Sense Check of The Next Wave of Scale: Why SenseAI Backs AI-First Founders

It’s tempting to think of AI progress as a story of bigger models, larger clusters, and ever-increasing GPU counts. And yet, if you zoom out from the infrastructure arms race and look at where real business value is being created, a less-heralded revolution is underway - one we at SenseAI believe will define this next decade: the rise of AI-first Applications.

Real business value today isn’t being created at the base of the stack. The true revolution lies in the rise of AI-first applications - companies that embed AI as the core driver of new workflows, capabilities, and business models.

Where We Are in the Stack; and Why It Matters

In the early innings of any platform shift, it's tempting to focus on the bottom of the stack, but as infrastructure matures and becomes a utility, and foundational models commoditize, the centre of gravity is shifting. 

Historically, platform shifts focus first on infrastructure, then move toward applications as technology commoditizes. During the internet boom, companies like Amazon and Google succeeded by delivering differentiated services on mature infrastructure, not by owning the infrastructure itself.

This transition raises the bar for differentiation. AI-first startups integrate AI tightly into workflows, enabling new capabilities rather than only incremental efficiency gains.

From Cost-Cutting to Capability Creation

AI is often framed as a tool for optimisation - reducing headcount, automating repetitive tasks, and lowering costs. This framing is limited and misses the broader opportunity.

AI-first startups don’t merely improve existing processes; they enable entirely new possibilities: revenue models that didn’t exist before, operational insights previously unthinkable, and customer experiences that redefine markets. These companies aren’t just helping incumbents run faster - they’re building the next generation of market leaders.

Where It’s Already Happening

We see this shift firsthand in our portfolio.

Irame, an AI-native audit platform, transforms traditional audit cycles that rely on lagging indicators and large teams of consultants. It uses always-on, reasoning-first AI agents to detect anomalies, respond to queries in natural language, and generate real-time, regulator-grade compliance reports. This shifts auditing from a retrospective process to proactive control.

Confido extends beyond hospital administration to expand care delivery. Its AI nursing agent manages scheduling, documentation, and patient engagement, effectively doubling nursing capacity and significantly increasing revenue within one quarter. The technology enhances staff capabilities without replacing them, delivering clear operational leverage.

Pipeshift operates deeper in the stack as a platform for deploying and managing open-source large language models. It provides enterprises with tools for fine-tuning models, monitoring performance, and autoscaling workloads, serving as essential infrastructure for AI-native enterprise applications.

In consumer healthcare, CureSkin leverages AI-powered skin analysis trained on over 50 million images to diagnose and personalise treatment. This enables scalable, high-quality care access 24/7 - even in remote areas - building trust and driving revenue beyond traditional models.

What Makes These Startups Investable?

The defensibility of AI-first startups derives from the degree to which AI is embedded in product workflows that unlock new user behaviours and revenue streams. In today’s market, what makes an AI-first startup truly investable is not just technical flair or wrapper-level innovation, but embedded intelligence: the ability to integrate AI so deeply into a business workflow that it doesn’t just automate tasks, it unlocks new behaviours, revenue streams, and decisions. The moat isn’t in the model architecture. It’s in outcome architecture - how well the product reshapes what’s possible for the user, not just what gets done faster.

That’s why AI-first startups are scaling at a velocity unseen in previous tech cycles. Cursor may be the headline, jumping to $100 million ARR in just over a year, but we’re seeing multiple startups in our portfolio on track to hit $1 million ARR in under nine months. For traditional SaaS, it used to take more than two years.

What changed? Time-to-value. When an AI-native product delivers measurable impact from day one—whether that’s revenue growth, operational visibility, or real-time control—deployment becomes a business decision, not a technology experiment.

India’s Position in AI: Building a Global Toolkit

India’s AI ecosystem is advancing rapidly. In Q1 2025, Indian AI-first startups secured over $800 million in funding, with nearly 30% of early-stage VC capital targeting AI-first companies. Many launch with global ambitions and operate with high efficiency and speed compared to their Western counterparts.

Global technology leaders are investing in Indian AI infrastructure and partnerships - Microsoft is investing $3 billion in Indian AI infrastructure. NVIDIA, AMD, and OpenAI are doubling down on local partnerships. The government’s ₹10,000 Cr India AI Mission is laying the groundwork for data, talent, compute, and deployment.

India’s competitive advantage lies in execution, technical talent, and frugal innovation, positioning it as a key player in AI application development and tooling for the global market.

Opportunity: Backing the Builders of the Post-Model Era

The opportunity is in building scalable, AI-first businesses that create measurable impact from day one. At SenseAI, our focus is on founders who integrate AI deeply and deliver outcomes that transform industries.

Our role is to provide more than capital: we offer technical expertise and operational guidance tailored to accelerate time-to-value and help startups navigate the complexities of scaling AI products globally.

In this evolving landscape, success depends on selecting and supporting startups that move beyond demos to durable outcome-driven architectures. That is the core of our investment thesis, and why we believe the most significant growth in AI is still ahead.