Cambridge Technology Enterprises Ltd Management Discussions

INDUSTRY OVERVIEW AND GLOBAL CONTEXT

This year, the tech spaces focus was on bringing results from Artificial Intelligence (AI), Agentic AI, Machine Learning and Data models that they put in place over the last few years. Enterprises globally moved from exploratory AI initiatives to deliberate, scaled deployments while the demand for specialized partners who can navigate this transition with precision increased. This became a structural transition with increasing enterprise AI projects and an ongoing reconfiguration of digital infrastructure priorities.

Technologies like Agentic AI, conversational AI, Natural Language Processing (NLP) have since emerged as some of the most consequential developments of this cycle. Businesses today have moved beyond standalone tools or co-pilot functions to actively architecting systems and engines where NLP systems understand nuance and human language to form the foundation of systems like chatbots; AI agents reason, plan, and act autonomously across interconnected workflows; and conversational AI models automate customer service, boost e-commerce sales, and streamline internal business operations. This shift has both considerable opportunity and corresponding responsibility for technology service providers. It needs deep competency and domain expertise in more than just model development and deployment, extending to orchestration architecture, safety frameworks, and enterprise integration at scale.

Enterprises are increasingly emphasizing on partners with domain credibility alongside engineering capability. Perhaps this is why global spending on AI-related services continues to grow at a sustained pace while enterprise-focused applications and industry-specific AI solutions are seeing a premium demand. This is particularly visible in sectors where the tolerance for generic solutions is low, and the stakes of deployment are high, like healthcare and life sciences, financial services, energy and utilities, and the automobile industries.

With a globally distributed delivery model, deep talent reserves, and maturing AI and data engineering practices, India-headquartered technology firms were able to serve the complex needs of multinational enterprises. The Indian IT services sector, in which the Company operates, maintains a strong position in this evolving landscape. The Companys geographic footprint across the United States, India, Malaysia, the Philippines, and Qatar provided relevant access to both a talent pool and customer base of these growing markets.

Cost optimization and infrastructure rationalization remained equally important priorities for enterprise customers year-round. While discretionary spending in certain areas remained cautious, investment in AI-driven productivity, automation, and process intelligence was relatively resilient, reflecting a genuine C-suite conviction around the long-term value of these capabilities.

BUSINESS OVERVIEW

Cambridge Technology Enterprises Limited (the Company or CTEL) is a business and technology services company with over 25 years of continuous operation. The Company builds and delivers custom AI solutions, data engineering services, enterprise application development, and managed technology services to a diverse portfolio of enterprise and Fortune 500 clients, globally.

The Companys service portfolio is organized around four principal areas of practice:

Artificial Intelligence and Machine Learning: This is where the Company builds the actual intelligence, including custom model development, trained for specific business problems, generative AI applications, natural language systems, and computer vision. Furthermore, our experts also build solutions for predictive analytics, anomaly detection, and recommendation systems to help enterprises act on the data they have.

Agentic AI: This was the most significant and sustained area of focus this fiscal year for us. Instead of building tools to assist human decision-making, we are now designing, developing, and deploying autonomous AI agent systems for enterprise use cases that can reason, act, and coordinate across enterprise workflows on their own.

Data Engineering: This practice helps us form the foundational layer for AI and ML model performance. No AI system performs well on poor data. From data strategy, readiness, and pipeline architecture to real-time streaming, DataOps, and business intelligence, we help lay the foundational work and the data infrastructures that make everything else possible.

Enterprise Applications: We help companies modernize legacy platforms, SaaS platform development, build AI-powered custom applications, and integrate enterprise ecosystems to ensure intelligence flows across the business. The practice also focuses on enterprise mobility, Identity and Access Management, and IoT integration.

The Companys operating model lies on three commitments that have been consistent for us across 25+ years of operations-delivering deep technical expertise across a focused set of capabilities; building process efficiencies for sustained operational value for clients; and maintaining long-term trusted relationships that extend beyond just individual project engagements.

Additionally, our expertise in data annotation work as critical enablers for AI model training and generative AI development and our broader capability offering. The Company serves enterprise clients across industries, with offices in the US and APAC regions.

KEY HIGHLIGHTS: FISCAL YEAR 2025-26

25+	1,000+	250+
Years in Operation Trusted by Global Enterprises US	Projects Delivered Across Diverse Industries APAC	Employees India

The year under review was defined by our refinements of service offerings to specialised Agentic AI delivery, a deepening of industry-specific solution capabilities, the strengthening of strategic partnership relationships, and a significant internal investment in enterprise-wide AI capability building.

Agentic AI: A Defining Practice Area

The most significant capability development of the year has been our formalization and deepening of our Agentic AI practice. While the Company has long operated at the intersection of AI, ML, and enterprise engineering, the emergence of enterprise-grade Agentic AI as a distinct and commercially viable domain has created a unique opportunity that we have been pursuing and seeing tangible results from.

What is Agentic AI

Agentic AI refers to systems in which AI models operate with a degree of autonomy. They reason, plan, and take action across connected enterprise workflows with minimal human intervention. The Companys approach to Agentic AI is purpose-built for enterprise contexts. Instead of applying generalized frameworks, we design and implement agent architectures tailored to the specific operational environment, data landscape, and governance requirements of each customer.

The Company has positioned its Agentic AI offerings around three measurable enterprise outcomes: meaningful reduction in operational disruptions with agents to anticipate and respond to dynamic conditions; improving customer satisfaction with agents that deliver personalized, context-aware interactions; and an enhancing operational efficiency with agents that autonomously manage complex, multi-step workflows that previously needed significant human coordination.

The Companys Agentic AI methodology encompasses the full solution lifecycle, from initial feasibility assessment and proof-of-concept design to production deployment and ongoing model refinement. During the year, we offered qualifying enterprise clients complimentary proof-of-concept engagements for Agentic AI use cases, generating a substantial pipeline and enabling prospective customers to evaluate the technologys applicability within their own operational environments.

This practice is further supported by the Companys proprietary work in lightweight, modular agent orchestration research and development activity that positions us as a builder of tailored AI-native solutions designed for efficiency, scalability, and precision in constrained enterprise environments. This internal capability development reflects the Companys commitment to staying ahead of the applied research curve rather than trailing it.

Machine Learning: Tailored Models for Complex Use Cases

The Company continued to deepen its machine learning practice during the year, with particular progress in the development of domain-specific and industry-calibrated models. Our ML methodology, covering supervised and unsupervised learning, deep learning, NLP, and ensemble approaches, was applied to an expanding range of use cases, including demand forecasting, anomaly detection, predictive maintenance, and intelligent document processing.

A significant area of progress has been the growing commercial interest from the animal health and pet nutrition industries in purpose-built AI and ML solutions. Enterprises in these sectors face distinct data challenges, including the complexity of biological variability, regulatory specificity, and supply chain intricacy, that standard AI tools are not enough to address. Our ability to develop tailored models calibrated to the data characteristics and business logic of these industries has resulted in meaningful engagement and early-stage delivery activity. The Company views this as a nascent but commercially viable vertical, and one that reflects its broader capability to serve highly specialized enterprise requirements across a range of industries.

Enterprise Applications: Modernization and Integration at Scale

One of the service clusters for the Companys revenue mix has been enterprise application modernization and development. The Companys focus has been on three dimensions of value delivery in this practice-transforming legacy platforms to SaaS architectures; developing custom AI-powered applications that extend operational intelligence; and integrating enterprise ecosystems to remove data silos and enable end-to-end process automation.

The Companys enterprise application engagements increasingly incorporate AI operationalization as a standard embedded design principle. This includes computer vision deployment, NLP-driven automation, AI-assisted quality management, and intelligent workflow orchestration. Our mobile-first capability further enables clients to extend these applications to distributed field and operational teams.

Additionally, our services like Infrastructure managed services, cloud transformation, and DevOps continued to help customers rationalize operating costs while maintaining resilience and scalability.

INDUSTRY VERTICAL FOCUS

The Company continued to sharpen its industry vertical focus during the year. The Company has five core verticals-Clean Tech, Energy and Utilities, Healthcare and Life Sciences, Automotive, Financial Services and Insurance, and Retail and E-Commerce. Each of them present a distinct AI and data engineering use cases, and our continued investment in domain expertise across these sectors strengthens our ability to deliver meaningfully differentiated solutions.

HEALTHCARE AND LIFE SCIENCES

Healthcare and Life Sciences has always been one of the Companys most active and important verticals, driven by the scale of AIs applicability across the care continuum, from discovery to delivery.

The key solution areas in which the Company has been engaged include:

Predictive Analytics and Personalization: AI algorithms and models can forecast patient outcomes and disease progression, allowing organizations to enable proactive and timely clinical interventions while designing personalized treatment routes

Medical Image Analysis: With computer vision models, we enable organizations to improve diagnostic accuracy by analyzing X-rays, MRIs, and CT scans, supporting early disease detection and treatment prioritization

Accelerated Drug Discovery: AI-first approaches can be applied to identify potential drug candidates, predict the efficacy of treatment plans, and reducing the time-to-market for clinical interventions

Electronic Health Records (EHRs): By automating data entry, extraction, and pattern recognition within clinical data systems, we can help organizations to enhance decision-making quality and reduce administrative burden and costs

Virtual Health Assistants: We can implement AI-driven conversational agents that can provide 24/7 patient support, query handling, and appointment management

Remote Patient Monitoring: With continuous analysis of wearable device data, institutions can monitor chronic conditions, detect anomalies, and enable timely clinical interventions

Within the broader life sciences category, the Company has seen growing commercial interest from enterprises in industries that work with complex biological variability, stringent regulatory requirements, and specific data challenges that standard AI tools do not adequately address. The Companys ability to develop domain-specific, purpose-built AI and ML solutions for these industries has generated meaningful pipeline engagement during the year, and can be viewed as a developing area of focused investment.

CLEAN TECH, ENERGY, AND UTILITIES

Customers in the energy and utilities sector operate large, complex physical asset bases, where the consequences of equipment failure, supply chain disruption, or regulatory non-compliance are material. This makes precision AI and data engineering solutions particularly valuable.

The Companys engagements in this vertical have spanned:

Production Optimization: Collating real-time data from production facilities, sensors, and drilling operations can help monitor equipment health and optimize throughput across mission-critical operations

Reservoir Modelling: With advanced data integration that combines seismic, historical, and geological datasets, we help enterprises construct and maintain digital reservoir models for actionable operational insights

Predictive Maintenance: Solutions for continuous IoT sensor monitoring with anomaly detection and predictive maintenance alerts can help identify potential equipment failures before they lead to downtime

Sustainability and Environmental Monitoring: We can analyse emissions, water quality, and habitat data to ensure regulatory compliance are supported and ecological impact is detected early

Supply Chain Optimization: With multi-segment data monitoring across transportation, inventory, and supplier systems, we help drive data-driven procurement and minimize supply disruption

Drilling Efficiency: By processing data from drilling sensors and rig telemetry, we help enable real-time monitoring and optimization of drilling parameters for mission-critical field operations

AUTOMOTIVE

The automotive sector is undergoing a major structural transformation, with the electrification of vehicle platforms, evolving connectivity requirements, and with increasing expectations of data-intelligent customer experiences.

The Companys automotive practice addresses several of the most commercially relevant dimensions of this transformation, including:

Electric Vehicle Ecosystems: Solutions like smart-charging infrastructure, Vehicle-to-Grid (V2G) integration, and energy usage optimization help EV platforms operate with connected ecosystems

Telematics and Connectivity: V2X (vehicle-to-everything) communication platforms and remote diagnostics solutions can enable real-time vehicle data monitoring with secure, integrated systems

Predictive Maintenance: With sensor data analysis and telemetry-driven anomaly detection, we can enable proactive maintenance scheduling and extend asset lifespan across vehicle fleets

Dealership Management Systems: We implement unified platforms that can standardize dealer operations, manage invoicing and billing workflows to bring higher transparency to inventory management

Logistics and Procurement: Solutions for demand forecasting and supply chain optimization bridge the gap between procurement and operational demand to enable supplier performance monitoring

Customer Support Automation: Omnichannel AI-powered support solutions like automated chatbots, appointment scheduling systems and more can help companies digitize and personalize customer interactions seamlessly

FINANCIAL SERVICES AND INSURANCE

Financial Services and Insurance clients have been early adopters of AI technology. The systems theyre working with right now are getting more sophisticated as demand grows in the vertical. The Companys engagements span risk management, operational automation, and customer intelligence, with solutions in AI and data engineering.

Our domain expertise here creates measurable differentiation across:

Fraud Detection and Prevention: Predictive analytics and computer vision models that identify unusual transaction patterns and customer behaviour anomalies in real-time

Regulatory Compliance: NLP-driven automation of compliance monitoring, reporting, and audit trail management that enables institutions to track and swiftly respond to regulatory updates

Risk Analysis and Management: Advanced analytics and real-time monitoring for credit risk assessment, market movement prediction, and compliance risk mitigation

Credit Scoring and Loan Approval: AI models that evaluate creditworthiness with greater accuracy, streamline approval processes, and accelerate lending decision timelines

Personalized Customer Experiences: Generative AI and LLM-powered chatbots that deliver customized financial advice, investment guidance, and round-the-clock product support

Operational Efficiency: RPA, NLP, and computer vision solutions that automate document processing, reduce manual errors, and free operational capacity

Cybersecurity: AI-driven threat detection, multi-factor and biometric authentication, and behavioural analytics for real-time identification and response to cyberthreats

RETAIL AND ECOMMERCE

Retail and ecommerce clients are increasingly opting for AI solutions that operate across the full customer and operations lifecycle. Starting from hyper-personalized shopping experiences at the front end to intelligent inventory and supply chain management at the back end.

The Companys retail practice is delivering across this entire spectrum:

Personalized Shopping Experiences: AI-powered recommendation engines that analyze customer behaviour to deliver contextually relevant, dynamically updated purchasing experiences;

Customer Relationship Management: Sentiment analysis and cross-channel integration that enable brands to respond to customer needs with greater precision;

Inventory Management: Real-time tracking, automated reordering, and demand forecasting capabilities integrate RFID, IoT, and predictive analytics to reduce stock-outs and overstock;

Supply Chain Optimization: AI and IoT-driven automation and traceability solutions that bring visibility and efficiency to procurement, logistics, and fulfillment operations;

Analytics and Business Intelligence: Advanced data analytics platforms that generate actionable insights from customer behaviour, sales trends, and operational performance data;

Mobile and Web Application Development: User-centric mobile and web applications with seamless checkout experiences, in-app behavioural analytics, and performance optimization.

FINANCIAL PERFORMANCE OVERVIEW

The following discussion of financial performance is based on the audited consolidated financial statements of Cambridge Technology Enterprises Limited and its subsidiaries for the financial year ended March 31, 2026.

The Companys revenue performance during the year reflects the transitional nature of this period. It is characterised by continued investment in new capability areas, particularly Agentic AI. The management acknowledges that certain investment decisions made during the year are expected to yield measurable commercial outcomes.

These were directed at building specialised capability and deepening strategic partnerships, and are expected to yield measurable commercial outcomes over a medium-term horizon. This goes alongside the delivery of ongoing client engagements across established practice areas.

Revenue from the Companys US operations constituted a significant portion of consolidated revenues. This continues to reflect the composition of the Groups long-standing client relationships in that geography. The Groups employee base and delivery operations across India, the United States, Malaysia, the Philippines, and Qatar provide an operating structure designed for both cost efficiency and client proximity.

The Company continues to hold its view that the breadth of its service portfolio provides a degree of revenue resilience against demand fluctuations in any single service line. The service portfolio spans across AI, data engineering, enterprise applications, and managed services.

The management will continue to pursue disciplined cost management alongside selective capability investment, with a view to improving operating margins progressively.

Note to Investors

Specific financial figures, including revenue, profit/loss, and other quantitative disclosures, are presented in the Consolidated Financial Statements and accompanying schedules forming part of this Annual Report. The discussion above is intended to provide qualitative context for the financial results and should be read in conjunction with those statements.

FINANCIAL AND OPERATIONAL PERFORMANCE

CONSOLIDATED PERFORMANCE

(Rupees in Crores)

Year	2025-26	2024-25
Revenue from operations	181.02	198.92
Total Expenses	182.88	250.22
Profit Before Tax	1.65	(46.05)
Profit After Tax	0.48	(48.06)
Total Comprehensive Income	12.43	(44.50)
Reserves & Surplus	60.74	48.31
Earnings Per Share (EPS)	0.24	(24.48)

REVENUE:

During the financial year ended March 31, 2026, the Company reported consolidated revenue of Rs. 181.02 crores, compared to Rs. 198.92 crores in the previous financial year, marking a year-on-year decline of 9.00%. This softening in topline performance was largely driven by weaker execution across certain subsidiary entities, the completion and non-renewal of select client engagements/projects, subdued demand in the broader IT services market, moderation in revenues from service-led offerings, and pricing pressures across the portfolio.

Notwithstanding these industry-wide headwinds including cautious technology spending by clients and elongated deal cycles the management remains focused on strengthening the Companys positioning through deeper engagement with existing accounts, expanding the addressable client base, diversifying its technology and digital service offerings, and investing in emerging growth areas such as AI/automation-led solutions. These initiatives are designed to build a more resilient, future-ready service portfolio and support the Companys continued commitment to delivering sustainable, long-term value to its stakeholders in an evolving technology landscape.

PROFIT BEFORE TAX (PBT) AND PROFIT AFTER TAX (PAT):

The Company delivered a significant turnaround in profitability. Consolidated profit before tax stood at Rs. 1.65 crores for the year, as against a loss before tax of Rs. 46.05 crores in the previous year, while profit after tax stood at Rs. 0.48 crores as against a loss after tax of Rs. 48.06 crores in the previous year a swing of nearly Rs. 48.5 crores at the PAT level. This improvement was driven substantially by disciplined cost management across the Group: employee benefits expense declined by approximately 25% to Rs. 109.29 crores (from Rs. 145.97 crores), other expenses reduced by approximately 57% to Rs. 17.17 crores (from Rs. 39.98 crores), depreciation and amortisation fell by approximately 41% to Rs. 8.89 crores (from Rs. 15.11 crores), and finance costs declined by approximately 16% to Rs. 7.90 crores (from Rs. 9.36 crores). These reductions reflect the closure of underperforming projects, rationalisation of bench costs, stabilisation of recently acquired entities following the completion of one-time integration adjustments, and continued optimisation of the Companys overall cost structure.

Basic and diluted earnings per share improved to Rs. 0.24 for the current financial year, compared to a loss per share of Rs. 24.48 in the previous financial year. Management continues to pursue focused strategic initiatives aimed at strengthening client engagement, broadening service offerings, and repositioning the Company toward higher-value, higher-margin engagements, in support of sustainable long-term value creation for stakeholders.

COMPREHENSIVE INCOME & RESERVES AND SURPLUS

During the financial year ended March 31, 2026, the Company reported a consolidated profit after tax of Rupees 0.48 crores as compared to a loss after tax of Rupees 48.06 crores in the previous year, reflecting an increase of 101%. Total Comprehensive Income also increased by 128% from Rs. (44.50) crores to Rs. 12.43 crores during FY 2025-26, highlighting the overall impact on the bottom line. Consequently, Reserves and Surplus increased by 25.73%, from Rupees 48.31 crores in FY 2024-25 to Rupees 60.74 crores in FY 2025-26.

RETURN TO PROFITABILITY

The improvement in profitability after tax during the financial year under review was driven by a combination of operational and strategic factors:

Closure and rationalization of underperforming projects, which arrested recurring losses and improved overall contribution margins; Stabilization of recently acquired entities, with the significant one-time adjustments and impairments recognized in the previous financial year not recurring during the year under review; Disciplined cost management, including a reduction in bench costs and tighter control over discretionary and administrative expenses; Lower finance costs following a net repayment of borrowings and improved working capital management during the year; Early benefits from strategic development expenditure incurred in the previous year, which began contributing positively to delivery capability and competitive positioning during the year.

While the turnaround in profitability is encouraging, it is important to note that a meaningful portion of the improvement reflects the non-recurrence of one-time charges and transitional adjustments taken in the previous year in connection with past acquisitions, rather than a purely organic improvement in the underlying business. Looking ahead, the Company remains focused on consolidating this improvement and building a more resilient earnings base. Continued investments in product development, delivery capability enhancement, and client engagement are expected to further strengthen the Companys competitive positioning over the medium to long term.

Additionally, the Company will continue to pursue measures aimed at optimizing operating costs, improving internal efficiencies, and better aligning resources with its long-term growth roadmap. These steps are expected to support the sustained recovery in margins and facilitate the rebuilding of reserves in the forthcoming periods.

EXPENDITURE

Total Expenditure decreased by 26.91% to Rupees 182.88 crores for the year ended March 31, 2026, as compared to Rupees 250.22 crores in the previous financial year. Out of the above, Employee Benefits Expense stood at Rupees 109.29 crores in FY 2025-26 as against Rupees 145.97 crores in FY 2024-25, a decline of approximately 25.13%.

The decrease in employee costs during the year reflects the Companys continued focus on workforce rationalization and right-sizing initiatives undertaken across the Group, including the scale-down and closure of non-profitable projects within acquired entities and a reduction in bench-related costs. These measures, initiated in the previous year as investments toward long-term organizational alignment, have now begun yielding tangible benefits in the form of a leaner cost structure. Management believes this improved cost discipline, combined with ongoing efforts to strengthen operational efficiency, has been instrumental in driving the Companys return to profitability during the year, while it continues to balance cost optimization with the need to retain and nurture key talent critical to future growth.

Finance Costs decreased by 15.60% to Rupees 7.90 crores for the year ended March 31, 2026, as compared to Rupees 9.36 crores in the previous year. The reduction in finance costs was primarily driven by a net repayment of borrowings during the year, with total borrowings declining from Rupees 86.24 crores to Rupees 73.32 crores as at year-end, reflecting the Companys continued focus on strengthening its balance sheet and reducing overall leverage. Improved working capital management and disciplined treasury operations further supported the reduction in interest outgo. Management remains committed to prudent capital management practices aimed at optimizing the Companys cost of capital and supporting sustained profitability going forward.

STANDALONE PERFORMANCE

(Rupees in Crores)

Year	2025 26	2024 25
Revenue from operations	57.24	66.43
Total Expenses	55.30	66.04
Profit Before Tax	3.77	4.85
Profit After Tax	2.73	2.54
Total Comprehensive Income	3.04	2.56
Reserves & Surplus	35.11	32.07
EPS	1.39	1.30

REVENUE

The Revenue of the company decreased by 13.83% to Rupees 57.24 crores for the financial year ended March 31, 2026, as compared to Rupees 66.43 crores in the previous financial year.

During the year under review, the Companys standalone revenue moderated from Rupees 66.43 Crores to Rupees 57.24 Crores. The performance was impacted by a marginal reduction in business volumes from certain overseas customers, resulting in the completion of specific projects and corresponding alignment of resource deployment. Further, the domestic business segment witnessed softer demand conditions, which affected revenue growth during the year. Lower license sales as compared to the previous year also contributed to the decline in revenue and profitability.

Despite these temporary challenges, the Company continued to maintain a strong operational foundation and responded proactively through effective resource optimization, enhanced operational efficiencies, and focused business development initiatives. The Company remains committed to strengthening relationships with existing customers, expanding its service offerings, diversifying its client base, and pursuing new opportunities across domestic and international markets. Management is confident that these strategic efforts will support sustainable growth and improved performance in the years ahead.

PROFIT BEFORE TAX

Profit before Tax (PBT) stood at Rupees 3.77 Crores for the financial year ended March 31, 2026, as compared to Rupees 4.85 Crores in the previous financial year, reflecting a decrease of 22.17%.

The moderation in profitability was primarily driven by lower revenues from certain domestic projects, a marginal reduction in business volumes from select overseas customers, and lower license sales during the year. In addition, other income decreased to Rupees 1.83 Crores from Rupees 4.46 Crores in the previous financial year, which impacted overall profitability.

The Company responded proactively to the changing business environment through effective resource alignment, prudent cost management, and continued focus on operational efficiency. These measures resulted in lower employee benefit expenses and reduced finance costs following the repayment of borrowings during the year, thereby helping to mitigate the impact on profitability. The Company remains focused on strengthening its business pipeline, expanding its customer base, and pursuing new growth opportunities across domestic and international markets to drive sustainable financial performance in the coming years.

PROFIT AFTER TAX, COMPREHENSIVE INCOME & RESERVES AND SURPLUS

Profit after Tax (PAT) increased by 7.30% to Rupees 2.73 Crores for the financial year ended March 31, 2026, as compared to Rupees 2.54 Crores in the previous financial year. Total Comprehensive Income also increased by 18.68% from Rs. 2.56 crores to Rs. 3.04 crores during FY 2025-26, reflecting the Companys resilience and continued focus on maintaining a healthy bottom line despite a challenging business environment.

The improvement in Profit after Tax was primarily supported by a lower tax expense during the year, which more than offset the decline in Profit Before Tax arising from lower revenues from certain domestic projects, a marginal reduction in business volumes from select overseas customers, lower license sales, and reduced other income. The Companys disciplined approach towards resource optimization, cost management, and operational efficiency also contributed to preserving profitability and strengthening overall financial performance.

Reflecting the Companys sound financial position, Reserves and Surplus increased from Rupees 32.07 Crores in FY 2024-25 to Rupees 35.11 Crores in FY 2025-26, supported by retained earnings. The Company remains focused on strengthening its core business, expanding its customer base, improving operational efficiencies, and pursuing growth opportunities across domestic and international markets, thereby creating a strong foundation for sustainable long-term growth and value creation for stakeholders.

EXPENDITURE

Total Expenditure decreased by 16.26% to Rupees 55.30 Crores for the financial year ended March 31, 2026, as compared to Rupees 66.04 Crores in the previous financial year. Employee Benefits Expense stood at Rupees 40.85 Crores in FY 2025-26 as against Rupees 44.89 Crores in FY 2024-25, a decline of approximately 9.00% .

The reduction in employee costs was primarily attributable to effective workforce optimization and resource alignment undertaken in response to changing project requirements and business volumes during the year. As certain projects reached completion and business volumes moderated in select segments, the Company realigned its resources to improve utilization and enhance operational efficiency while continuing to retain and strengthen its core talent pool required to support ongoing and future business opportunities. These measures contributed to a more efficient cost structure without compromising the Companys delivery capabilities.

Further, Finance Costs decreased by 14.79% to Rupees 4.51 Crores for the financial year ended March, 31 2026, as compared to Rupees 5.29 Crores in the previous financial year.

The decline in finance costs was primarily driven by the Companys continued focus on optimizing its capital structure and reducing debt levels during the year. Supported by prudent financial management, improved cash flows, and disciplined working capital practices, the Company was able to lower its borrowing requirements, resulting in reduced interest costs. This reflects the Companys ongoing commitment to maintaining financial discipline, strengthening its balance sheet, and enhancing long-term shareholder value.

The details of the financial performance of your company are appearing in the Balance Sheet, Profit & Loss Account and other financial statements forming part of this Annual report.

SEGMENT INFORMATION

The primary business segment of your Company is Information Technology Services. The primary activity as per NIC code is Computer programming, consultancy and related activities.

FINANCIAL RATIOS

Following are ratios for the current financial year and their comparison with preceding financial year, along with explanations where the change has been 25% or more when compared to immediately preceding financial year:

STANDALONE:

S. No. Ratio Description	March 31, 2026	March 31, 2025	Change (%)	Explanation
1. Debtors Turnover/ Trade Receivables Turnover Ratio	26.49	27.75	(4.53)	-
2. Inventory Turnover	NA	NA	NA	NA
3. Interest Coverage Ratio/ Debt Service Coverage Ratio	(0.36)	(0.59)	(38.17)	The Debt Service Coverage Ratio (DSCR) improved from (0.59) in the previous year to (0.36) during the current year, resulting in a variance of 38.17%. The improvement was primarily attributable to the closure/repayment of higher interest-bearing foreign currency loans during the year, which resulted in a reduction in the Companys debt servicing obligations and finance costs.
4. Current Ratio	0.83	0.85	(2.01)	-
5. Debt Equity Ratio	0.46	0.91	(49.30)	The debt-equity ratio improved significantly to 0.46 as at 31st March 2026 from 0.91 as at 31st March 2025, representing a 49.30% reduction, primarily driven by the company\u2019s initiative to mitigate foreign currency risk by repaying external borrowings using fixed deposits and refinancing the balance through INR-denominated debt, resulting in a more stable capital structure, reduced exposure to currency fluctuations, and improved financial stability.
6. Operating Profit Margin (%)	13.79	14.30	(3.57)	-
7. Net Profit Margin (%)	0.05	0.04	24.52	The Net Profit Ratio improved to 0.05 as at 31st March 2026 from 0.04 as at 31st March 2025, reflecting a 24.52% increase, as the Company maintained strong profitability despite lower export sales, driven by a cost-plus model where reduced billing by the overseas subsidiary led to proportionate cost and revenue alignment, resulting in stable margins and improved overall profitability.
8. Return on Net Worth/ Return on Equity Ratio (%)	4.99	4.92	1.34	-

CONSOLIDATED:

S. No. Ratio Description	March 31, 2026	March 31, 2025	Change (%)	Explanation
1. Debtors Turnover/ Trade Receivables Turnover Ratio	3.87	3.65	6.21	-
2. Inventory Turnover	NA	NA	NA	NA
3. Interest Coverage Ratio/Debt Service Coverage Ratio	2.33	(2.30)	(201)	The Debt Service Coverage Ratio has improved from (2.30) to 2.33, reflecting a 201% increase, primarily due to a turnaround in EBITDA from negative to positive, indicating improved operating performance, coupled with a reduction in Interest Expense, resulting in a significant enhancement in the Company\u2019s ability to service its debt obligations during the year.
4. Current Ratio	2.31	1.63	42	The Current Ratio has improved from 1.63 to 2.31, reflecting a 42% increase, primarily due to a proportionately higher reduction in Current Liabilities compared to the decrease in Current Assets, resulting in a strengthened liquidity position and improved ability of the Company to meet its short-term obligations, demonstrating better working capital efficiency during the year.
5. Debt Equity Ratio	0.91	1.27	(28)	The Debt-Equity Ratio has decreased from 1.27 to 0.91, reflecting a 28% reduction, primarily due to a decrease in Debt along with a simultaneous increase in Equity, indicating a shift towards a more balanced capital structure and reduced financial leverage during the year.
6. Operating Profit Margin (%)	5.18	(17.97)	(128.83)	The Operating Profit Margin increased from (17.97%) to 5.18% during the current year due to improved revenue generation and operational efficiencies, resulting in a turnaround from an operating loss to an operating profit at the Group level.
7. Net Profit Margin (%)	0.01	(0.23)	(103.95)	The Net Profit Ratio has improved from (0.23) in FY 2024-25 to 0.01 in FY 2025-26, mainly due to the Company\u2019s recovery from losses to a net profit during the year. This improvement is driven by better cost control, improved operational efficiency, and the impact of corrective measures taken in the previous year. Although sales have slightly declined, the Company has been able to improve profitability through effective margin management and rationalization of expenses.
8. Return on Net Worth (%)/ Return on Equity Ratio (%)	0.02	(0.68)	(103)	The Return on Equity Ratio has improved from (0.68) to 0.02, reflecting a 103% change, primarily due to a turnaround in Net Income from negative to positive, despite an increase in Equity, indicating an improvement in the Company\u2019s profitability and more efficient utilization of shareholders\u2019 funds during the year.

CAUTIONARY STATEMENT

Certain statements in this report or elsewhere in the Annual Report may contain statements concerning Cambridge Technology Enterprises Limited and its growth prospects, expected financial position, business strategy, future development of the companys operations, general economy, industry structure and other developments that are individually and collectively forward-looking statements.

Such forward-looking statements are not guarantees of actual results, future performance or achievements and are subject to known and unknown risks, uncertainties and assumptions that are difficult to predict. These risks and uncertainties include, but are not limited to, the performance of the Indian economy and of the economies of various international markets, the performance of the industry in India and world-wide, competition, changes in government policies or regulations of India, changes relating to the administration of the company, the companys ability to successfully implement its strategy, the Companys future levels of growth and expansion, technological implementation, changes and advancements, changes in revenue, income or cash flows, the

Companys market preferences and its exposure to market risks, as well as other risks.

The Companys actual results, levels of activity, performance or achievements could differ materially and adversely from results expressed in or implied by this report. The Company assumes no obligation to update any forward-looking information contained in this report.

HUMAN RESOURCES

With 250+ employees globally, Cambridge Technologys talent pool includes experts in AI and data engineering, enterprise application development, cloud and infrastructure, and business process management.

The Company has long invested in technical certifications and professional development across its competency centres in India and the United States. During the year, we extended this commitment through the organisation-wide AI literacy programme, described in described in the Certifications section above. Being a structurally important investment, it equipped all our employees to operate effectively in an AI-augmented delivery environment.

The Company continues to attract experienced professionals in AI, ML, data engineering, and enterprise architecture. While the market demand across these disciplines remained high with specialised expertise being considered as a differentiator, talent retention, structured capability-building, and a culture of technical excellence remained foundational to our delivery model.

Active investment in learning infrastructure and internal mobility pathways ensures that the company develops and retains high-potential employees, while offering them an inclusive and supportive work environment.

OPPORTUNITIES

The technology landscape continues to evolve rapidly. This is being driven by increased enterprise focus on AI, agentic AI, data-led decision-making, cloud modernization, and automation initiatives. Businesses across industries are increasingly seeking solutions to improve their operational efficiency, enhance customer experiences, strengthen resilience, and accelerate innovation.

The Company is focused on building effective custom solutions to meet this demand. We are committed to help our customers derive measurable value from emerging technologies. It is well-placed to meet this need with our specialized technology and integration expertise, scalable implementation capabilities, and outcome-oriented transformation programs. The ongoing developments in the technology space present opportunities for the Company for our strong domain knowledge, delivery capabilities, and the ability to support clients through complex technology adoption cycles.

In addition, enterprises are increasingly prioritizing modernization of legacy systems, integrating data ecosystems, enabling responsible adoption of AI technologies, and optimizing cloud and digital infrastructure investments. The growing need for agility, compliance, security, and business continuity is encouraging organizations in the technology space to pursue long-term transformation strategies rather than isolated initiatives.

The Company believes these evolving market dynamics create opportunities across sectors and geographies where technology continues to serve as a key enabler of business growth and operational excellence. While the pace and extent of technology investments may vary across markets, the long-term fundamentals supporting AI, data, and automation-led transformation remain favourable.

Threats, Risks, and Concerns

Risk Category	Description and Mitigation Approach
Technology and Market Risk	Failure to keep pace with emerging paradigms could erode competitive positioning. The pace of development in AI, particularly in agentic and foundation model architectures, requires continuous investment in capability building. The Company mitigated this through sustained internal R&D, strategic partnerships, and the organisation-wide AI training initiative undertaken during the year.
Client Concentration Risk	The Company continues to pursue portfolio diversification across geographies and verticals. However, a portion of the Companys revenue is derived from a limited number of long-standing enterprise relationships. While these relationships are characterised by significant depth and tenure, any material change in a key clients technology investment posture could affect short-term revenue predictability.
Currency and Exchange Rate Risk	The Company\u2019s natural hedge through USD-denominated costs partially mitigates this exposure. Given that a significant proportion of the Companys revenues is denominated in foreign currencies, primarily US Dollars, fluctuations in exchange rates can affect reported financial results.
Talent Retention Risk	The competition for specialized AI, ML, and data engineering talent remains intense in the markets where the Company operates. The Company\u2019s investment in learning, career development, and a technically stimulating work environment are intended to support retention.
Regulatory and Compliance Risk	The Company\u2019s ISO and SOC 2 Type 2 certifications along with compliance infrastructure provide a structured foundation to meet these requirements. Evolving data privacy regulations, AI governance frameworks, and sector-specific compliance requirements across the jurisdictions in which the Company operates, necessitate continuous monitoring and adaptation.
Macroeconomic Risk	The Company monitors macroeconomic indicators as part of its pipeline and demand forecasting activities. Broader economic uncertainty in key markets, including the United States, may result in clients deferring or reducing technology investment.

INTERNAL CONTROL SYSTEMS AND ADEQUACY

System Design and Scope: The Company maintains internal control systems commensurate with the nature, size, and complexity of its operations. These systems are designed to ensure the reliability of financial reporting, the safeguarding of assets, the prevention and detection of errors and fraud, compliance with applicable laws and regulations, and the effective and efficient conduct of operations.

Audit Committee Review: The Companys Audit Committee reviews the effectiveness of internal controls periodically and engages with the Statutory and Internal Auditors to assess the adequacy of controls and the timely remediation of observations. During the year under review, no material weaknesses in internal financial controls were identified that would have a material impact on the Companys financial reporting.

Information Security Posture: The Companys information security posture is supported by its ISO certifications, which mandate documented policies, structured audit processes, and clearly defined roles and responsibilities across data handling, service delivery, and compliance functions.

ISO/IEC 20000-1:2018 Certification: Attainment of ISO/IEC 20000-1:2018 certification validates that we meet international IT Service Management Systems standards.

ISO/IEC 27001:2022 Certification: Attainment of ISO/IEC 27001:2022 certification validates our continued efforts toward ensuring data safety and complying with the highest security standards.

TISAX Certification: Attained TISAX certification, which assesses the security of CTEL IT infrastructure, processes, and systems to protect to protect its critical assets, data, and services.

SOC 2 Type 2 Certification: Attained SOC 2 Type 2 certification, which assesses Managements Description of a Service Organizations System Relevant to Security, Confidentiality, Availability and the Suitability of the Design and Operating Effectiveness of Controls.

OUTLOOK

Strategic Focus: The Company enters fiscal year 2026-27 with a well-defined strategic focus. Its portfolio of capabilities is closely aligned with the most significant demand trends in enterprise technology. The Agentic AI practice is now a formally structured and commercially active service line. It is expected to be a meaningful contributor to pipeline development over the coming quarters. The Companys established presence in enterprise AI, data engineering, and application development provides a synergistic backdrop to this newer practice.

Industry-specific Growth Pathways: Industry-specific solution development across healthcare, life sciences, animal health, and pet nutrition sectors represents a differentiated and commercially promising growth pathway. The Company will continue to develop deep, domain-calibrated capabilities in these areas. It continues to build on the engagement and interest generated during the current year.

Strategic Partnerships: The Companys strengthened Oracle and Salesforce partnerships are expected to generate incremental commercial activity. Clients in these ecosystems increasingly seek AI-integrated enhancements to their existing platform investments. The Company is well-positioned to serve this demand.

Operating Dynamics: The Company is mindful of the macroeconomic and competitive dynamics of its operating environment. Accordingly, it will continue to pursue disciplined investment, focused capability development, and the deepening of its long-term client relationships as its primary strategic priorities.

Forward-Looking Statement: This section contains forward-looking statements that reflect the Companys current views and expectations regarding future events and business outcomes. These statements are subject to known and unknown risks, uncertainties, and other factors that may cause actual results, performance, or achievements to differ materially from those expressed or implied. Investors are advised not to place undue reliance on such statements.

INDUSTRY STRUCTURE, DEVELOPMENTS & OPPORTUNITIES

OUR SERVICES

AI & Machine Learning

Agentic AI & Automation

SaaS Solutions & Custom Apps

Cloud Migration & Transformation

Enterprise Mobility

Managed Services

Business Intelligence & Analytics

IoT & IIoT Services

Cybersecurity

Data Analytic s & Engineering

We meet businesses across sizes, industries, and geographies where they are to help them deliver operational efficiencies, enable better user experiences, and streamline workloads with tailor-made services and solutions. With over two decades of expertise as a global technology services company, we help them solve complex challenges with intelligent service across domains like AI, machine learning, data engineering, enterprise applications, SaaS, and DevOps. From offering strategic workshops and ready-to-deploy solutions to state-of-the-art integrations, we help enterprises enable a tech stack that stands the test of time.

Headquartered in India with marketing and support from the US, we pride ourselves on partnerships with experts like AWS, Confluent, Google, Oracle, Atlassian, Tricentis, and many more to give our customers the best technology in the market. This is why we have competencies in niche technologies from our partners to help customers understand what they need and how to implement it seamlessly. We bring certainty to delivery standards while helping customers scale up quickly to create a digital workspace, embedding resiliency, continuity, and security.

Our experts-led service offerings and extended partner ecosystem help enterprises with:

Operationalizing AI to derive last-mile value

A data lifecycle approach

State-of-the-art integrations

Unified systems for data sanitation & analytics

Unified infrastructures for compute, storage, & networking

Customized strategies & implementation roadmaps

Performance-oriented monitoring

Governance & testing for deployments

SERVICE OFFERINGS

Recognized as a thought leader with ISO 20000-1: 2018 and ISO 27001:2022 certifications, our gamut of end-to-end services in AI, data, applications, infrastructures, and the cloud can help with every unique, complex challenge. Our services, solutions, and over 250 + employees transform businesses for a changing world with strategic workshops to ready-to-deploy solutions.

Artificial Intelligence

AI and Agentic AI

Our AI practice delivers enterprise-grade integration of advanced AI models and agents into daily enterprise operations, increasing efficiencies, predictive capabilities and data-based insights. With deep domain expertise in operationalizing AI, we enable enterprises to drive efficiencies, optimize processes, and deliver meaningful outcomes with custom models and solutions, real-time intelligence, cross-platform interoperability, accelerating time-to-value and innovation. Our AI solutions leverage predictive analytics, NLP, computer vision, and other capabilities to drive data-driven decisions at scale for enterprises, keeping them ahead of the competition.

Data Engineering

Our data engineering services provide the foundational backbone for enterprise AI and analytics initiatives. We design and implement modern data architectures that unify fragmented data sources, enable real-time processing, and support scalable analytics across hybrid and multi-cloud environments. From building robust data lakes and ETL pipelines to enabling data observability and lineage, we ensure that enterprise data is accessible, reliable, and AI-ready with curated solutions engineered for performance, compliance, and seamless integration with downstream AI and BI systems

Enterprise Applications

Through our enterprise application services, we help modernize core business systems and enable seamless interoperability across digital ecosystems. We architect, develop, and integrate cloud-native applications tailored to enterprise needs-spanning ERP, CRM, supply chain, and workforce solutions. With our approach focused on modularity, API-first design, and low-code extensibility, our solutions help enterprises accelerate deployment and adaptability, embedding analytics and AI into enterprise workflows, driving automation, optimizing user experiences, and ensuring business continuity across complex, distributed environments.

Our Expertise

Artificial Intelligence

Agentic AI

Machine Learning

Data Engineering & Analytics

Natural Language Processing

Data Platforms & Integrations

Computer Vision

Predictive Analytics

Conversational Apps

Data Strategy & Governance

DataOps

SaaS & DevOps

FOCUS INDUSTRIES

Businesses today need to upgrade and keep up with trends for uninterrupted operations. On the other hand, new companies might need more tools or expertise to conduct effective transformations. This is where we help.

See the various use cases that we work on with decades-long expertise across verticals like energy/industritals, manufacturing, life sciences & pharmaceuticals, banking and financial services (BFSI), and security/access management.

Data Infrastructure

Retail

Pharma & Life Sciences

Energy

Banking/Insurance

Manufacturing

Rapid Prototyping

Healthcare

Automotive

Telecommunication

Identity & Access Management

Logistics