Below is a tabular comparison of E2E Networks Limited’s financial performance, highlighting key expenses and metrics on a quarter-over-quarter (QoQ) and year-over-year (YoY) basis:
| Particulars | Q2 FY2025 | Q1 FY2025 | QoQ Change | Q2 FY2024 | YoY Change |
|---|---|---|---|---|---|
| Revenue from Operations | ₹47.55 crore | ₹41.33 crore | 15.03% | ₹21.65 crore | 119.52% |
| Other Income | ₹0.86 crore | ₹0.34 crore | 152.94% | ₹0.40 crore | 115.00% |
| Total Income | ₹48.41 crore | ₹41.67 crore | 16.15% | ₹22.05 crore | 119.52% |
| Expenses: | |||||
| – Purchase of Services and Consumables | ₹7.24 crore | ₹6.67 crore | 8.54% | ₹5.06 crore | 43.07% |
| – Employee Benefit Expenses | ₹6.09 crore | ₹5.11 crore | 19.37% | ₹3.61 crore | 68.69% |
| – Depreciation and Amortization | ₹12.57 crore | ₹10.70 crore | 17.52% | ₹2.53 crore | 396.44% |
| – Finance Costs | ₹3.62 crore | ₹3.36 crore | 7.74% | ₹0.36 crore | 905.56% |
| – Other Expenses | ₹2.78 crore | ₹2.27 crore | 22.47% | ₹1.80 crore | 54.44% |
| Total Expenses | ₹32.30 crore | ₹28.11 crore | 14.92% | ₹13.36 crore | 141.79% |
| Profit Before Tax | ₹16.11 crore | ₹13.56 crore | 18.79% | ₹8.69 crore | 85.34% |
| Tax Expenses | ₹3.96 crore | ₹3.42 crore | 15.79% | ₹2.90 crore | 36.90% |
| Net Profit After Tax | ₹12.15 crore | ₹10.14 crore | 19.79% | ₹5.79 crore | 109.80% |
Q2 Result.pdf (6.1 MB)
While the results are impressive across various financial metrics, I was hoping to see stronger topline growth. The generative AI industry in India still has a long way to mature, but as this transformational technology is adopted across industries globally, it opens up opportunities for new players—especially those focused on GPU-intensive rather than CPU-centric hyperscalers. This shift is not limited to India but is a worldwide trend. Incumbents like AWS and Azure are also making strides in the GPU space with some exciting innovations. The key reason I believe new entrants can capitalize on this is the evolving usage of technology by emerging companies. Unlike the pre-generative AI era, when cloud computing was a smaller part of total expenditures, cloud GPU costs are now becoming a major factor in business models of tech companies.
As investors, I believe we need to stay vigilant regarding the rapidly shifting landscape of this industry. This could be one of the fastest technological shifts the world has seen. The drivers of this change include rapid advancements in GPU chip technology, improvements in large language models (LLMs), AI Agents and quicker adoption of AI across industries. Over time, the cost of these components will decrease, further driving demand, innovation and adoption.
Exciting times lie ahead!
Disclosure – Invested
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