Francisco D’Souza’s next big bet: Backing the future giants of tech with Recognize

Could you talk to us about your transition from the IT industry to private equity? What made you take this leap of faith?

I left Cognizant after 26 years because I wanted to write another chapter, and I spent a little time thinking about what the next chapter would be after I left. I realised that I loved the technology services industry… I’d grown up there, spent almost all my career there, and so I wanted to stay involved in some way… Because I’d operated a business for a long time, it became almost a natural idea to say, ‘maybe I can… invest in the industry’. And so, at Recognize, we’re private equity investors, but we only focus on investing in digital services businesses. It gives me an opportunity to learn a new craft, if you will, in investing, but at the same time stay involved in an industry that I know and I love, and hopefully I can bring some value to the companies in which we invest. So, it’s a nice balance.

While the IT industry is not new to PE investments, for someone like you who has run a big IT firm, how do the learnings play a role in your investment and approach to value creation?

I think there are multiple ways to create value when you invest. At Recognize, we are entirely focussed on one sector. Since we know the companies in the sector… the founders… I think that gives us a bit of an edge because of our familiarity with the industry. We tell the founders and entrepreneurs we work with that we bring two things... capital and capability, because you need both… for the investment to be successful. We’ve been around for a long time, so we understand how it works. We have networks of talent that we can bring to the portfolio companies if needed. We have networks of clients, partners, and we bring all of those to our portfolio companies. And because we just focus on one industry, that focus allows us to be deeper in those areas.

How do you scout for companies when you are looking to invest? Have any of your bets gone wrong?

We have a very disciplined process of sourcing to finally making an investment decision... One of the interesting things about Recognize is that you have this very nice kind of confluence of operators and investors working side by side every day, on every deal. And so, the sourcing process starts with casting a very wide net. We try to network broadly in the industry because we’re only focussed on this industry, that is a limited universe of companies. And then we’re also well connected with the bankers and others in the industry.

We have a good top of the funnel, but before that we think of ourselves as thematic investors investing in tech services... a $1 trillion industry… We’re trying to find the fast growth pockets that we think are going to have sustained momentum… And so we identify themes. For example, we identified cybersecurity as a theme… cloud as a theme. Once we identify the themes, then we have a very focussed sourcing against each of them. From there, we have a very disciplined process of doing diligence on the company.

We have a formal investment committee… [it] meets once a week, and for any deal that we do, we probably review it with our investment committee two or three times, sometimes maybe even four times, before we finally make the decision to invest. Along the way, as we’re doing diligence, as we’re getting to know the company, the management team, we are also formulating our view on how we can be most helpful… what are the things that we can do. And we codify that into a plan… by the time we get to the end of diligence, we already have a preliminary version of what… we can do that will be helpful to the company, and we’re reviewing those… with the management team. So that as we are coming up with these ideas, the management team is also sort of buying into them, and then we make the decision to invest.

We’ve made 13 investments so far. We have exited one and we are in the process of exiting our second… Once that transaction is complete, there’ll be 11 active companies in the portfolio. And we’re pleased with our investments, and we just continue to work to make them all great investments.

Has the entire amount from your first fund been deployed? Are you looking to raise more money?

We’re still deploying from the first one. We don’t comment publicly on fundraising. At this point we are investing actively. And we don’t think that capital is a constraint for us.

Coming to AI, is there a need for India to build its own large language models (LLMs)? If you were still at the helm of an IT company, how would you have ridden this wave?⁽²⁾

It’s a complicated topic. What should IT services companies do? And what should India do? These are separate questions. For IT services companies, there are three things they should be doing. The first is that AI, in general, is a revenue opportunity, and so they need to build capabilities to take advantage of that… The second thing is that AI will change how IT services companies deliver their services… And the third, which is maybe a little less obvious, is that in getting AI to do the work, IT services companies will need to invest in R&D themselves to produce these agents that are going to do the work.

Then the question is, what should India do, which is a broader question. In my view, if you simplify LLMs in AI, there are three layers of the stack. You have infrastructure, which is largely computing. We talk about GPUs as the big constraint there, and you have power... those have the biggest constraints right now. At the next level, you have the algorithm itself. Today… algorithms are mostly being made open source, so the algorithms are largely available. And then the third layer is the data itself, that the algorithms learn and train on. My view is that the algorithms themselves are largely available… The GPU and power constraints will alleviate over time in two ways: One, they may become more available as Nvidia produces more [GPUs] and other competitors enter the space, and as more power comes online. But, also… algorithms will become more efficient… And as algorithms become more efficient, it will reduce the need for GPU use and power.

Then the question comes to data. My view is that those who control the data will win the AI [battle] overnight… Also, data becomes the real advantage. I think in the context of India, we should be focussed on building its models over time, but not general models like OpenAI is publishing, but unique models based on Indian data. And the last thing I’m quite optimistic about, because I think India is one of the most densely digitised countries for its scale.

If we are to take GenAI as an inflection point creating a level playing field, home-grown IT services firms still seem to be shying away from investing substantially in R&D or acquisitions compared to some of their global peers. What is holding them back?

In IT services, M&A is not generally an end in itself. It’s a means to an end. So, you can achieve those in different ways. When a company needs to add a particular capability, or needs to enter a new geography or enter a new industry, it’ll do an acquisition… Now, M&A is one way to get there, but there are some firms that are very good at doing that organically... The first point I would make is that there are multiple moves to the end, and M&A is not always the answer… I think across the industry, it’s probably fair to say that the volume of M&A has gone up… If you go back, say, 10 or 15 years… most enterprises in the world ran their businesses on a small number of tech platforms… the Oracle ecosystem, the SAP ecosystem, the Microsoft ecosystem, or Cisco. So, there were a small number of very large tech players, and those players sort of dominated the enterprise ecosystem. Then the cost of innovation dropped dramatically because of the cloud… [and] we saw an explosion of SaaS companies, each focussed on some small niche of the market. Over the last 10 years, the client technology stack has gone from two or three big providers to hundreds of smaller players surrounding these big players.

What does that mean for services? The big services companies historically had to have big practices in those big areas. Now they have to build practices in many of these smaller areas as well… because building practices across hundreds of these smaller technologies is difficult, so M&As become a way to fill those gaps… And my prediction is that, that will continue to be driven mostly because of this — the fragmentation of technology.