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AnalysisMar 2026

Deferred Leverage: Why Deeptech P&Ls Read Differently

Ten years, three sectors, one theme. Ingro co-founder Ankit Mittal on Deferred Leverage — the condition in which a cost structure is engineered to compress at scale, but the compression lags revenue growth by design.

Schematic of Deferred Leverage — an illustration of the mechanism described in this post, not plotted from a specific company's accounts. Revenue inflects smoothly; unit cost falls only in steps, as yields improve, tooling amortises, supply chains localise and volume crosses its threshold. The gap between the two inflections is the lag.
Schematic of Deferred Leverage — an illustration of the mechanism described in this post, not plotted from a specific company's accounts. Revenue inflects smoothly; unit cost falls only in steps, as yields improve, tooling amortises, supply chains localise and volume crosses its threshold. The gap between the two inflections is the lag.

Ten years. Three sectors. One theme: deeptech. Robotics (GreyOrange). EVs (Sheru). Energy (Ingro Energy).

Every time Nakul Mehan, Shikhar Sharma and I built deeptech products, the hardest conversation was with capital. "Disruptive technology, and still the margins are thin. Why?"

Deferred Leverage

We call it Deferred Leverage: the condition in which a business's cost structure is engineered to compress at scale, but the compression lags revenue growth by design. It is the mechanism that bridges the gap between top-line inflection and bottom-line inflection.

The cost curve compresses in steps — when yields improve, when tooling amortises, when potential downsides taper out, when supply chains localise, when volume finally crosses the threshold you have been engineering toward for 18 months.

A SaaS business earns its margin the day it signs the contract. A hardware business earns it on a future production run. The P&L looks the same in year two. The trajectories are completely different.

A translation problem

The benchmark was built for a different kind of business. Deeptech speaks in curves, cycles and compounding thresholds. Capital speaks in milestones, multiples and quarterly marks. Same business, two different readings of the same data.

A translation problem needs translators. Not consultants. Not advisors. People who have lived both sides — who speak the language of the technology and the language of the business cycle it will disrupt. We call them Oracles.

Finding the Oracles first

We started building Ingro Energy differently. We found our Oracles first: Mr. Shailesh Mishra, who has lived the energy sector's cycles across decades, and Mr. Naga Satyam, who understands battery technology at a depth China spent thirty years ensuring no one outside their borders would.

The thesis, stated plainly

Ingro Energy provides AI-powered Battery Energy Storage Solutions (BESS) to enterprises and SMEs. The idea is simple — help businesses save money on electricity — and the problem is as simple as this chain:

  • Energy is strategic, hence tightly regulated
  • Energy rules are complex, since starting from scratch is not an option
  • Energy is a constant optimisation problem for everyone
  • Lower cost is achievable via the right and diverse mix
  • A diversified mix needs bundling via storage
  • Every business needs a custom solution
  • An AI substrate is necessary to deliver custom solutions for the many

Execution feeds learning. Learning feeds execution. Keep at it.

With India's deeptech capital finally catching up to its builders — with stimulus from the Office of the Principal Scientific Adviser to the Government of India — the conversation about how to model the non-linear path of building deeptech products is ready to be had.

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