about our work in the rail sector or read our vision for the rail sector:��Rethinking Rail – The Digital Transformation in Railways.

A detailed technical description of this project by experts at ��ѻ��ý and Qualcomm is available here: .

The automotive industry has a rare opportunity to rethink how value is created and captured across the battery lifecycle.

Those who act on battery traceability and lifecycle innovation today will lead on secured transparency, sustainability, and efficiency tomorrow, assuring long-term competitiveness. The European Union’s Digital Battery Passport (DBP) is more than a compliance checkbox—it’s a strategic enabler. The DBP provides full transparency across the battery lifecycle, turning complex data challenges into competitive advantages.  

With select provisions set to take effect in 2027, the new EU regulation offers automotive players a chance to shape the future of battery value, sustainability, and customer experience. It offers an integrated digital approach that unlocks significant value. Here, we share concrete actions companies can take across four key priorities to harness the opportunities within this new regulatory environment. 

1. Driving supply chain resilience and product innovation 

With the DBP, product traceability is more important than ever. Future-forward companies can strengthen supply chain, sourcing, engineering, and R&D functions with stronger data tracking and sharing. With better visibility into where materials come from and how they’re used, companies can avoid supply shortages, source more responsibly, and make smarter design choices.  

This kind of traceability helps build trust with customers and regulators by showing a clear commitment to sustainability. It also lays the foundation for more sophisticated data-sharing across the value chain. 

2. Augmenting service offers and product performance 

The value of an integrated approach to DBP compliance doesn’t stop upstream. Once the battery is in use, the DBP enables downstream innovation through continuous performance monitoring powered by digital twins – data-driven digital models of each battery in play. By harnessing the insights these models provide, companies will be able to detect issues early and schedule maintenance proactively, while improving battery durability and after-sales operations.  

Real-world usage data can also feed directly into product development, helping to design better batteries. Meanwhile, insights into driving behavior and energy use have the potential to unlock personalized services like smart charging recommendations and energy-efficient routing, enhancing the overall customer experience. 

3. Extending battery life and value for circular growth 

Building on these operational gains, the DBP creates new opportunities for lifecycle value and business model innovation. By leveraging this granular, real-time data on battery condition and usage, companies can accurately assess when a battery is ready for a second life—whether repurposed for another vehicle, redeployed for energy storage, or sent for recycling. This extends asset value while helping manufacturers meet end-of-life obligations more efficiently and responsibly. 

4. Ensuring data security and transparency 

Under the extended producer responsibility framework, manufacturers are responsible for their batteries through the end of the battery lifecycle. Different countries and regulations require different sets of compliance data, provided or collected by stakeholders all along the value chain, from dealers and insurers to consumers, technicians and recyclers. In these complex ecosystems, transparency and security are vital. Robust data security and transparency can help manufacturers ensure accurate, real-time information is provided to every operator in the battery lifecycle.  

Secure, transparent data management also enables first-life producers to seamlessly transfer economic responsibility to second-life producers, a process that requires data certification and verifiable credentials from all parties. This is especially important in the case of electric vehicle (EV) batteries, which frequently have a second life with a different producer. 

5. Maximizing revenue opportunities 

In parallel, the same data enables new revenue models. Using this clear and secure insight into battery health and residual value, companies can offer services like leasing or swapping—innovative solutions that are helping to reshape the EV market and further EV adoption. Additionally, better data means second-life applications become more viable and scalable, shifting batteries from being single-use components to long-term assets that support circular growth. 

Take action today for a more sustainable tomorrow 

At ��ѻ��ý, we help automotive players harness the full potential of the DBP through technology and strategic innovation. Our Product Traceability for Automotive offer combines deep industry expertise with advanced digital solutions to unlock operational gains while working towards a circular, sustainable future.����

The DBP is a catalyst for transformation across the battery value chain. By acting now—and going beyond minimal compliance—companies can turn transparency into a lever for greater efficiency, innovation, and growth.  

Mobility, meet action. 

To learn how to turn DBP data into business value, you can also find us at, Europe’s premier automotive event, where we’ll be demonstrating our unique ability to turn data challenges into long-term competitive advantage.��

^{September 9-12, 2025 | Find us at Hall B1, Booth 22}