Why you should build more AI wrapper businesses

In the fast-paced world of tech startups, AI is the new frontier. However, a common critique threatens to derail many promising ventures:

“Isn’t this just an AI wrapper?”

This question, often posed by venture capitalists, can spell doom for startups building on existing AI platforms. But is the situation as dire as it seems?

Nope.

[Reproduced from Ashish Sinha’s newsletter]

The Wrapper Dilemma

When pitching an AI startup, founders often face skepticism about the uniqueness of their offering. Questions like “What if ChatGPT enables this?” highlight the fear that major AI platforms could easily replicate or obsolete these startups’ functionalities.

However, dismissing all AI wrappers outright might be shortsighted. To understand why, let’s examine the recent history of successful tech businesses.

Case Studies: SAAS and Fintech

In the last decade, two categories have dominated the tech startup landscape, particularly in India:

1. SAAS (Software as a Service)
2. Fintech

These sectors have attracted significant funding and M&A activity. Interestingly, both can be considered “wrapper” businesses in their own right.

SAAS: More Than Just Database Wrappers?

At their core, SAAS products are sophisticated database wrappers. They perform CRUD (Create, Read, Update, Delete) operations through user-friendly interfaces, enhanced with business logic. However, their value proposition extends far beyond this simplification:

• User Experience: SAAS products offer intuitive interfaces that make complex data operations accessible to non-technical users.
• Industry-Specific Solutions: Many SAAS companies tailor their offerings to specific industries, incorporating deep domain knowledge.
• Integration and Automation: By connecting various data sources and automating workflows, SAAS products create efficiencies that individual databases cannot match.
• Analytics and Insights: Advanced SAAS offerings provide valuable business intelligence derived from the data they manage.

India’s Fintech == UPI Wrapper

In India, the fintech revolution is largely built upon UPI (Unified Payments Interface), a real-time payment system run by the consortium of major banks government.

While it’s true that UPI forms the backbone of many fintech services and it’s just fine to call fintech startups UPI wrappers, successful companies in this space offer much more:

• User-Friendly Interfaces: Fintech apps simplify complex financial transactions for millions of users.
• Unique use-cases/Value-Added Services: From budgeting tools to investment advice, fintech companies layer additional services on top of basic payment functionality.
• Financial Inclusion: Many fintech startups focus on bringing banking services to underserved populations.
• Data-Driven Insights: By analyzing transaction data, fintech companies can offer personalized financial products and services.

The fintech sector in India has attracted over $20 billion in funding in just the last four years, demonstrating the immense value investors see in these “wrapper” businesses.

The Case for Wrappers

So why do wrapper businesses succeed? The answer lies in the value they provide to end-users and businesses:

1. Problem-Solving: Successful wrappers address specific pain points that the underlying platforms don’t solve directly.
2. Efficiency: They often streamline processes, saving time and resources for their users.
3. Accessibility: Wrappers can make complex technologies accessible to a broader audience.
4. Specialization: Many wrapper businesses focus on niche markets, offering tailored solutions that general-purpose platforms can’t match.

The key principle here is the Jobs-To-Be-Done (JTBD) framework.

Users don’t care whether a product is a “wrapper” or a groundbreaking innovation; they care about how well it solves their problems.

Building Successful AI Wrappers

For AI startups looking to succeed in this competitive landscape, here are some strategies to consider:

1. Deep Integration: Go beyond simple one-step wrappers. Create solutions that integrate AI capabilities deeply into existing workflows or industries.
2. Domain Expertise: Combine AI with specialized knowledge in specific sectors. This creates barriers to entry that even advanced AI platforms might struggle to replicate quickly.
3. User Experience: Focus on creating intuitive interfaces and experiences that make AI accessible to non-technical users.
4. Data Advantage: If possible, build proprietary datasets that enhance the AI’s capabilities in your specific domain.
5. Continuous Innovation: Stay ahead by constantly improving your offering and expanding its capabilities.
6. Solve Complex Problems: Target multi-step processes or complex workflows where your wrapper can add significant value.

TL;DR

While the fear of being “just another AI wrapper” is valid, history shows us that wrapper businesses can be immensely successful when they provide real value. The key for AI startups is to focus on solving genuine problems, leveraging domain expertise, and continuously innovating.

As the AI landscape evolves, there will undoubtedly be challenges. Some wrapper businesses will become obsolete as core AI platforms expand their capabilities. However, those that focus on deep, industry-specific solutions and continually adapt to user needs will find opportunities to thrive.

The future of AI startups doesn’t lie in competing directly with giants like OpenAI or Google, but in finding unique ways to apply and enhance AI capabilities for specific use cases. By doing so, they can create lasting value that goes far beyond being “just a wrapper.”

What’s your take?