Scaling without outside funding: Intuitive's unique approach to technology consulting

In an industry that is somewhat an epitome of hypergrowth hype and VC fueled burn rates, it is inspiring to read about Intuitive’s approach to doing things differently—and sustainably—under the CEO leadership of Jay Modh.

With a revenue of $100 million, Intuitive has achieved legitimacy on a global scale without a dime of outside funding, instead relying on its deep engineering and automation, and an acute focus on wisely understanding business outcomes.

In this conversation, Modh takes us through individual challenges of cloud modernisation and the data readiness for AI powered by co-creation with their clients. And how governance should not be seen as a brake, instead a competitive advantage. 

From building digital secured highways, to scaling Agentic AI, Modh talks about how Intuitive is positioning some of the most complex companies in the world to innovate with confidence.

You're managing Intuitive across several geographies. Can you provide us an overview of your company's global footprint?

Intuitive is a highly distributed organization. While core executive leadership is primarily in Dallas, we have operations in several key regions both in the United States and internationally. In the U.S., we obviously have large bases in Dallas, New York, New Jersey, Boston, and the Bay Area.

Internationally, we have teams in Paris, the UK, and India, and technology leadership in India. We also have team members in Canada and France. As a whole, about 40% of our workforce is in North America, 5% in Europe and the UK, and the remaining 55% in India. This footprint gives us an incredible level of nimbleness and access to different talent pools.

You have reached a $100 million valuation with absolutely no external capital funded into the company. Why and how did you get there?

From the outset, we made a commitment to not raise debt or seek external capital unless we absolutely had to. This allowed us to maintain complete control of our direction as a company and to make bold bets to react quickly to customer demands. We built the company on sound business fundamentals, not just big top-line revenue.

Financial independence took us out of the short-term grind of worrying about investors, and allowed us to build value that mattered to us. We've been disciplined about that, and I think that is why we've been able to keep growing sustainably.

If you could summarize what sets Intuitive apart in one sentence, what would you say?

We are a tech company that focuses on innovation and automation engineering, providing measurable business outcomes. We simplify complexity, emphasize value and make sure our clients receive a lasting competitive advantage. It is not about transformation. It is about measurable impact. As someone once said, "If you cannot measure it, you cannot improve it." That is exactly what we help our clients do.

What are the most common challenges your clients are currently bringing to you—and how is Intuitive addressing them?

Broadly speaking, the top three categories we deal with are infrastructure modernization, AI readiness, and security and governance. First, companies are moving from tech-enabled to tech-led, and our customers and the market need secure, scalable hybrid-cloud environments on which to build; we help them create what we call the Digital Highway.

Second, while customers have an appetite for AI, many of us are starting from a point of data-readiness. AI is only as powerful as the data you are feeding it. We fix data readiness, from ingestion and tagging to governance and security.

Third, in a rapidly evolving AI landscape, the issues of governance and trust become essential components of AI orientation and adoption. We work with the enterprise to take the uncertainty out of AI adoption, provide compliance and support corporate responsibility. When done correctly, these are not barriers; they are enablers.

To put it simply—we treat data like the fuel you burn, the AI like the engine, and governance like the brake or governor in determining how fast and safe you can go. We help enterprises drive fast—and safely.

You mentioned innovation and automation are primary means of solving problems. Can you talk a little more about that methodology?

We think for any complex problem, a good 60–70% of it can be solved through innovation. That's always our first principle. Then where we see any inefficiencies; be it in workflows or process, automation works for the other 20% of the friction. The remaining 10–20% is where the engineering plays its important role, and it allows to touch on the scale, security and governance aspects.

In data specifically, we are referencing the last 5–6 years of massive investments. We partner with platforms like Databricks and DataMiner and we've invested in companies like TESL and Strike AI for securing their AI models.

We've also invested in building our own accelerators and IP that integrate with enterprise systems, and we have over 10 PhDs on our team - which is rare at our scale! In addition to that are a big part of the solve for enterprise-grade issues.

How do you view Intuitive, as a service company or a solutions/platform company?

We are somewhere in between. We are fundamentally a high-end consulting and engineering services company. But we lead with solutions and accelerators. Unlike every other player in the traditional service space, who will apply thousands of engineers to your 5-year contract, we have a deep understanding of the business for our clients. We co-create the solution with them, we deploy accelerators to fast track outcomes, and we measure the value delivered. That approach is fundamentally different from traditional systems integrators like TCS or Wipro.

How crucial is your India team in being a global innovator and delivery engine?

India is absolutely fundamental—not just from a delivery perspective, but really in being a driver of innovation. We have never seen India as a cost point. The engineers that we employ are coming in today ready to experiment, to build and to complex solve. The market ecosystem in India has evolved from a “cost point” to one that is values experimentation, agility and quickness of execution. We are, at Intuitive, creating a culture of experimentation and execution by leveraging a combination of experienced and agile young minds. This is helping us move away from the traditional GSI model of delivering services and solutions to a solution first, innovation led mode of delivery.

What are the verticals Intuitive globally and in India are focused on?

We operate in three sectors: BFSI; health and life science; and energy, manufacturing and consumer goods. We’re approximately working with 130 Fortune 1000 companies and global health systems, and a number of large NGOs.

Many of our U.S. and European clients have created their GCC's in India, but increasingly we see decision power shifting to the Indian leadership of these companies, which presents new opportunities. Ironically, these enterprises are now contacting us for local collaboration, and their executive we have engaged with around the world are the same executives seeking local collaboration. Therefore, our continued growth rates in India have been very reputation and delivery led.

Can you mention few of the organizations that you work with?

In the U.S. we work with 3 of the top 10 banks, 13 of the biggest healthcare providers, 5 CPG firms, and 3 of the top 10 pharma companies. Most of this clients have GCCs based out of India and we work with their leadership who sit in India to scale the outcomes. Together, this relationship has fueled tremendous growth for us in the region.

From a cloud onboarding and scale perspective, what does the typical client journey look like? 

Our approach is consultative and outcome-led. It begins with understanding the client’s business goals, pain points, and key success indicators. We engage with the entire CXO suite of the client – their CIOs, CTOs, CFOs, CISOs, procurement leads, etc. 

Additionally, we provide a reference architecture and an accelerators in pre-built form that are relevant to the client's environment. 

We do not stop at frameworks. We co-create bespoke solutions together. Their journey is typically from proof of concept (POC), to proof of value (POV), to proof of scale (POS), with governance and security also being considered from day 1.

Where does the bulk of your innovation take place (internally, client environments)?

Jay Modh: Over 90% of our innovation is co-created with our clients. Many of our clients are in highly regulated spaces like healthcare, pharma, and banking, so typically, we will innovate together solely in their secure environments. We obviously have our internal lab spaces—both on-prem and cloud-native—but the majority of our discovery and meaningful innovation happens in close collaboration with clients. 

What trends do you see in AI and cloud in the next 1–3 years?

In the cloud space, we see a shift from migration to modernisation (and platform engineering). Enterprises are focussing on modernisation of both applications and databases because those are critical levers of agility, security, and business value.

In AI it is about data readiness; the majority of enterprise data is very fragmented or very poor quality which makes any AI effort difficult. Next is understanding existing processes—the way work is done at scale—which is critical for enabling GenAI.

But the true ROI is Agentic AI—autonomous systems which don’t just tell you what to do, but just do it. We’ve been investing heavily in this space since 2018. GenAI can help plan your vacation, Agentic AI can help book your tickets and hotels. That is the future of enterprise automation.

Have you partnered with others to build these Agentic AI capabilities?

Indeed, we partner with all major hyperscalers - AWS, Microsoft Azure, Google Cloud, etc. We’ve invested strategically into DevRev, which is developing Agent OS - a platform that powers Agentic AI ecosystems. We internally use and deploy DevRev on behalf of clients. When combining DevRev with our analogous multi-cloud engineering capabilities, we can create remarkably coherent, intelligent, and contextual solutions.

To conclude, with regards to the outcomes delivered with AI, do you focus on enabling platforms - like MLOps, or on discrete use cases for business?

We do both. As referencing earlier, our AI journey with clients is end-to-end - from data strategy & ML engineering to MLOps, model training, governance, GenAI, and Agentic AI. We have an exceptional differentiator in our talent pool (PhDs, CIOs from major enterprises, and exceptional advisory board), and, combined with our automation IP, and strategic partnerships we can deliver measurable transformational outcomes - not just tech deployments.

Is there anything else you would like to add?

I would just add that the pace of change we are bearing witness to, is being driven by innovation, automation, and engineering; is faster than anything we have seen yet in moving the world forward. We aren’t talking about traditional IT services anymore, but rather, capitalizing on innovation, at scale, to drive real problem solving and improve lives in the process. That’s what we’re here for at Intuitive.