Xelpmoc Design and Tech Ltd Management Discussions

Discussion and Analysis

Global economy ^<1>

Global growth is projected to remain at 3.3% for both CY2025 and CY2026, which is below the historical average of 3.7% recorded from CY2000 to CY2019.

Headline inflation is expected to decrease to 4.2% in CY2025 and further to 3.5% in CY2026, with advanced economies likely returning to target inflation levels more quickly than their emerging market and developing counterparts.

In terms of individual country performance, Chinas growth is forecasted at 4.7% year-over-year in CY2025, which is below expectations, while Indias growth has also slowed significantly due to a marked decline in industrial activity. The euro area is experiencing sluggish growth, particularly in Germany, which is lagging behind other countries in the region due to weaknesses in manufacturing and goods exports. Japans economy has seen a slight contraction due to temporary supply disruptions. United States shrank at an annual pace of 0.5% in the first quarter of CY2025 as the trade wars disrupted business.

Despite ongoing global disinflation, some countries are still grappling with persistently high inflation, indicating that progress may be stalling. While core goods price inflation has returned to or fallen below trend levels, services price inflation remains above pre-COVID-19 averages in many economies, especially in the U.S. and the euro area. In response to stubborn inflation, central banks are taking a cautious approach to monetary policy, with some even raising interest rates, reflecting a divergence in monetary policy across different nations.

The IMF projections expect that current policies will continue amidst temporary uncertainties in trade policy. Energy commodity prices are expected to decline by 2.6% in CY2025 due to weak demand from China and strong supply from non-OPEC+ countries, while nonfuel commodity prices are anticipated to rise by 2.5% due to adverse weather affecting food and beverage production.

World trade volume estimates have been slightly revised downward for CY2025 and CY2026 due to increased trade policy uncertainty, although this impact is expected to be temporary, with some trade flows accelerating in anticipation of tighter restrictions.

Indian Economy ^<2>

The Indian economy demonstrated remarkable resilience during the fiscal year 2024-25, maintaining its status as the fastest-growing major economy with a GDP growth rate of 6.5%. This growth was underpinned by robust macroeconomic fundamentals, proactive government policies, and a rebound in private consumption. The services sector, contributing 64.1% to Gross Value Added

(GVA), grew by 7.5%, driven by strong performance in public administration and other services, while the agricultural sector recorded a notable growth of 4.6%, bolstered by favourable weather conditions and government initiatives.

Inflation trends showed a positive shift, with headline inflation moderating to an average of 4.6% from 5.4% in the previous year. This decline was attributed to easing input cost pressures, effective supply management, and the transmission of prior monetary policy actions. Core inflation also saw a reduction, reflecting broad-based moderation across goods and services. The Monetary Policy

Committee (MPC) responded to these dynamics by shifting its stance to neutral and subsequently reducing the policy repo rate by 25 basis points to 6.25%, facilitating improved liquidity conditions in the economy.

In the realm of technology, India is strategically positioning itself as a leader in Artificial Intelligence (AI) Learning (ML). The government has launched initiatives such as the IndiaAI Mission and established centers of excellence focused on AI applications in healthcare, agriculture, and sustainable urban development. These efforts aim to foster innovation and self-reliance in the burgeoning AI sector, which is critical for enhancing productivity across various industries.

Furthermore, The Reserve Bank of India

(RBI) has also taken significant steps to enhance the financial ecosystem by launching repositories for FinTech and regulated entities, capturing essential data on technology adoption, including AI and ML.

Looking ahead, the Indian economy is poised for sustained growth in FY2025-26, supported by a revival in consumption demand, continued government capital expenditure, and the strengthening of consumer and business confidence.

However, challenges such as global trade uncertainties, geopolitical tensions, and financial market volatility remain potential risks to the growth outlook.

The governments commitment to developing foundational AI models and problem-specific solutions will be pivotal in harnessing technology for economic advancement and ensuring long-term sustainability.

Global IT Spend

Worldwide IT spending is projected to reach $5.74 trillion in CY2025, marking a 9.3% increase from 2024, according to Gartner, Inc. This growth reflects the accelerating demand for technology solutions as organizations continue to prioritize digital transformation. As businesses recognize the strategic importance of IT investments, they are increasingly allocating resources toward innovative technologies that enhance operational efficiency and competitive advantage.

The data center systems segment has been a significant driver of this growth, with spending surging nearly 35% in 2024. Although the growth rate is expected to moderate in CY2025, the segment is still set to grow by almost $50 billion, primarily due to server sales. Projections indicate that server sales will nearly triple from over $134 billion in CY2023 to approximately $332 billion by CY2028, with more than $257 billion anticipated in CY2025. This trend underscores the critical role of data centers in supporting cloud services and enterprise applications.

Additionally, software spending is expected to rise by 14% to $1.23 trillion in CY2025, driven by a growing reliance on software solutions. A notable portion of this spending will focus on AI-related projects, contributing an additional $6.6 billion in 2024 and $7.4 billion in CY2025, largely due to Generative

AI products.

The IT services sector is also poised for growth, with an expected increase of 9.4% to $1.73 trillion in CY2025.

This growth reflects the rising demand for managed services and digital transformation initiatives, highlighting the need for organizations to leverage external expertise in navigating complex technology environments. Overall, the outlook for global IT spending remains positive, presenting significant opportunities for innovation and growth.

Worldwide IT Spending Forecast (Millions of U.S. Dollars) Annual Report

	CY2024	CY2024	CY2025	CY2025
	Spending	Growth (%)	Spending Estimated	Growth Forecast (%)
Data Center Systems	318,008	34.7	367,171	15.5
Devices	735,764	6.2	805,722	9.5
Software	1,087,800	11.7	1,239,779	14.0
IT Services	1,587,913	5.6	1,737,754	9.4
Communication Services	1,530,299	2.0	1,596,890	4.4
Overall IT	5,259,784	7.2	5,747,317	9.3

Indian IT Spend ^<3>

Indias IT spending is poised for robust growth, projected to reach $161.5 billion in CY2025, reflecting an 11.1% year-on-year increase. growth trajectory follows a solid performance in the previous year, where spending hit $145.4 billion, marking a 9.8% rise. While the forecast for CY2025 is slightly lower than earlier estimates, the absolute increase underscores the resilience of the Indian IT sector. Key drivers of this growth include software and IT services, which are expected to rise significantly, with software spending anticipated to grow by 16.9% to $17.9 billion and IT services by 11.2% to $30.1 billion.

The global landscape mirrors this trend, with worldwide IT spending projected to reach $5.74 trillion in CY2025, driven largely by advancements in generative AI (GenAI). Gartner forecasts that GenAI will account for over $1 trillion in spending by CY2028, influencing over 50% of software expenditure within application software by CY2026.

As enterprises prioritize and digitization, investments in AI-ready infrastructure are becoming essential. However, it is important to note that while CIO budgets are increasing, much of this growth may be absorbed by rising costs, leading to a disparity between nominal and real IT spending. This dynamic presents challenges for CIOs as they navigate budget constraints while striving to enhance technological capabilities in an increasingly competitive landscape.

Emerging trends in Information Technology_industry

Artificial Intelligence

The artificial intelligence (AI) market is poised for substantial growth, with projections indicating an increase from US$ 757.58 billion in CY2025 to approximately US$ 3,680.47 billion by CY2034, reflecting a robust CAGR of 19.20%. North America currently dominates the market, contributing over 36.92% of the share in CY2024, driven by significant investments from leading tech companies and research institutions. The regions commitment to innovation, particularly in robotic technologies, positions it as a leader in AI advancements, which are essential for transforming various sectors, including manufacturing and everyday life.

The Asia-Pacific region is emerging as the fastest-growing segment, with a projected CAGR of 19.8% from CY2025 to CY2034. Government initiatives supporting AI-driven health systems and rapid digitalization are key factors propelling this growth. The widespread adoption of AI across diverse sectors such as healthcare, finance, and transportation underscore the technologys critical role in enhancing operational efficiency and service delivery.

As startups and established companies alike leverage AI solutions, the region is set to become a significant player in the global AI landscape.

Europe is also expected to experience notable growth in the AI market, particularly within the transportation and research sectors. The increasing utilization of AI technologies, coupled with stringent regulations aimed at ensuring safety and compliance, is fostering a conducive environment for market expansion. As organizations across Europe integrate AI into their operations, the region is likely to witness enhanced productivity and innovation, further contributing to the global AI ecosystem.

In conclusion, the AI market is characterized by rapid technological advancements and increasing investments from major players. The convergence of digital technologies and AI is reshaping industries, driving efficiency, and fostering new business models. As organizations continue to adopt AI solutions, the market is expected to attract new entrants, resulting in a dynamic and competitive landscape. Favourable government initiatives and strategic collaborations will further bolster the growth trajectory of the AI market, positioning it as a cornerstone of future economic development.

Manufacturing

The global market for AI in manufacturing is set to grow from US$ 3.2 billion in CY2023 to US$ 20.8 billion by CY2028, with a remarkable CAGR of 45.6%. This growth reflects AIs transformative impact on the sector, driven by Industry 4.0 principles such as smart automation and data-driven decision-making. AI enhances production efficiency, reduces operational costs, and improves product quality by analysing real-time data, predicting machine failures, and automating tasks. By 2025 end, AI will be further integrated into manufacturing, leading to the emergence of smart factories that are more adaptive, resilient, and competitive.

AI TRENDS IN MANUFACTURING

Impact of Defects in Manufacturing

In the manufacturing sector, even

minor defects can result in substantial

losses, including wasted materials,

costly recalls, and damage to brand

reputation. Historically, quality control

has depended on human inspectors

and basic automated systems, which

are increasingly proving to be inefficient

and error prone. However, AI-driven

quality control, utilizing advanced image

processing and computer vision, is

revolutionizing defect detection, product

verification, and real-time production line

optimization.

Importance of Real-Time

Image Processing

Real-time image processing is crucial in high-speed manufacturing environments that produce thousands of units per hour. Traditional inspection methods often struggle to consistently identify defects at this scale. AI-powered systems provide instantaneous analysis of products as they move along the production line. Computer vision algorithms can scan items in milliseconds, detecting surface imperfections, structural inconsistencies, and misprinted labels. These systems employ object detection to identify physical defects and optical character recognition (OCR) to verify essential text-based information, such as expiration dates and barcodes.

Reducing Human Error and Enhancing

Efficiency

AI significantly reduces human error and waste in quality control processes. Even the most skilled inspectors can overlook details due to fatigue and distraction during repetitive tasks. In contrast, AI maintains a consistent level of accuracy, analysing each unit with precision regardless of production volume. Furthermore, AI-powered predictive maintenance enhances operational efficiency by analysing real-time data to forecast equipment failures before they occur. This proactive approach minimizes costly downtime, reduces unnecessary repairs, and extends the lifespan of machinery.

Advancements in Robotics and Safety

Additionally, AI-driven robotics are transforming manufacturing processes beyond basic tasks. With capabilities in real-time analysis and perception, modern robots are enhancing assembly, packaging, sorting, and quality control. This advancement not only boosts productivity but also improves workplace safety by implementing real-time monitoring systems for hazard detection and unauthorized personnel identification.

AI in Supply Chain Management

In supply chain management, AI is reshaping demand forecasting and inventory management, critical components for operational success. Traditional forecasting methods often rely on historical data, which can overlook unexpected disruptions and market fluctuations. AI-driven demand forecasting leverages vast amounts of real-time information to predict product demand with greater accuracy, enabling manufacturers to optimize inventory levels and enhance supply chain resilience. By integrating AI into these processes, companies can reduce costs, improve operational efficiency, and better navigate the complexities of modern manufacturing.

Financial Services

The global market for generative AI in financial services is projected to reach

US$ 1.95 billion in CY2025 and is expected to exceed US$ 15.69 billion by 2034, reflecting a robust compound annual growth rate (CAGR) of 26.29% from 2025 to 2034.

As technological advancements and economic uncertainties continue to transform the financial sector, coupled with significant changes in consumer behaviour and regulatory demands, CY2025 is anticipated to present both challenges and opportunities for banking and financial services.

Midway through the decade, established financial institutions are experiencing unprecedented competition from challenger banks and fintech disruptors, prompting them to rapidly adopt AI solutions to improve customer experience.

AI TRENDS IN FINANCIAL SERVICES

Automation and Operational

Efficiency

By CY2025 end, the automation of back-office functions such as transaction processing, reconciliation, data entry, compliance, and fraud detection will become standard practice. Financial institutions that have achieved a high level of AI maturity will transition towards more advanced applications, including fully autonomous decision-making and real-time risk assessment. This shift promises significant efficiency gains and reduced operational costs, but it also raises challenges related to customer data privacy and ethical AI usage.

Enhanced Customer Service through AI Assistants

The role of autonomous chatbots and AI assistants in customer service is rapidly evolving. By CY2025 end, these technologies will provide 24/7 support and manage increasingly complex interactions. The next generation of automated customer service agents will not only respond to inquiries but will also anticipate customer needs, offering proactive support and creating a more personalized experience.

Generative AI in Financial Planning

Generative AI will play a crucial role in financial planning and advisory services.

By leveraging customer behavioural data and advancements in natural language processing (NLP), AI agents will deliver tailored advice on savings, pensions, and investments. This virtual financial advisory capability will empower customers to make informed decisions that align with their individual financial goals.

Demand for Sustainable

Finance Products

As consumer demand for sustainable and ethical financial products grows, financial institutions will need to adapt by offering investment opportunities in renewable energy and ESG-focused funds. Transparency regarding data such as energy consumption and carbon emissions will be essential, enabling customers to understand the environmental impact of their financial choices. Institutions that excel in this area will position themselves as valuable partners in their customers sustainability journeys.

Central Bank Digital Currencies (CBDCs)

The development of Central Bank Digital

Currencies (CBDCs) is gaining momentum, with countries like China, Brazil, and those in the Eurozone advancing their initiatives. CBDCs represent a secure, government-backed alternative to cryptocurrencies, providing the benefits of blockchain technology while mitigating risks associated with volatility and fraud.

This trend reflects a broader shift towards a more digital global financial system.

Quantum Computing in Finance

While still in experimental stages, the application of quantum computing in financial services is attracting significant interest and investment. By 2025, we may witness initial operational deployments of quantum technologies, which have the potential to revolutionize areas such as risk analysis, fraud detection, automated trading, and cybersecurity. The unique capabilities of quantum computing could enable financial institutions to perform complex calculations at unprecedented speeds.

Rise of Next-Gen Banking Services and

Super-Apps

The convenience of managing financial activities through centralized apps and digital platforms is drawing customers away from traditional banks. The emergence of fintech startups and super- apps, which combine payment services with lifestyle functionalities, is accelerating this trend. Financial institutions must adapt to this evolving landscape to remain competitive.

Regulatory Landscape and

AI Oversight

As the adoption of AI in financial services expands, so too does the need for regulatory oversight. By CY2025 end, new legislation will likely emerge to promote transparency and mitigate risks associated with bias and unethical AI practices. Navigating this evolving regulatory environment will be a critical challenge for banks, fintech startups, and financial service providers.

Cyber Preparedness and Resilience

In an era marked by increasing cyber threats, geopolitical tensions, and economic uncertainty, financial institutions must prioritize operational resilience. Establishing robust contingency plans will be essential for maintaining business continuity in the face of disruptions. Demonstrating resilience will not only build consumer trust but also ensure the survival of financial organizations amid various existential threats.

The global market for AI in aerospace and defense is estimated to be valued at

US$ 25.43 billion in CY2024 It is expected to increase to US$ 27.95 billion in CY2025 and is projected to reach approximately US$ 65.43 billion by CY2034. This growth represents a compound annual growth rate (CAGR) of

9.91% from CY2024 to CY2034.

The integration of artificial intelligence in the aerospace and defense sectors involves the adoption of AI systems by companies to accelerate their design cycles, a critical phase prior to manufacturing and final deployment in coordination with air traffic control.

The application of AI in this market encompasses manufacturing and maintenance processes, including factory automation, supply chain optimization, and the analysis of large data sets to assist maintenance engineers.

Embracing Digital Engineering and AI

The integration of digital engineering has been a focal point for the industry, supported by strategies from the

Department of Defense (DoD) and the emergence of innovative startups. However, challenges remain, particularly in achieving interoperability among tools and vendors. The digital supply chain often encounters breakdowns, especially among tier-two and tier-three suppliers who struggle with adoption. While AI holds significant promise for transforming operations, its implementation is still met with some hesitation.

AI-Driven Data Management for Actionable Insights

In an unpredictable global environment, organizations must prioritize immediate, data-driven decision-making. The key challenge lies in ensuring interoperability across various data analytics systems and platforms. Secure and scalable data sharing both internally and with industry partners, government agencies, and allies is crucial for success.

To leverage data as a strategic asset, organizations need to dismantle silos, aggregate information from diverse sources, and provide real-time, actionable insights that are accessible to users at all skill levels. The ability to rapidly process vast amounts of information can significantly influence operational success

AI Applications Across Aerospace and Defense

AI is making substantial inroads across various domains within aerospace and defense:

• Aircraft Design and Engineering: Generative design tools are being utilized to optimize component weight and structure, while AI-driven simulations and digital twin technologies are reducing the need for physical prototypes. Notable examples include the Airbus AI-optimized cabin partition and Boeings machine learning applications in 787 production.

• Manufacturing and Smart Factories:

Predictive analytics are employed to monitor part and tool wear, preventing machine downtime. Computer vision technologies enhance quality assurance through automated inspections, and adaptive robotics, powered by reinforcement learning, facilitate precision assembly.

• Avionics and Flight Systems: Real-time decision support tools assist pilots with optimized rerouting, while autonomous navigation systems provide landing and take-off assistance. Enhanced Human-Machine Interfaces (HMIs) incorporate natural language interaction to improve user experience.

• Predictive Maintenance: AI technologies enable sensor fusion and anomaly detection for engine health monitoring, while fleet-wide learning systems forecast maintenance schedules, reducing Aircraft on Ground (AOG) incidents and generating cost savings.

• Mission Systems and Defense

Applications: AI is employed for target recognition, combat simulation, and real-time decision aids. AI-enabled unmanned aerial vehicles (UAVs) and loyal wingman systems are becoming increasingly prevalent, alongside simulation-based war gaming and algorithmic warfare planning.

The global market for artificial intelligence (AI) in cybersecurity was valued at US$

24.82 billion in CY2024, increasing to US$ 29.64 billion in CY2025, and is projected to exceed US$ 146.52 billion by CY2034.

This growth reflects a robust compound annual growth rate (CAGR) of 19.43% from

CY2024 to CY2034.

The demand for AI in cybersecurity is expected to rise during the forecast period, driven by the expansion of 5G technology and the increasing need for cloud-based security solutions among small and medium-sized enterprises. AI is becoming increasingly popular in the cybersecurity landscape as organizations seek to protect sensitive information. End users are anticipated to adopt AI-driven cybersecurity measures to address security challenges and detect emerging threats that can arise at any time, contributing to the steady growth of this market.

AI TRENDS IN CYBERSECURITY

Enhanced Physical Security through AI

AI-powered surveillance systems are revolutionizing physical security by providing advanced capabilities beyond traditional recording. These systems utilize real-time object detection, motion tracking, and facial recognition to automatically identify potential threats and suspicious activities. For instance, AI can detect unattended bags in public spaces, unauthorized access in restricted areas, and unusual behaviour patterns in crowded environments. This proactive approach to security enables organizations to respond swiftly to potential risks.

Advanced Digital Surveillance

In the digital realm, businesses increasingly rely on AI to monitor vast amounts of online content. AI-driven digital surveillance is essential for detecting fraudulent transactions, preventing identity theft, and analysing suspicious behaviour in real time. Machine learning models continuously adapt to new threats, improving detection accuracy and enabling organizations to stay ahead of cybercriminals.

Revolutionizing Cybersecurity Measures

AI is fundamentally changing how companies safeguard their data. Traditional static security measures are being replaced by AI-driven solutions that analyse millions of data points to detect anomalies, identify cyber threats, and predict potential breaches before they occur. AI-powered threat intelligence platforms can recognize patterns in hacking attempts, flag phishing attempts, and automate responses to cyberattacks, significantly enhancing an organizations defensive capabilities.

Automated Monitoring and

Rapid Response

One of the key advantages of AI in surveillance is its ability to monitor video feeds continuously, flagging suspicious activity in real time. In high-traffic areas such as airports and train stations, AI systems can detect unattended bags, unusual movements, or aggressive behaviour. In retail environments, AI can help prevent theft by identifying suspicious actions, such as individuals attempting to conceal items. This automated monitoring reduces reliance on human operators and ensures that security teams are alerted instantly, minimizing response times and potential damage.

Object and Individual Detection in High-Risk Areas

AI-driven video analytics enhance security in high-risk locations by recognizing specific objects, such as weapons or unauthorized vehicles. When ethically applied, facial recognition technology can verify identities and detect individuals on watchlists, making it particularly valuable in sensitive environments like banks, stadiums, and government buildings.

Predictive Capabilities and

Pattern Recognition

AI systems excel at analysing large data sets to establish normal behavioural patterns. By continuously learning from new data, these systems can differentiate between routine activities and suspicious deviations. For example, in office buildings, an AI system might recognize typical employee entry patterns. If an individual attempts to access the building through a restricted entrance at an unusual time, the system would flag this as an anomaly and alert security personnel.

Lower False Positive Rates and Improved Accuracy

Traditional security systems often suffer from high false alarm rates due to rigid rule-based programming. AI-based anomaly detection significantly reduces false positives by considering multiple contextual factors before flagging an event as suspicious. This leads to more accurate threat identification and fewer unnecessary disruptions, allowing security teams to focus on genuine threats.

Proactive Threat Prediction

AIs ability to analyse historical data enables organizations to predict potential security breaches before they occur. In cybersecurity, AI can identify early signs of phishing attacks or unauthorized access attempts based on past incidents. In physical security, AI can forecast crime-prone areas by analysing historical events, allowing organizations to adjust their security measures proactively.

The global machine learning market was valued at US$ 93.95 billion in CY2025 and is projected to exceed US$ 1,407.65 billion by CY2034, reflecting a robust compound annual growth rate (CAGR) of 35.09% from

CY2025 to CY2034.

Over the past decade, machine learning

(ML) has advanced at an extraordinary pace, becoming a vital component across various industries, including healthcare, finance, education, and artificial intelligence (AI) development. ML is poised to transform how we engage with technology, analyse data, and address complex challenges. However, this rapid evolution brings with it significant challenges and opportunities that will influence the future of this groundbreaking technology.

AI TRENDS IN MACHINE LEARNING finance, and the Internet of

AI-Augmented Software Development

Machine learning is increasingly being leveraged to automate various software development tasks, including code generation, debugging, and testing. AI-powered tools such as GitHub Copilot and Tabnine are assisting developers in writing optimized code, which reduces development time and minimizes errors. Going forward,AI-assisted programming is anticipated to become even more sophisticated, facilitating faster software innovation across industries.

Explainable AI (XAI) and Ethical Machine Learning

The emergence of black-box AI models has raised concerns regarding transparency and accountability in machine learning.

Explainable AI (XAI) aims to enhance the interpretability of ML decisions, ensuring that stakeholders understand how AI reaches its conclusions. With tightening AI regulations, organizations will be compelled to adopt ethical AI frameworks to mitigate bias, promote fairness, and build trust in automated decision-making processes.

Federated Learning and Decentralized AI

Federated learning represents a significant advancement in AI, allowing models to be trained across multiple devices without the need to share raw data. This decentralized approach enhances privacy and security, making it particularly valuable in sectors such as healthcare, Things (IoT), where sensitive data cannot be freely exchanged. In future, federated learning is expected to play a crucial role in AI-driven applications that require real-time data processing while maintaining enhanced security.

AI for Edge Computing and IoT Integration

With the growing proliferation of IoT devices, machine learning is increasingly moving towards edge computing, where data is processed locally on devices rather than relying on cloud-based servers. This trend reduces latency, improves efficiency, and enables real-time decision-making in applications such as autonomous vehicles, smart cities, and industrial automation. The integration of AI with edge computing is set to enhance operational capabilities and responsiveness.

Reinforcement Learning in Real-World Applications

Reinforcement learning (RL), which was once primarily utilized in gaming and robotics, is now being applied across various industries, including finance, logistics, and autonomous systems. By 2025 end, RL is expected to be instrumental in optimizing decision-making processes in dynamic environments, allowing AI to learn from real-world interactions and adapt to changing conditions effectively.

Quantum Machine Learning (QML) on the Horizon

Quantum computing holds the potential to revolutionize machine learning by significantly accelerating complex calculations. Although still in its nascent stages, quantum machine learning (QML) is anticipated to gain traction in CY2025, with researchers exploring its applications in cryptography, material science, and AI optimization. However, practical implementation remains a challenge due to current limitations in quantum hardware.

The global metaverse market is estimated to touch US$ 183.16 billion in CY2025 and is projected to exceed US$ 2,369.70 billion by CY2033, reflecting a compound annual growth rate (CAGR) of 37.70% during the forecast period from CY2025 to CY2033.

As we look towards the future, the metaverse is emerging as a transformative digital landscape that promises to reshape various industries, including marketing, entertainment, and business operations. With a projected market size of US$ 2,369.70 billion by CY2033, the metaverse is poised for significant growth, driven by advancements in technology and changing consumer behaviours. This section outlines key trends that are expected to define the metaverse landscape in the coming years.

TRENDS IN MACHINE LEARNING

Decentralized Virtual Economies

The integration of blockchain technology, digital assets, cryptocurrencies, and NFTs is enhancing trust and ownership in virtual economies, enabling secure transactions and new business models.

AI-Powered Avatars and Virtual Assistants

Intelligent AI avatars will enhance user experiences by providing assistance and engaging in meaningful interactions, adapting to individual preferences for a more immersive experience.

Augmented Reality (AR) and Virtual Reality (VR) Integration

The convergence of AR and VR technologies will enrich user interactions in both digital and physical environments, facilitating interactive educational experiences and retail innovations.

Virtual Workspaces and Collaboration Tools

The metaverse will advance virtual office environments, allowing seamless collaboration and enhanced productivity through immersive tools that simulate physical office settings.

Gaming Integration and

Cross- Platform Experiences

The gaming industry will drive metaverse development, creating cross-platform experiences that blend traditional gaming with dynamic virtual interactions.

Sustainable Practices and

Green Technology

Increasing awareness of climate change will prompt developers to adopt eco-friendly practices, utilizing renewable energy sources and creating solutions reduce carbon footprints.

Virtual Real Estate Expansion

The virtual real estate market will grow as individuals and businesses invest in digital properties for various purposes, with architects and designers creating unique environments to enhance user engagement.

Business Overview

At Xelpmoc Design and Tech Limited, we offer technical and expert consulting services to corporates, startups, and the government. We are adept at developing next-generation Artificial Intelligence and Machine Learning technology and specialize in Natural Language Processing and Data Analytics.

We collaborate as a Technology Partner and Consultant, working with multiple clients across the spectrum, including governments, businesses, individuals, and startups, helping them optimize their data. Our subsidiary company is Signal Analytics Private Limited.

Going forward, we will focus more on our technology-driven product suite. We are actively seeking to onboard new clients and are currently in discussions with a few prospective customers. We deliver a diverse range of technology-driven products, services, and solutions, including managed services and advanced technology platforms. We are focusing on creating innovative solutions tailored to meet the needs of various industries, including legal tech, banking, financial services, insurance (BFSI), and real estate.

Our integrated service platform allows us to reduce development and maintenance costs by leveraging our collective resources and expertise.

Product Suite

AI and ML Solutions: Xelpmocs product suite includes AI-driven applications designed to automate and enhance processes within organizations. These solutions aim to improve accuracy and efficiency, particularly in document processing and data analysis.

ElderTech: We have made a significant entry into the ElderTech space by introducing our first SaaS product tailored for senior living operators. This end-to-end platform supports both real estate developers and specialized senior care providers, enabling them to enhance operational efficiency, streamline service delivery, and improve the overall experience for residents. As Indias aging population grows, we recognize the increasing demand for technology-driven solutions in senior living.

• Legal Tech: In the legal sector, we are developing advanced technology solutions designed to streamline legal processes for law firms and corporate legal departments. Our product suite includes document automation tools, e-discovery platforms, and case management systems that leverage AI and machine learning. These solutions allow us to significantly reduce the time spent on manual tasks, save 80-90% on contract management, and identify risks early, ultimately lowering legal operational costs and enhancing compliance monitoring.

• BFSI Tech: Our BFSI technology product is transforming how the banking, financial services, and insurance (BFSI) sector manages its documentation and processes. By automating the identification and classification of various document types, we minimize the time spent on manual sorting and reduce human error, ensuring compliance with regulatory standards. In the insurance sector, our product accelerates claims processing through automated data extraction and validation, leading to quicker turnaround times, enhanced customer satisfaction, and significant cost savings.

FY25 Financial performance snapshot

Total operating revenue was _ 39.0 million in FY25 as compared to _ 64.7 million in FY24. Adjusted Operating EBITDA was

_ (73.2) million in FY25 as compared to

_ (149.1) million in FY24. The fair value of the Companys portfolio investments as on March 31, 2025, stands at ~_ 631.8 million as compared to ~_ 582.9 million as on March 31, 2024. Xelpmoc has served 64 clients in FY25 as compared to 62 clients in FY24. The Company has a strong and qualified team of 50 members.

Highlights of the year ended March 31, 2025

The Board of Directors of the Company approved the proposal of sale/disposal of equity investment of 1,22,232 Equity Shares of the face value of Re.1/- per share in Fortigo Network Logistics Private Limited, at a consideration of

Rs.1.30 crores

The Board approved further acquisition of 8,481 shares in One Point Six

Technologies Private Limited (OPSTPL), updated shareholding of 7.9% on a Fully diluted basis by way of conversion of receivables of Rs. 1.20 crores into equity. OPSTPL i.e. Pencil, enables authors to publish books for free across multiple channels worldwide in both e-book and paperback format, in every language in the world, to understand how readers read their books and make iterative changes, to continuously improve their products to create more commercially successful products.

The Board approved the proposal of participate in buy back offer of Mayaverse

Inc, Associate entity, to the extent of entire 2,500 shares held in Mayaverse Inc and subsequent to acceptance of such shares, Mayaverse Inc, ceased to be Associate entity of the Company.

The Board of Directors of the Company approved the proposal of sale/disposal of preference shares investment of 1,61,550, 0.01% Optionally Convertible Preference

Shares (OCPS) and 6,443, 0.01% Pre

Series A Cumulative Compulsorily

Convertible Preference Shares (CCPS) of the face value of Re.1/- per share, in Firstsense Technology Private Limited, at a consideration of Rs.1,67,993/-.

Material events occurring after the year ended March 31, 2025

The Board of Directors of the Company approved the proposal for part sale / disposal of its investment in Mihup

Communications Private Limited ("Mihup").

As per the proposed Share Purchase Agreement, 11,782 Series Seed CCPS of the face value of Re.1/- per share at a price of Rs.8,487.32/- per share aggregating to total consideration of Rs. 100 million will be transferred.

Our Competitive Strengths

Comprehensive Offerings and

Support

We deliver a wide range of technology-driven products, services, and solutions, including managed services, integration solutions, and advanced technology platforms. Since our inception, our portfolio has grown to include data science, query optimization, and rapid iteration services. We assist entrepreneurs in launching as well as scaling their businesses.

Access to Expertise

Our leadership team and founding members possess extensive knowledge from various sectors, including finance, retail, media, and entertainment. This expertise is further enhanced by specialists from different industries who contribute their insights. We have developed a network of independent industry experts who collaborate with us as consultants, providing guidance to our clients on the necessity for specific technological and data-centric services and our capability to deliver them.

Client-Focused Organizational Structure

Our Company is organized around our solution offerings, allowing clients to access our comprehensive suite of services and the specialized expertise within each area, regardless of project location. We prioritize building relationship-driven engagements with our clients through our key personnel, aiming to foster long-lasting partnerships. Our integrated service platform enables us to reduce development and maintenance costs for our clients by utilizing our collective resources and expertise to a wide range of services.

Skilled Management and Innovative Culture

Our executive team consists of individuals who have held senior positions in prestigious companies across various sectors. They play a vital role in fostering a culture that promotes creativity, proactivity, and collaboration. Furthermore, we have established talent development programs designed to identify and cultivate the next generation of leaders within our organization.

Our Growth Strategies

Corporate engagements

We have successfully completed projects for various corporations, tackling challenges such as fraudulent data detection, website and application enhancement, and supply chain optimization. We aim to build on these achievements and pursue further collaborations with these clients on projects that offer greater value.

Entrepreneurial partnerships

We serve as a technological co-founder for the startups we partner with, aiding in the development of their products tech features and capabilities. We also assist in connecting them with large enterprises for product marketing, with the expectation that our startup partners can meet the needs of an additional 2.5 billion people globally. Our track record includes significant success stories, and we look forward to engaging with more visionary entrepreneurs.

Domain and technology advancement

We are committed to ongoing investment in data science, deep learning, and AI. We aim to enhance our domain expertise and tech prowess by identifying high potential businesses and recruiting talented individuals in these areas who can contribute to our products and solutions, thereby solidifying our market credibility.

Market expansion initiatives

Our Singapore presence is geared towards serving the African and Latin American markets. Each of our international locations is well-positioned for substantial growth in the coming years.

Outlook

Our strategic emphasis will sharpen on our core competencies in data science, artificial intelligence, and machine learning. We plan to enhance Xelpmocs proprietary services and products to better meet the needs of our corporate clients. By focusing on in-house product development, we aim to position ourselves as a leader in technology solutions, providing our clients with innovative tools that drive operational excellence and foster growth. We are actively seeking to onboard new clients for these products and are committed to achieving profitability through these products while maintaining a strong focus on our customers needs and market demands. Our investment portfolio encompasses a diverse range of startup companies. Although these startups are designed to operate efficiently with lean structures from the beginning, they are currently in the

Financial Performance

Rs in millions	Q425	Q325	QoQ%	Q424	YoY%	FY25	FY24	YoY%
Revenue from Operations	7.1	8.3	(14.8)%	9.1	(22.5)%	39.0	64.7	(39.7)%
Other Income	1.1	2.3	(50.4)%	3.9	70.2%	9.0	15.1	(40.1%)
Total Income	8.2	10.6	(22.5)%	13.0	(36.9)%	48.0	79.8	(39.8)%
Adjusted Operating EBITDA	(15.3)*	(19.8)*	NA	(49.2)*	NA	(73.2)*	(149.1)*	NA
% of Operating Revenue	NA	NA	NA	NA	NA	NA	NA	NA
PAT	(18.4)	(20.9)	NA	(60.4)	NA	(80.7)	(138.9)	NA

The fair value of our investments in our clients as on March 31, 2025 stands at approximately Rs 631.8 million

* Adjusted Operating EBITDA is after excluding ESOP expenses of Rs0.1mn, Rs0.1mn, Rs 1.9mn, Rs 0.4mn and Rs (32.2)mn in Q4FY25,

Q3FY25, Q4FY24, FY25 and FY24 respectively

Key Financial Ratios

	FY25	FY24	% change
D/E Ratio	-	-	-	Debt free company
Current Ratio	3.67	3.49	5%	Due to Utilisation of Preferential Allotment funds for working capital
				purposes
Inventory Turnover Ratio	-	-	-	No Inventory
Debtors Turnover Ratio	3.72	1.14	226%	It indicates that the receivables realisation period has
				increased due to outstanding receivables from opening
				debtors
Interest Coverage Ratio	-76.64	-59.56	-	Negative as there is no debt
Operating Profit Margin	-2.04	-1.90	-	Negative as the Company has incurred loss during the year
Net Profit Margin	-2.07	-2.15	-	Negative as the Company has incurred loss during the year

early phases of revenue generation and continue to require capital. As a result, without timely financial support, they may face challenges in sustaining their operations. Given this context, we are adopting a cautious approach regarding new startup engagements, choosing to collaborate only with those startups that demonstrate a compelling opportunity and significant revenue potential.

Risk Management

The Board of Directors regularly evaluates the Companys business risks and formulates strategies to address them. The Senior Management team, led by the Managing Director, plays an active role in risk management by implementing appropriate mitigation measures.

Key Business Risks and Mitigation Strategies:

Market Risk

Fluctuations in local and global economies, political instability, and regulatory changes can impact the technology sector. An industry downturn could negatively affect our operations. To mitigate market-specific risks, the

Company plans to diversify its presence and client base across various regions and sectors.

Competition Risk

We operate in a highly competitive market that is experiencing an influx of new entrants. To maintain our competitive advantage, it is essential for companies to adopt cutting-edge technologies and develop innovative applications for clients.

Our Company differentiates itself through our extensive expertise, advanced technology solutions, and customer-centric offerings, which enable us to withstand competitive pressures.

Technology Risk

The rapid pace of technological advancement, changing business models, and the introduction of new software and products require organizations to adopt advanced technologies to improve efficiency. The success of a tech service provider depends on its ability to deliver effective solutions to clients. To manage this risk, our Company continuously refines our services and solutions to meet the evolving needs of the industry.

Talent Risk

The technology sector may face a significant talent shortage. At Xelpmoc, we consider human capital our most valuable asset. Recognizing its importance to our success, we strive to create an inclusive and diverse work environment while offering attractive benefits to our employees. We foster a culture of innovation and entrepreneurship and provide opportunities for employee training and development.

Human Resources

Xelpmoc recognizes that exceptional talent is a crucial driver of business growth. As such, the Company is dedicated to fostering a supportive environment that promotes the professional development of its employees while aligning with organizational goals. A variety of learning and development programs are offered to equip employees with the necessary skills and knowledge. The Companys HR strategy focuses on attracting, recruiting, training, and retaining top talent to ensure high performance.

Significant emphasis is placed on cultivating a workplace culture that values diversity, inclusivity, creativity, empathy, and respect. Furthermore, the Company aims to inspire enthusiasm among its workforce and maintain high levels of engagement through employee-centric events and competitive reward systems.

As of March 31, 2025, the Companys team comprised 45 members, including full-time employees, interns, and consultants.

Internal Control Measures

The organization has implemented strong internal control systems and a systematic internal audit process to safeguard its assets and ensure the accuracy and reliability of financial and operational data. Internal audits are conducted by an external firm of Chartered Accountants, and their reports are submitted to the Audit Committee of the Board of Directors. Additionally, we utilize a monthly business review process as a critical operational check, evaluating the performance of various units and making necessary adjustments.

A capital expenditure control system is also in place to monitor investments in new assets and projects, with clear accountability for completing projects within the designated time frame and budget. The Audit Committee and Senior Management receive regular updates on the outcomes of internal audits, and Senior Management is informed of the actions taken in response to audit findings. The Audit Committee reviews the Companys financial statements on a quarterly, semi-annual, and annual basis. The corporate governance section of the Annual Report provides a comprehensive overview of the Audit Committees activities, as well as those of other

Board Committees.

Throughout the year, a thorough review of internal financial controls was conducted, yielding satisfactory results, and recommendations for improvements were considered and implemented. Policy guidelines and

Standard Operating Procedures (SOPs) are updated as needed to align with changing business requirements.