Making Every Watt Count: Ayush Gupta on How Enlog Cuts Electricity Costs by About 23% with AI

In this engaging interaction with StartupTalky, Ayush Gupta, Co-founder and CTO of Enlog, sheds light on how his company is cutting energy waste and saving businesses up to 23% on electricity bills. From PGs to hotels, he explains how Enlog’s AI-driven tech spots waste, acts fast, and even prevents disasters. Gupta shares how building everything in-house gave them an edge in the energy space. With bold plans to cut 1 million tonnes of carbon emissions by 2027, Enlog is not just about smart savings, it is about shaping a cleaner, more efficient future for India.

StartupTalky: Your solutions reportedly reduce energy consumption by up to 23%. Based on your deployments, what typical electricity usage patterns have you observed in hostels, PGs, and hotels? What are the primary sources of wastage you have identified?

Mr. Gupta: We've seen consistent energy wastage from ACs, geysers, and common area appliances running without occupancy. In PGs and hostels, lights and fans are often left on 24/7. In hotels, HVAC systems run in unoccupied rooms due to a lack of control integration. Our system cuts this by responding to usage patterns, real-time data and occupancy, with zero human intervention. That’s why the 23% reduction reflects our average outcome. 

StartupTalky: Since being founded in 2019, Enlog has seen strong revenue growth, from INR 17 lakh in FY23 to INR 1 crore in a month. Could you explain the key drivers behind this growth and the strategies that enabled this scale-up? 

Mr. Gupta: That scale wasn’t just from selling devices, it came from proving that intelligence, once embedded into infrastructure, compounds. 

Our growth came from three levers: a full-stack product (hardware + AI + UI), a plug-and-play deployment model, and a results-oriented GTM. We didn’t ask clients to trust dashboards instead, we let them see savings in their bills. That propelled our expansion.

StartupTalky: Enlog has managed over 20,000 MWh of electricity and reduced more than 4,000 tonnes of carbon emissions. On average, how much electricity does each client manage through your systems, and what is the typical emissions reduction per client? How do these outcomes relate to the cost of implementation and the average payback period for different types of businesses? 

Mr. Gupta: On average, each client manages approximately 15 MWh of electricity annually through our systems. This management translates to a reduction of about 2.7 tonnes of carbon emissions per client per year. But what really matters to businesses is ROI.

The cost of implementing our solutions varies based on the scale and specific requirements, but typically sees a return on investment within 8 to 10 months, thanks to the substantial savings on electricity bills.

StartupTalky: Enlog aims to help India reduce 1 million tonnes of carbon emissions by 2027. Based on your current impact, what annual reduction rate do you need to achieve this goal? What strategies are you putting in place to accelerate your progress? 

Mr. Gupta: To reach our goal of reducing 1 million tonnes of carbon emissions by 2027, we need to average an annual reduction of approximately 250,000 tonnes. Our strategy includes expanding our client base faster across various sectors, enhancing our energy-saving tech further, and forming partnerships to scale further. We are also offering ESG and impact reporting to help clients integrate emissions into their operational decisions.

StartupTalky: With global electricity demand expected to rise by 40% by 2040, how does Enlog’s technology help address peak demand challenges? Could you share data or examples from any pilot projects that highlight your impact on reducing peak loads? 

Mr. Gupta: Peak load management is where intelligence matters most. For example, in a pilot project with a mid-sized hotel, our system reduced peak load by 15% by optimising the operation of HVAC systems based on occupancy and external temperature data. Our system doesn’t just respond, it predicts. By modelling consumption spikes and load cycles, we enable buildings to flatten their own demand curves, like traffic signals managing congestion. 

Such interventions not only lower energy costs but also contribute to grid stability on a scale. 

StartupTalky: You are expanding into metro cities like Hyderabad, Pune, Mumbai, and Bengaluru. What client growth are you targeting in these markets over the next two fiscal years, and what regional differences in energy usage patterns have you noticed compared to Delhi-NCR? 

Mr. Gupta: These cities have unique energy usage patterns; for instance, Mumbai’s high humidity levels lead to increased HVAC usage, while Bengaluru’s moderate climate results in different consumption behaviours. Understanding these regional differences allows us to use location-based AI presets to adapt across climates. We’re targeting an 8x growth in our client base as we expand across metro cities over the next two fiscal years.

StartupTalky: Enlog is transitioning to edge computing with custom System on Chips (SoCs). What improvements in data processing speed and latency do you expect from this shift, and how will it enhance real-time electricity optimisation for your users? 

Mr. Gupta: Our shift to edge computing with custom System on Chips (SoCs) means decisions happen milliseconds after data is captured, right at the edge. But this shift isn’t just about speed, it’s about true autonomy. For our clients, this means instant, intelligent adjustments that improve savings and system responsiveness. In incidents where milliseconds matter, like preventing overheating or short circuit, this kind of on-chip decision-making makes all the difference. 

StartupTalky: Enlog was founded with a core question: why is electricity still treated as a fixed cost when it can be optimised? How did this philosophy shape your initial product roadmap and go-to-market strategy, particularly for cost-sensitive sectors? 

Mr. Gupta: I’ve always believed electricity is too critical to everyday life to be treated as a blind expense. Our roadmap started with one question: how do we make every watt self-aware? 

That led to our approach: one universal device, built for autonomous action, not just visibility. We entered through cost-sensitive sectors not because they were easy, but because they had the most to gain. If you can build intelligence that works at a PG-level unit cost, where we help in improving their profitability, you can scale it anywhere. 

StartupTalky: Your AI not only monitors but actively diagnoses and optimises energy usage. Could you share a real-world example where your system helped prevent significant energy loss or equipment failure? 

Mr. Gupta: In one instance at a co-working space, we saw meeting room ACs running without any occupancy for hours, but no one noticed that. Our models identified it, learned the pattern, and started switching them off when not needed. It didn’t rely on alerts or manual intervention rather, it simply made the decision and delivered savings. 

Then there was a hotel where we caught a phase imbalance. It could’ve ended badly. The system spotted it, isolated the circuit, and sent a ping to maintenance. It happened fast. No one had to think. That’s when it hit me, we’re not just saving energy, we’re preventing disasters.

StartupTalky: You have built both hardware and software entirely in-house, which is rare among startups. What were the biggest challenges you faced during development, and how does owning the technology give Enlog a competitive advantage over those using off-the-shelf solutions? 

Mr. Gupta: Developing both hardware and software in-house posed challenges, including the need for specialised talent and significant R&D investment. However, I believe in first-principle thinking. This approach allowed us to create highly integrated and customised solutions, giving us a competitive edge over companies relying on off-the-shelf products. Owning the full stack gives us the freedom to scale faster and make something that never existed before. 

Our proprietary technology ensures better performance, scalability, and solves the real problems of client needs, which no one is doing.

StartupTalky: With installations across more than 1,580 PGs and 120 hotels, how do you ensure consistent system performance and scalability? What does your support and maintenance model look like to manage such a large and widespread client base? 

Mr. Gupta: We’ve built our system like a telecom network-designed to handle heavy loads with low latency, fault tolerance, and automatic scalability. Just like how network technology gets connected even in remote areas, our solution works smoothly in low-network zones across India. We monitor performance proactively, so often we know about issues before our clients do. 

From day one, we designed for scale, aiming to reach every corner of the country. Our operations model is lean by design: instead of adding more support staff as we grow, we scale intelligence through AI-driven tools, being a tech-first startup, a true tech-first approach to sustainable growth. 

StartupTalky: Enlog was recently recognised with a DeepTech & AI award at Startup Mahakumbh 2025. How do awards like these contribute to building your brand credibility, attracting talent, and forming strategic partnerships? 

Mr. Gupta: Winning the DeepTech & AI award at Startup Mahakumbh 2025 was a huge boost for us, especially after a rigorous assessment by a national panel of industry experts, confirming we're ahead of others in this space. It’s not just about the recognition, but the validation that we’re leading in a complex space where energy, hardware, and AI come together.

Having Union Minister Piyush Goyal visit our booth and appreciate our innovation was incredibly motivating for the whole team. Awards like this really help open new doors and build trust with potential partners, and attract talented people who not just build apps but aspire to innovate.

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