This Legal article is written by Kirti Rai
BALLB ,9TH SEM
RAYAT BAHRA UNIVERSITY, MOHALI
Introduction
It’s late at night. The streets outside are quiet, your stomach is not. You open Swiggy or Zomato, scroll through menus, and place that order for pizza or biryani. What happens next looks simple: the app confirms your order, tells you it has found a delivery partner, and promises food at your door in 30 minutes.
But the real drama is happening in the background. The app isn’t just flipping a switch. It is running a chain of complex calculations—working out which rider is closest, which route is less clogged with traffic, whether it should group two deliveries together, and how to make sure you get food that still feels fresh. It’s like dozens of small puzzles being solved at the same time, every single second, for thousands of people.
This hidden machinery—these invisible algorithms—are the true backbone of food delivery platforms. And that’s where the big question begins: can these systems be patented? Should companies like Swiggy and Zomato be able to say, “This is our invention, and nobody else can copy it without permission”?
If they can’t, a rival platform might copy the logic overnight. That would make innovation feel pointless. But if they can, there’s the risk of locking up ideas that are essential to fair competition. Patent law was written in a very different era, long before apps and algorithms were part of daily life. And now, we’re trying to make old rules fit new realities.
This isn’t just a dry legal debate. It has real consequences—for the engineers who design these systems, for the riders who depend on fair assignments, and for customers like you who just want food to show up on time.
Most of us never think about this hidden machinery. To us, the app feels like magic—food appears when we tap a screen. But for the companies, the magic comes from sweat, sleepless nights, and constant trial-and-error. Teams of engineers spend weeks fixing small bugs, riders give feedback about what slows them down, and data scientists tweak formulas late into the night. It’s not glamorous, but it’s what keeps your midnight cravings satisfied.
The Technology Behind Food Delivery Platforms
To understand why patents matter here, you have to know what’s actually happening inside these apps. Swiggy and Zomato aren’t just restaurants on a screen—they’re massive logistics companies disguised as food apps. And logistics is hard.
The heart of the system is a set of assignment algorithms—rules that decide who gets what order, when, and how. These algorithms are constantly pulling in live data from different sources. Imagine a giant control room with screens showing traffic updates, rider locations, restaurant delays, and customer demands. Except there is no human control room—it’s all automated.
Think about it from the rider’s point of view. A rider logs in at 6 PM on a Friday evening in Mumbai. The app sends him three orders in a row, all from different restaurants, but somehow the route works out smoothly. He picks up the first, then the second, and drops them off without getting stuck in a traffic nightmare. The rider doesn’t see the complex logic behind it—he just knows the app made his night easier. But if the algorithm is poorly designed, the same shift could be a nightmare: long waits at crowded restaurants, angry customers, wasted fuel. For the rider, the quality of the algorithm is the difference between earning enough for rent or barely breaking even.
Some of the main parts of this puzzle:
Location Matching: The app has to pick the right rider for the job. It’s not always the closest one. Maybe the nearest rider is about to take a break, or maybe they’re already overloaded. The system must decide in seconds.
Traffic Prediction: Real-world roads are unpredictable. GPS and AI models try to figure out the best possible estimate. A 10-minute route on paper could turn into 25 minutes if a protest blocks the road.
Order Clubbing: If two people in the same neighborhood order at the same time, it makes sense to give them the same rider. But if the timing is off, everyone ends up waiting. The algorithm has to balance efficiency with customer satisfaction.
Dynamic Pricing: When it rains in Bengaluru, suddenly there aren’t enough riders. The app quietly raises delivery fees to encourage more riders to log in. The algorithm is deciding how much to charge you.
Customer Preferences: The system even remembers small things—if you always tip well, or if you hate onions, or if you tend to cancel orders when the wait is too long. This data feeds into future decisions.
Let’s take a real example. You order biryani from Connaught Place in Delhi during lunch rush. The app doesn’t just say, “Find nearest rider.” It checks whether the restaurant is running late with orders, whether traffic around Rajiv Chowk is backed up, whether the rider nearby has already been on the road for too many hours, and whether two more orders from Karol Bagh can be added to the same trip without messing up timings. All this happens in seconds. And you see only a clean little line: “Your order has been picked up.”
So the question is: does the complexity of this system automatically mean it should be treated as an invention worthy of patent protection? Or is it just smart problem-solving using tools everyone already has access to?
Patent Law Basics
Here’s where the law enters the picture. In India, patents are governed by the Patents Act of 1970. On paper, the requirements are straightforward:When this law was written, nobody could have imagined today’s world. The internet was still decades away, and food delivery apps weren’t even a dream. The law was designed to protect machines, chemical compounds, and physical inventions—things you could hold in your hand. Algorithms and AI-driven platforms blur the lines. They’re invisible but powerful, and they don’t fit neatly into the old boxes. That mismatch is why so much confusion exists today.
1. The invention must be new. No one in the world should have published or used it before.
2. It must involve an inventive step—something not obvious to others in the field.
3. It should have industrial application—meaning it’s useful in practice, not just on paper.
4. And crucially—it must not fall under the list of exclusions.
This is where software and algorithms run into trouble. Section 3 of the law specifically excludes “mathematical methods, business methods, computer programs per se, and algorithms.” In plain words: if all you’ve invented is a formula, a business trick, or a piece of code, you can’t patent it in India.
But the world outside India is not so strict. In the US and Europe, patents are allowed if the software shows a technical effect—for example, improving logistics, enhancing safety, or optimizing energy use. China is even more flexible, granting patents on software-based innovations as long as they are practically applied.
This mismatch is why Indian startups feel stuck. They operate in a global digital economy, but their home country has rules written for a different time.
Are Algorithms Patentable in India?
At first glance, the answer is simple: no. Section 3(k) says algorithms are out. End of story.
But here’s where things get real. Courts are not abstract—they deal with actual disputes brought in by companies and individuals. When a company spends crores building an AI system that genuinely improves delivery times, judges can’t ignore that it has value. At the same time, they also know that if they start granting patents too freely, one company could monopolize everyday methods, choking competition. This tug-of-war between protecting innovation and keeping markets fair plays out in every hearing, every appeal, every ruling.
But the reality is messier. Indian courts have shown that not every computer-based invention is automatically rejected. If the invention goes beyond abstract calculation and creates a technical effect in the real world, it might stand a chance.
Think of it like this:
If you try to patent a formula that calculates the shortest distance between two points, that’s clearly abstract and won’t be allowed.
But if you design a system that takes GPS signals, weather reports, rider energy levels, and traffic updates, and then produces a new way of scheduling deliveries that saves fuel and reduces delays—that’s a real-world technical solution. Courts might listen.
The hard part is drawing the line between “just code” and “code that solves a tangible technical problem.” Delivery systems live right in that grey area.
Comparative International Perspective
Looking at how other countries treat software patents makes the contrast sharper.
United States: The Alice Test asks two questions. First, is the invention an abstract idea? Second, does it add something inventive enough to make it practical? A simple routing app might fail, but Amazon’s “anticipatory shipping” patent passed because it changed how logistics worked at scale.
What’s fascinating here is that global companies already design their strategies around these differences. For example, a startup in Bengaluru may avoid filing in India because of Section 3(k), but the very same invention could be filed in China or the US where the chances are higher. This creates a patchwork situation: the same piece of technology might be considered an “invention” in one country and “just code” in another. For founders and investors, this is confusing but also strategic—they know where to push, where to hold back, and where to play safe.
European Union: The EU focuses on “technical character.” The software must solve a technical problem in a technical way. If a delivery algorithm reduces accidents or improves fuel efficiency, it could qualify.
China: Much more generous. If the invention shows practical application, it can be patented. Given China’s booming food delivery sector, companies like Meituan file patents regularly.
India: Still cautious. Courts sometimes show flexibility, but the law hasn’t caught up. Pressure is building as startups grow and global competition increases.
Case Studies & Precedents
A few famous cases show how the system has worked elsewhere:
Amazon’s One-Click Patent: A simple idea—buying with one click instead of a cart process—turned into a major patent win for Amazon. It was controversial, but it gave Amazon a huge edge.
Uber’s Routing Patents: Uber has successfully patented some of its ride allocation methods, which look a lot like food delivery assignment systems. If it works for rides, why not for food?
These cases also show how blurry the line is between “obvious” and “inventive.” Amazon’s one-click patent looked ridiculously simple to outsiders, but it reshaped how millions of people shop. Uber’s routing patents seem like technical tweaks, but in practice they changed how rides are matched worldwide. The Ferid Allani case gave Indian companies a ray of hope—but the problem is, no two judges may interpret “technical effect” in exactly the same way. That uncertainty makes it risky to spend money on filing patents in India.
Ferid Allani Case in India (2019): The Delhi High Court said computer-related inventions can be patentable if they make a “technical contribution.” This case is often cited as hope for software patents in India.
Challenges in Patenting Delivery Algorithms
Even if the door is open a little, big challenges remain:
The Section 3(k) wall is still there. It blocks most software claims.
Imagine a startup founder in Delhi with a clever new system for clubbing multiple orders. She knows the idea works, she’s tested it, riders love it, customers benefit from shorter waits. But when she tries to file a patent, the examiner says, “This is just an algorithm.” She could spend years in legal battles, pouring money into lawyers instead of product development. By the time she gets a ruling, bigger rivals might have already rolled out a similar system. That’s the reality many young founders face.
Overlap with copyright and trade secrets—code is already protected by copyright, and methods can be kept confidential.
Proving novelty is hard—lots of platforms use similar routing logic. Distinguishing one from another is messy.
Technology moves too fast—by the time a patent is granted, the system might already be outdated.
Public interest worries—if one company locks up key delivery methods, competition shrinks, costs rise, and customers suffer.
Humanising the Debate
Picture a young engineer in Swiggy’s Bengaluru office. It’s pouring outside, deliveries are breaking down, riders are exhausted, and customers are angry. She spends nights tinkering with a model that predicts rain patterns, adjusts assignments, and prevents riders from being overloaded. After months, it works—complaints drop, riders get fairer workloads, and food arrives hotter.
Now flip the story. Think about a delivery rider pedaling through Chennai traffic in the blazing sun. He doesn’t care about patents or legal jargon. All he wants is an app that doesn’t overload him with three orders in opposite directions. For him, a well-designed algorithm means fewer angry phone calls from customers, fewer wasted kilometers, and maybe even enough time to grab a cup of tea between orders. When courts debate whether these systems should be patentable, they’re indirectly shaping his daily reality, even if he never knows it.
Should her work be patentable?
If yes, she and her company get recognition and protection. Innovation feels worth it.
If no, another platform could copy the same idea tomorrow, and her effort would feel wasted.
This is where the debate feels less like law and more like life. Because patents don’t just affect lawyers in suits. They affect delivery partners who spend hours on bikes. They affect customers waiting for dinner. And they affect the young minds in tech hubs who want their work to matter.
The Future of Food Delivery Patents in India
So where do we go from here?
The bigger question is whether India wants to position itself as a leader in digital innovation or remain cautious. On one side, there’s the risk of letting companies lock up basic ideas. On the other, there’s the danger of driving talent away if they feel their work will never be protected. In a country where millions of young engineers are entering the workforce, the way we settle this debate could decide whether the next breakthrough in AI logistics is born in Bengaluru or in Silicon Valley.
India might eventually reform Section 3(k) to make space for AI and software-based inventions.
Courts may start recognizing AI-driven systems that clearly show technical effects.
Companies might adopt hybrid protection models—using copyright, trade secrets, and patents together.
Swiggy and Zomato may simply go abroad for patents, creating a patchwork of protections across countries.
Recommendations
Companies: Draft smarter patent applications. Highlight the technical impact, not just the logic.
Policymakers: Update the law. A digital economy cannot run on rules written for a pre-digital world.
Courts: Keep the door open for innovations that solve real problems.
Startups: Don’t rely only on patents. Use trade secrets and strong internal controls to guard your edge.
Conclusion
The debate over whether Swiggy and Zomato’s delivery algorithms should be patentable is not just about law—it’s about fairness, progress, and recognition.
Think of it this way: every time your food arrives on time, hot and intact, there’s a silent network of people and programs making it happen. Riders on bikes, engineers behind screens, algorithms crunching data—they all work together. Whether or not the law calls this patentable doesn’t change the effort that went into it. But it does change who gets credit, who gets rewarded, and who gets to keep building the future. That’s why this question matters so much more than it looks on the surface.
India’s law is still conservative, but cracks are appearing. Courts are slowly acknowledging that not all algorithms are abstract, and some deserve protection. Globally, the trend is moving toward acceptance, especially for applied software systems.
The balance is delicate. We need to reward engineers for creating better systems, but not in ways that crush competition or make food delivery unaffordable.
Food delivery may look simple from the outside, but it’s really a web of technology, law, and human effort. Algorithms shape whether your meal arrives hot, whether a rider gets a fair break, and whether young innovators feel their work matters. The legal system has to decide how much of this hidden machinery deserves to be locked up as private property, and how much should remain open so the whole ecosystem can grow.
One thing is certain: algorithms will keep changing how we eat, how we work, and how we live. The question is whether the law can keep up.
