E2E Networks Ltd Management Discussions

Disclaimer: Certain Statements made herein describing the Companys expectations or predictions are forward looking statements . The Company s results, performance or achievements can significantly differ materially from those projected via such statements. Important factors that could make a difference to the Companys operations include, among others, economic conditions affecting demand/supply, changes in government regulations, tax regimes, economic developments and other incidental factors. The Company assumes no responsibility in respect of forward- looking statements that may be amended or modified in future on the basis of subsequent developments, information or events.

INDUSTRY STRUCTURE AND DEVELOPMENTS

The global technology landscape is undergoing a fundamental transformation driven by Artificial Intelligence (AI), accelerated computing, cloud infrastructure and advanced data infrastructure. AI has evolved into a strategic business capability, with organisations increasingly integrating AI into core business processes. As adoption moves from experimentation towards production, computing infrastructure is becoming a critical foundation for the next generation of digital transformation.

Global demand for accelerated computing is being driven by the rapid adoption of AI workloads across model

AI applications move into production, demand is increasingly development,training,fine-tuning expanding beyond training towards inference and increasingly agentic workloads, creating sustained demand for scalable, high-performance infrastructure.

At the same time, the growing availability and capability of open-weight AI models is broadening access to advanced AI capabilities and changing how organisations approach AI deployment. This is increasing the importance of infrastructure that enables customers to control their models, data and workloads rather than relying exclusively on externally hosted AI services.

Where compute is located and who controls the underlying infrastructure is therefore becoming an important consideration alongside performance and cost. Increasing focus on data control, cybersecurity, privacy and regulatory requirements is driving demand for sovereign and private AI infrastructure, particularly among organisations with sensitive or mission-critical workloads.

Together, these trends are creating long-term opportunities for specialised AI infrastructure providers capable of combining scalable accelerated computing with the software and infrastructure capabilities required to support AI from development and training through production inference and agentic applications.

The scale of this opportunity is reflected in the rapid growth projected for the global neocloud market. Having generated an estimated US$25 billion in revenue in 2025, the market is forecast to expand more than seven-fold to US$180 billion by 2030, and further to US$400 billion by 2031 (Source: Synergy Research Group, 2026). This trajectory underscores the magnitude of infrastructure build-out required to meet AI-driven compute demand over the coming decade.

Supporting this growth, McKinsey & Company estimates that global data center capital expenditure will need to reach approximately US$6.7 trillion by 2030, with nearly 70% of this investment driven by AI workloads (Source:McKinsey & Company, The Cost of Compute, April 2025).

Looking ahead, the demand mix within the neocloud market is expected to shift meaningfully toward inference: by 2030, AI inference workloads are projected to account for approximately 80% of total neocloud market revenue, as enterprises move from model training toward large-scale deployment of AI applications (Source: ABI Research, The State of Neocloud, 2026).

OUR BUSINESS, OUTLOOK AND STRATEGY

Our Business

E2E Networks Limited is an Indian AI-focused cloud infrastructure provider delivering accelerated computing, storage, networking and software platforms for AI workloads. The Company has evolved from an Infrastructure-as-a-Service (IaaS) provider into an AI-first cloud platform, enabling enterprises, AI-native companies, developers and research institutions to build, train, fine-tune and deploy AI applications at scale.

The Companys infrastructure provides scalable, high-performance computing resources for AI model development, training and inference, while its software platforms provide an integrated environment for developing, deploying and operating AI workloads.

E2E is building towards an integrated AI factory where customers can progress from experimentation and model development to production-scale inference and increasingly agentic AI applications, combining compute infrastructure with software capabilities while maintaining a focus on performance, ease of use and cost efficiency.

The Company also provides sovereign and private AI infrastructure, enabling customers to deploy AI workloads in environments that provide greater control over their data, models and infrastructure.

Business Outlook

Artificial Intelligence is expected to remain a major driver of technology and infrastructure investment over the medium and long term. As organisations move from AI experimentation and model development towards production deployment, AI is increasingly becoming part of core business workflows, driving demand for scalable and economically efficient infrastructure.

The AI opportunity is also expanding beyond conventional digital applications into physical and mission-critical environments. Advances in physical AI, robotics, autonomous systems, scientific computing and industry-specific AI are creating new workloads across training, simulation and inference, while financial services, healthcare, manufacturing and other enterprises are increasingly embedding AI into core operations. towards inference The evolution of work loads from training and fine-tuning and increasingly agentic applications is expected to further expand the opportunity for AI infrastructure providers. At the same time, the growing use of open-weight models and demand for private and sovereign AI are creating a need for flexible infrastructure that can operate across cloud and customer-controlled environments.

Customers are increasingly evaluating AI infrastructure not only on raw performance, but also on cost efficiency, its combination of accelerated computing infrastructure, utilisation, flexibility networking, storage and software platforms positions the Company to participate in this evolution as AI moves from experimentation to production and increasingly agentic workloads.

Strategic Priorities

Looking ahead, the Company intends to focus on the following strategic priorities:

? Expand AI Infrastructure: Scale accelerated computing capacity together with networking and storage infrastructure to meet growing demand across AI training, inference and production workloads, while remaining flexible across evolving compute technologies.

? Strengthen AI Software Platforms: Develop the Companys software platforms to simplify AI development, deployment and operations, creating an integrated layer across compute infrastructure and supporting workloads throughout the AI lifecycle.

? Drive the Shift to Inference and Agentic AI: Enable customers to progress from model development and training to production-scale inference and increasingly agentic applications, including AI systems that can execute defined enterprise workflows.

? Advance Sovereign AI Capabilities: Expand public, private and customer-controlled deployment options that provide greater control over data, models and workloads, supported by open and vendor-neutral software.

? Scale Deploy infrastructure and appropriate funding arrangements in a capital-efficient manner, with increasing utilisation and longer-term customer commitments supporting the economics and predictability of the Companys growing infrastructure base.

? Expand Internationally: Build the Companys international presence and partnerships to serve AI-native companies and enterprises outside India, while maintaining India as the Companys primary market.

OPPORTUNITIES AND THREATS

The rapid advancement of Artificial Intelligence (AI), accelerated computing and cloud technologies is reshaping the global digital infrastructure landscape. Growing enterprise adoption of AI and increasing investment in AI for specialised providers. At the same time, the pace of this infrastructure are creating significant transformation is compressing the window to build durable competitive positions. Rising demand for AI compute and sovereign infrastructure creates opportunities for providers that can scale with the market.

OPPORTUNITIES

Growing Adoption and Expansion of Artificial Intelligence

Artificial Intelligence is moving rapidly from experimentation and model development into production use across enterprises, AI-native companies and research institutions. As AI becomes embedded in core business processes, demand for scalable accelerated computing, networking, storage and supporting software infrastructure is expected to grow substantially.

The opportunity is expanding beyond conventional digital applications into physical and mission-critical environments.

Physical AI, robotics, autonomous systems, scientific applications and industry-specific AI are creating new compute-intensive workloads across training, simulation and inference, broadening the addressable market for AI infrastructure providers.

Inference and Agentic AI

The AI infrastructure opportunity is evolving from predominantly model training towards increasingly continuous inference and agentic workloads. As AI applications move into production, inference can become a persistent infrastructure requirement rather than an episodic training workload.

The emergence of agentic AI introduces a further layer of opportunity. An AI model primarily generates responses to inputs; an agentic harness provides the execution layer around the model, enabling it to maintain state, access tools and data, evaluate results and take actions. Through an iterative execution loop that can observe, reason and act, the harness can turn a model into a system capable of executing multi-step tasks and enterprise workflows.

As agentic systems become more capable and widely deployed, a single business task may involve multiple model invocations, tool calls and iterations. This can create more persistent inference demand and expand the role of AI infrastructure from supporting model development to powering continuously operating AI systems.

Transformation of Enterprise Workloads

AI is not only being added to existing software; it is beginning to change how software itself is built. Layers of conventional application logic can increasingly be compressed into AI models and agentic execution, shifting workloads from traditional general-purpose infrastructure towards accelerated computing.

As enterprises replace or augment conventional workflows with AI-native systems, this creates an opportunity for specialised AI infrastructure providers to support the resulting compute-intensive workloads. The transition from deterministic applications to systems that can reason, use tools and execute multi-step tasks could create a growing and recurring demand for inference infrastructure.

Sovereign AI and Data Control

The increasing availability and capability of open-weight models is making advanced AI increasingly deployable outside proprietary API environments. This is creating demand for infrastructure that gives organisations greater control over their models, data and workloads.

Sovereign and private AI infrastructure can enable customers to control where models and data operate, how and how they models are fine-tuned, deployed. This creates an opportunity for infrastructure providers that combine accelerated computing with software platforms and customer-controlled deployment environments.

Specialised AI Infrastructure and Cloud Migration

As AI becomes a larger component of technology spending, customers are increasingly seeking infrastructure optimised for AI workloads rather than relying solely on general-purpose cloud environments. Specialised providers can offer dedicated or flexible capacity, workload-specific performance, cost efficiency and greater control.

This creates an opportunity for specialised AI infrastructure providers to capture workloads migrating from general-purpose cloud environments, while also supporting new AI workloads as they move from experimentation into production.

THREATS

Intense Industry Competition

The cloud infrastructure industry remains highly competitive, with global hyperscalers, regional cloud providers and specialised AI infrastructure providers competing for AI infrastructure demand. Capacity expansion across the industry may further intensify competition for customers, infrastructure resources and talent. The Company seeks to maintain its position through differentiated AI infrastructure and software platforms, customer experience, innovation and strategic partnerships.

Rapid Technological Changes

Rapid advances in Artificial Intelligence, accelerated computing, networking and software may change customer preferences and the relative performance and economics of different infrastructure configurations. The Company monitors technological developments and invests in infrastructure, engineering and product innovation to remain aligned with evolving requirements.

Infrastructure, Colocation and Supply Chain Constraints

The availability of suitable data-centre colocation capacity, power and network connectivity is critical to deploying and operating AI infrastructure at scale. Delays in securing such capacity or achieving Ready for Service (RFS) dates may affect infrastructure deployment plans. The Company mitigates these risks through advance planning, infrastructure and technology partnerships, prudent procurement and diversification of infrastructure and supply arrangements where feasible.

Capital Intensity and Infrastructure Economics

AI infrastructure requires significant upfront investment, while its economics depend on capacity utilisation, pricing, infrastructure and financing costs, and customer adoption. Changes in these factors may affect the economics of infrastructure investments. The Company maintains disciplined capital allocation and evaluates expansion against customer demand, utilisation and available financing.

Cybersecurity and Data Protection Risks

Cloud infrastructure providers manage mission-critical workloads and sensitive customer information, making cybersecurity and data protection important priorities. Increasingly sophisticated cyber threats, ransomware and data security risks require robust security, resilience, disaster recovery and compliance frameworks. Agentic AI and autonomous workloads may introduce additional security risks requiring evolution of the Companys security practices. The Company maintains security controls, continuous monitoring, periodic assessments, disaster recovery mechanisms and recognised information security and data protection practices.

Regulatory and Compliance Environment

Regulation governing Artificial Intelligence, cloud computing, data privacy and cybersecurity continues to evolve across jurisdictions. Changes in laws, data protection, data localisation or technology regulation may require changes to the Companys infrastructure, processes and governance. The Company monitors regulatory developments and maintains appropriate governance and compliance frameworks.

Macroeconomic and Geopolitical Factors

Global economic conditions, geopolitical developments, foreign exchange fluctuations and technology spending patterns may influence enterprise investment and infrastructure procurement cycles. The Company maintains financial discipline, prudent capital allocation, operational efficiency and a diversified customer base to strengthen business resilience.

SEGMENT WISE OR PRODUCT WISE PERFORMANCE

The Company operates in a single primary business segment; hence separate segmental reporting under Ind AS 108 is not applicable.

RISKS AND CONCERNS

The Company s business is exposed to a range of strategic, operational, financial, technological, regulatory and cybersecurity risks that are inherent to the cloud computing and Artificial Intelligence (AI) infrastructure industry.

Rapid technological advancements, evolving customer requirements, increasing competition, changing regulatory frameworks and the growing importance of information security require continuous monitoring and proactive risk management.

The Company has established an enterprise-wide Risk Management Framework supported by a Board-approved Risk Management Policy to identify, assess, monitor and mitigate material risks that could impact its business objectives. The framework enables systematic evaluation of risks based on their likelihood and potential impact and facilitates the implementation of appropriate mitigation measures. Risk assessments are carried out on a periodic basis, and significant and the Risk Management Committee to ensure timely response and effective governance.

Given the critical nature of cloud infrastructure services, the Company continues to focus on ensuring high service availability, infrastructure resilience, business continuity and disaster recovery capabilities. Continuous investments are made in technology, automation, monitoring systems and cybersecurity controls to safeguard customer data, strengthen operational resilience and minimise service disruptions.

The Company also closely monitors developments relating to Artificial Intelligence, cloud computing, data privacy, cybersecurity and other regulatory requirements to ensure continued compliance with applicable laws and industry standards. In addition, the Company periodically reviews its technology roadmap and infrastructure expansion plans to remain aligned with evolving customer requirements and emerging technology trends.

As demand for AI infrastructure continues to grow, the Company remains conscious of potential risks relating to technology obsolescence, availability of advanced computing infrastructure, cybersecurity threats, talent acquisition, supply chain dependencies and increasing competitive intensity within the cloud infrastructure industry. The Company seeks to mitigate these risks through prudent business planning, disciplined capital allocation, technology partnerships, continuous innovation, strong governance practices and a customer-centric operating model. The Board and the management believe that an effective risk management framework is integral to the Companys long-term growth strategy. The Company remains committed to continuously strengthening its governance processes, internal controls and risk management practices to safeguard stakeholder interests and create sustainable long-term value.

INTERNAL CONTROL SYSTEMS AND THEIR ADEQUACY

The Company has the internal control systems in place, adequate for the size of the Company and the nature of its business. The primary function of our internal control systems is to ensure efficiency in business operations, safeguarding of companys assets, adherence to policies and procedures, protecting and detecting errors and frauds, strict compliance with applicable laws and ensuring the reliability of financial statements and reporting. The Company has in place the internal financial controls for the various processes of the Company such as Revenue reporting and recognition, Fixed assets, Finance and accounts, Taxation, Treasury, HR & Payroll and Procurement etc. The internal control systems adopted by the Company ensures that all transactions are executed with proper authorisation, are recorded and reported correctly, and assets are safeguarded and protected against loss from unauthorised use. In addition, the compliance of corporate policies is duly monitored. The internal audits carried out by the Internal Auditor of the Company and management reviews supplements the process of internal financial control framework. Internal Audits are conducted at regular intervals to assure the management of fair transactions, as per set policies and processes. Efficacy of internal control systems are tested periodically by Internal Auditors and internal control over financial reporting is tested and certified by Statutory Auditors.

The Company has in place an Audit Committee, which serves as an important interface between the Statutory Auditors, Internal Auditors, and the Management, facilitating comprehensive discussions on matters within its terms of reference, including those pertaining to financial reporting, internal controls, and overall governance. Further, recognizing the importance of proactive risk oversight, the Company has also constituted a Risk Management Committee. This Committee is entrusted with the responsibility of formulating, monitoring, and reviewing the risk management framework, ensuring the identification, assessment, and effective mitigation of risks that could potentially impact the Company s strategic, operational, and financial objectives.

MATERIAL DEVELOPMENTS IN HUMAN RESOURCES AND INDUSTRIAL RELATIONS

At E2E Networks Limited, our people remain the cornerstone of our growth and a key differentiator in delivering innovation-led cloud and AI solutions. As the Company continues to strengthen its position in the rapidly evolving Artificial Intelligence and cloud infrastructure ecosystem, we recognise that attracting, developing and retaining high-quality talent is fundamental to achieving our long-term strategic objectives. We are committed to fostering an inclusive, collaborative and high-performance work environment where employees are empowered to innovate, take ownership and contribute meaningfully to the Companys sustained growth.

Our Human Resources philosophy is centred on creating a culture that encourages continuous learning, professional excellence, accountability and mutual respect. We believe that a motivated and engaged workforce drives superior customer outcomes, operational excellence and sustainable value creation. Guided by these principles, the Company continues to invest in people-centric initiatives that enhance employee engagement, strengthen leadership capabilities and support individual career aspirations while aligning employees with the Companys vision, values and business objectives.

As the technology landscape continues to evolve, particularly in the areas of ArtificialIntelligence, cloud computing and digital infrastructure, the Company remains focused on building future-ready capabilities across the organisation. Structured learning and development programmes, technical upskilling initiatives, leadership development interventions and cross-functional exposure enable employees to continuously enhance their professional competencies and remain aligned with emerging industry trends and technological advancements.

Performance excellence continues to be an integral part of the Companys people strategy. Our performance management framework is designed to promote a merit-based culture by recognising and rewarding high performance, encouraging innovation and supporting continuous feedback and professional development. The Company believes that recognising individual and team contributions strengthens employee motivation while Employee well-being remains a key organisational priority. The Company strives to provide a safe, inclusive and respectful workplace where diversity of thought is encouraged and employees are supported both professionally and personally. Various employee engagement initiatives, collaborative programmes and open communication channels continue to strengthen trust, teamwork and organisational cohesion, contributing to a positive and productive work environment.

The Company also remains committed to maintaining the highest standards of workplace ethics, integrity and governance. Our policies and practices promote transparency, equal opportunity, respect and compliance with applicable laws, reinforcing a culture founded on accountability and responsible corporate conduct.

As on March 31, 2026 , the Company had 207 employees on its rolls. Industrial relations remained cordial and harmonious throughout the year, reflecting the strong relationship between the management and employees and an engaged, motivated and future-ready workforce capable reaffirming of supporting its long-term growth aspirations.

FINANCIAL PERFORMANCE AND HIGHLIGHTS

The financial performance during the Financial Year 2025-26 has been summarized below:

(Amount in Rs. Lakhs)

Particulars	FY 2025-26	FY 2024-25
Revenue from operations	24558.01	16396.08
Total Expenditure other than finance cost and depreciation	11931.78	6730
Earnings before Interest, Tax and Depreciation (EBITDA)	12626.23	9666.08
Other Income	3400.64	3942.68
Depreciation	16922.69	6007.6 1
Finance Costs	1224.13	1322.01
Profit/(Loss) before tax (PBT)	(2119.95)	6279.14
Current Tax	0	3.89
Deferred Tax	(522.40)	1588.44
Deferred Tax Expense pertains to earlier years	(40.96)	(62.62)
Net Profit for the Year (PAT)	(1556.59)	4749.43
Other Comprehensive Income	93.89	(85.64)
Total comprehensive income for the period/year	(1462.70)	4663.79
Paid-up Equity Share Capital (Face value of Rs. 10/- Per share)	2055.65	1,996.79
Basic EPS (in Rs.)	(7.75)	28.28
Diluted EPS (in Rs.)	(7.61)	27.21

During the financial year under review, the Company delivered a strong performance, registering significant growth across key financial parameters compared to the previous financial year.

Revenue from Operations grew to Rs. 24,558.01 lakhs from Rs. 16,396.08 lakhs in the previous year, reflecting a strong growth of 49.78% , driven by increased business volumes, expanded cloud infrastructure offerings, and deeper market penetration.

Other Income stood at Rs. 3,400.64 lakhs as against Rs. 3,942.68 lakhs in the previous year, reflecting a moderation of 13.75% , primarily on account of rationalisation in non-operating income streams during the year.

Total Expenditure (excluding finance costs and depreciation) increased to Rs. 11,931.78 lakhs from Rs. 6,730.00 lakhs in the previous scale-up of operations, year, an increase of 77.29% , in line with the significant higher resource deployment and Capacity Expansion.

EBITDA stood at Rs.12,626.23 lakhs as against Rs. 9,666.08 lakhs in the previous year, reflectinga growth of 30.63% . While absolute EBITDA improved, the EBITDA margin moderated due to higher operating expenditure incurred in scaling up the Companys GPU and cloud computing capabilities.

Depreciation increased sharply to Rs. 16,922.69 lakhs from Rs. 6,007.61 lakhs in the previous year, a rise of new technology infrastructure, GPU assets, undertaken 181.69% ,primarilyonaccountofsignificant during the year to support the Companys long-term growth strategy.

Finance Costs stood at Rs. 1,224.13 lakhs as against Rs. 1,322.01 lakhs in the previous year, reflecting a marginal decrease of 7.40% , on account of optimised borrowing mix and better treasury management.

Profit Before Tax (PBT) stood at a loss of Rs. 2,119.95 lakhs as against a profit of Rs. 6,279.14 lakhs in the previous year. The shift to a loss position is primarily attributable to a substantial increase in depreciation charges consequent to large-scale expansion during the year and is not reflective of any deterioration in the underlying operating performance of the Company.

Tax Expenses for the year comprised Nil current tax (previous year: Rs. 3.89 lakhs), deferred tax credit of Rs. 522.40 lakhs (previous year: deferred tax expense of Rs. 1,588.44 lakhs), and deferred tax credit pertaining to earlier years of Rs. 40.96 lakhs (previous year: Rs. 62.62 lakhs), resulting in a net tax credit of Rs. 563.36 lakhs for the year.

Net Profit After Tax (PAT) for the year stood at a loss of Rs. 1,556.59 lakhs as against a profit of Rs. 4,749.43 lakhs in the previous year. The loss is primarily a consequence of significantly higher depreciation charge arising from large-scale expansion of GPU and cloud infrastructure assets, which is a planned and strategic investment in the Companys future growth capacity. The underlying cash-level operations of the Company remain healthy as reflected in the EBITDA performance.

Other Comprehensive Income for the year was a income of Rs. 93.89 lakhs as against a expense of Rs. 85.64 lakhs in the previous year, resulting in a Total Comprehensive loss of Rs. 1,462.70 lakhs for FY 2025- 26, as against a Total Comprehensive income of Rs. 4,663.79 lakhs in the previous year.

Paid-up Equity Share Capital stood at Rs. 2,055.65 lakhs (face value of Rs. 10/- per share) as at March 31, 2026, as against Rs.1,996.79 lakhs in the previous year, reflecting capital infusion during the year.

Earnings Per Share (EPS) for the year stood at Rs. (7.75) Basic and Rs. (7.61) Diluted , as against Rs. 28.28 (Basic) and Rs. 27.21 (Diluted) in the previous year. The negative EPS is a direct outcome of the higher depreciation impact on account of Expansion and is not indicative of any weakness in the Companys operational fundamentals.

The year under review was marked by a substantial increase in both revenues and EBITDA. The Company demonstrated strong operational performance, enhanced productivity, and strategic investments in capacity expansion. The strong cash flows position the Company for sustained growth in the coming years.

BASIS OF PREPARATION OF FINANCIAL STATEMENTS

The standalone financial statements have been prepared in compliance with Indian Accounting Standards ( Ind AS), the provisions of the Companies Act, 2013 (the Companies Act), as applicable and guidelines issued by the Securities and Exchange Board of India (SEBI). The Ind AS are prescribed under Section 133 of the Companies Act read with Rule 3 of the Companies (Indian Accounting Standards) Rules, 2015 and amendments issued thereafter.

The Management accepts the responsibility for the integrity and objectivity of these financial statements, as well as for various estimates and judgements used therein. The estimates and judgements relating to the financial statements have been made on a prudent and reasonable basis, so that the financial statements reflect in a true and fair manner the form and substance of transactions, and reasonably present the state of airs, profit/loss and cash flows for the year.

RATIO ANALYSIS

Ratio	FY 2025- 26	FY 2024- 25	% Change as compared to previous FY	Remarks/Reason for change where change is + 25% or more as compared to Previous FY
Debtors Turnover/Trade Receivable Turnover Ratio	18.28	26.62	(31.35%)	The Trade receivable turnover ratio has decreased due to increase in payment terms of debtors.
Inventory Turnover	N. A	N.A	N.A	Since the Company does not have any inventory, the Inventory Turnover Ratio is not applicable.
Debt Service Coverage ratio	5.49	3.91	40.47%	The Debt service coverage ratio has increased due to increase in earnings.
Interest Coverage Ratio	(0.79)	5.85	(113.52%)	The Interest Coverage Ratio has decreased due to lower earnings resulting from higher depreciation expenses following the capitalization of new assets.
Current Ratio	1.20	1.70	(28.97%)	The Current Ratio has decreased due to decrease in Cash and cash equivalents utilised for payments to Capex vendors during the year.
Debt Equity Ratio	0.09	0.05	88.83%	The Debt Equity ratio has increased due to new term loan availed by company for business expansion.
Operating Profit Margin (%)	51.41%	58.95%	(12.79%)	The ratio has decreased on accounts of higher operating expenditure incurred in scaling up the capacity during the year.
Net Profit Margin (%)	(6.34%)	28.97%	(121.88%)	The Net profit ratio has decreased due increase in depreciation on account of Servers purchased for business expansion.
Return on Net Worth / Return on Capital Employed (%)	(0.50%)	4.48%	(111.26%)	The ratio is decreased due to loss in current year on account of depreciation for additional capex done by Company.