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How tomorrow’s billion-dollar startups need to be approaching emerging technologies

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By Gayatri Sachdeva

India’s startup ecosystem is on the brink of a transformative decade, often hailed as “India’s techade.” The country’s digital economy, powered by a burgeoning number of startups and tech innovators, is set to play a pivotal role in boosting India’s share in the global digital economy. By 2047, India aims to emerge as a developed nation, with its tech-driven enterprises leading the charge. This vibrant ecosystem is evidenced by the remarkable rise of unicorns and their close successors.

India boasts over 50 soonicorns (startups poised to achieve unicorn status soon). These companies are navigating a landscape fraught with opportunities and challenges, from scalability to maintaining innovation, all while aiming to contribute significantly to New India’s growth.

Statistics to note:

● According to the Indian Tech Startup Landscape Report 2023 by Nasscom and Zinnov, over 950 new technology startups were founded and over 750 were funded in the past year.

● The country has over 31,000 tech startups, with their cumulative funding exceeding $70

billion over the last five years.

● Approximately 70% of Indian startups are investing in emerging technologies like AI, ML, and NCLC to enhance product capabilities and internal efficiencies.

Navigating the complexities of scaling with emerging taechnologies like AI, ML, Low-code

As startups transition from early-stage ventures to high-growth companies on the cusp of becoming unicorns, navigating the complexities of scaling becomes a critical challenge.

Early-stage startups can often rely on simple tools and makeshift solutions to manage their operations, but as they grow, these approaches become increasingly inadequate. In this context, emerging technologies like machine learning (ML), artificial intelligence (AI), and low-code platforms emerge as game-changers, offering robust solutions.

These technologies are not just buzzwords but critical tools that enable startups to innovate rapidly, scale efficiently, and maintain a competitive edge. The integration of AI and ML allows these companies to harness vast amounts of data for smarter decision-making and personalized customer experiences.

Meanwhile, low-code platforms empower them to develop applications swiftly & maximise productivity.

Indian scaleups Navigating operational challenges

“Building a tech stack for today’s scale and scope, which absorbs headcount and slows you down when you face tomorrow’s scale and scope.” – Failing to be future-proof and not investing upfront where it matters, Scaling through Chaos.

Temptation of quick fixes (and falling for good marketing)

In the initial stages of growth, many startups gravitate towards readily available tools like Google Sheets, Notion, and various ticketing and payment systems. These tools are highly effective for small teams focused on rapid expansion and revenue generation. However, as the startup scales, these solutions can become productivity traps. What initially served as quick fixes turned into bottlenecks lacking role-based access or difficulty adapting to new business processes or workflow, lack of customisations and more thus hindering further growth and efficiency.

Just as in the popular ‘Lifecycle of startups – Scaling through chaos’, there is a critical shift that must occur during a startup’s growth phase: Transitioning from early generalists who cover a wide range of activities to specialists dedicated to specific subdisciplines, customer segments, or product areas.

This shift is essential for maintaining operational efficiency and sustaining growth. Without adopting more specialized tools and processes, startups risk falling into the trap of relying on generalist solutions that no longer meet their evolving needs.

For instance, managing IT support tickets via a shared WhatsApp group and Google Sheets might work for a small team but quickly becomes unmanageable as the company expands. Incomplete data, disorganized workflows, and inefficient processes can stifle growth.

Complexity and inefficiency

Scaling introduces complexity and inefficiency. Teams expand, new locations and partners are added, and the need for more sophisticated processes becomes evident. The initial simplicity of operations gives way to a complex web of responsibilities, tools, and data. This shift can lead to significant challenges, including:

Scalability: Ensuring that technology infrastructure can handle increased demand without compromising performance.

Technical debt: Addressing shortcuts taken during rapid growth while continuing to

innovate.

Maintaining innovation: Sustaining a culture of innovation amid rapid scaling.

Data security and privacy: Protecting large volumes of user data and complying with

regulations.

Talent acquisition and retention: Competing for top tech talent in a competitive market.

Infrastructure management: Optimizing complex technology infrastructure for cost, performance, and reliability.

Regulatory compliance: Navigating the complexities of compliance as the company expands.

Adapting to new technologies: Staying ahead by adopting emerging technologies.

The tech companies’ new favourites

Machine Learning and AI

Machine learning and AI are at the forefront of technological innovation for high-growth startups.

According to a report by Nasscom and Zinnov, 70% of Indian startups are investing in AI to enhance product capabilities and internal efficiencies. AI technologies enable companies to analyze vast amounts of data, automate decision-making processes, and deliver personalized customer experiences. By integrating AI-driven insights, startups can enhance their product offerings, optimize operations, and identify new market opportunities. For example, predictive analytics powered by ML can help in anticipating customer needs, thereby improving customer satisfaction and retention.

Low-Code Development

Low-code development platforms offer a strategic solution to scaling challenges by providing a visual development environment with a layer of abstraction for building business operational tools and digital workflows at speed. Here’s how low-code can transform the growth journey of soonicorns:

1. Accelerated development and faster time-to-market: Low-code platforms significantly reduce the time required to develop and deploy applications. Companies can quickly address internal inefficiencies and respond to market demands.

2. Enhanced scalability and reduced technical debt: The ability to quickly iterate and deploy solutions ensures that the technology stack can scale in line with business growth without accumulating the compromises that often plague traditional development approaches.

3. Impact engineering over trivial engineering: Low-code empowers engineering teams to focus on high-impact projects rather than getting bogged down with trivial tasks. By streamlining the development process, engineers can dedicate more time to innovation and strategic initiatives that drive the company forward.

4. Investing in scalability tools: Implementing low-code solutions provides startups with the tools they need to scale efficiently. These platforms offer built-in scalability features that help manage growing data volumes, user loads, and complex processes.

How unicorns are reaching new digital transformation heights

Case Studies

1. FinBox, a Bengaluru-based fintech startup, uses AI to provide credit scoring and underwriting solutions to financial institutions. By analyzing alternative data sources, FinBox enables lenders to assess creditworthiness more accurately, facilitating access to credit for underserved populations.

2. Niramai, a health tech startup, employs AI and machine learning to detect early-stage breast cancer through thermal imaging. This non-invasive, radiation-free method is cost-effective and scalable, making it accessible to a broader population and significantly improving early diagnosis rates.

3. Unicorn Purplle (an online cosmetics retailer) is aggressively making the switch from a traditional stack to a secure and customizable low-code stack to streamline its administrative processes, from sales campaigns to merchandise management, significantly improving efficiency and scalability. While enhancing how internal users perform their day-to-day, these tools directly impact the brand’s website visitor engagements.

4. CleverTap, a company specializing in customer lifecycle management and mobile marketing services, has utilized DronaHQ developer tool to build internal tools and enhance the efficiency of its internal teams. CleverTap has empowered its engineering, customer success, and support teams to efficiently manage API access, downtime, and maintenance tasks by providing quick tools and streamlined communication workflows.

5. A Mumbai-based stationery manufacturer leveraged low-code developer technology to develop a bespoke CRM system, transforming their lead nurture process. The intuitive user interface significantly boosted adoption rates among sales teams, ensuring they could manage leads effortlessly. The low-code platform also facilitated the easy implementation of generative AI features, enabling the creation of personalised emails tailored to each customer’s needs.

Conclusion

As India’s digital economy continues to grow, driven by startups and tech innovators, adopting emerging technologies like machine learning, AI, and low-code solutions will be crucial for soonicorns aspiring to become unicorns. By embracing these technologies, soonicorns can unlock their full growth potential, streamline operations, and maintain a competitive advantage in a fast-evolving market.

The future lies in innovating with agility and efficiency today, ensuring sustained growth and success in the dynamic landscape of tomorrow. As Gartner anticipates, the adoption of Low-code development platforms will continue to grow at 20% per year, reaching $44.5 billion by 2026. This growth underscores the strategic importance of these technologies in navigating the complexities of scaling and achieving long-term success.

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