Singapore’s ICT Fund confirms plans to launch $100m second vehicle in 2019

Brijesh Pande

Singapore-based venture capital firm ICT Fund is launching its $100-million second vehicle in 2019, confirming an earlier story by DEALSTREETASIA.

ICT Fund II will issue average check sizes of $10 million and invest in 12-14 enterprise technology firms across Southeast Asia. 

According to Brijesh Pande, founder and managing partner of ICT Fund, the second fund will target 20-25 limited partners (LP), of which it expects 10-15 to be new backers. Pande added that it is seeking out more corporates and family offices this round. The fund’s average LP commitment size will be $4-5 million. 

The venture capital firm last closed its $35-million ICT Fund I in 2015. The fund made six investments in companies such as Deskera, Latize, Six Scape, Taiger and Vi Dimensions.

In an interview with DEALSTREETASIA, Pande shared that the fund is looking to merge a few of its companies to create a larger entity.

“We will be using Fund II to look into that strategy. Some people have done this really successfully in other parts of the world. We feel we have the eco-system to be able to operate and manage these companies and to create a larger player in the enterprise tech space,” he said. 

The fund also expects to see exits from its portfolio companies in the next two years.

“We are already talking to a few industry majors regarding our portfolio companies. We are likely to have one or two exits in 2019. Given our companies have patented core technologies, we will most likely exit via trade sales other than Deskera, which is likely an IPO candidate,” said Pande.

Edited excerpts with Brijesh Pande, Founder and Managing Partner of ICT Fund I & II:

You said you looked at about 200 companies. How do you find the quality of deal flow in this part of the world?

For a vibrant tech startup ecosystem to fall into place you need access to a large customer base, availability of capital (both financial and human capital), government support and investments in core R&D. 

Asia is at the epicentre of the global demand for technology – be it that close to 60% of the world’s consumers are in Asia or that companies in emerging Asia are underinvested by a factor of up to 6 times compared to their developed world counterparts. There is significant dry powder in Asia and in Singapore especially there is significant support from the government in supporting early stage technology companies. The area which needed most development was investments in core R&D but there are significant changes in that regard of late.

China is now filing more AI patents than the US (driven by significant investment dollars by the large Chinese tech companies). South/ SE Asia is still playing catch up in deep tech R&D but large global tech companies (like Apple and Oracle) dropping significant R&D centers into India are examples of progress in these regions as well.

Consequently, we have seen the quality of deal flow improving significantly in the last 3 to 5 years as the ingredients for a vibrant enterprise technology eco-system in Asia (especially Singapore) continue to fall into place.

We strongly believe that Singapore provides one of the best eco-systems for early stage enterprise technology companies in Asia, given ease of doing business, supportive government initiatives, availability of capital and ability to attract global human capital. As such, our operations are headquartered here and we continue to encourage our portfolio companies to domicile their headquarters here. 

But even if you look at some of your companies, they are still looking at expanding operations in the US.

That’s correct. In building a global software company you cannot ignore the opportunity in the developed markets, especially the US. The buying behaviour and the buying capability of developed markets like the US versus developing markets is very different. 

Firstly, the average Asian enterprise sales cycle is longer than the US, as you spend more time convincing people of the need to adopt a technology to begin with. Secondly, the average ticket size in developing Asia is smaller. You’ll find very few enterprises here that are spending tens of millions of dollars on software; you’ll find many of those in developed markets (especially the US). Thirdly, the collection cycles for Asia are at least two to three times longer than their Western counterparts. India is especially notorious for collections. As a result, enterprise tech companies that choose to focus only on Asia run the risk of running out of cash quickly because the cash conversion cycles can be long. Keeping these in mind, it makes strategic sense for large enterprise tech companies to explore expansion in both developed markets and developing markets.

We do understand that expanding into the markets like US can be very competitive and capital hungry, but if managed strategically it does result in an improvement in cash collection cycles as well as average ticket sizes (and significantly for investors, also in valuation multiples).

It seems Asian deep tech companies take a long time to raise capital. How do you see this pan out for your portfolio companies? 

The market potential of consumer technology is intuitively easier to comprehend because most investors will easily understand the size of a particular market and the basic good or service that the consumer tech platform will provide (or improve). It is more difficult for deep tech because you have to take a strong view on the underlying technology (and its global relevance). To take such a view you need to have expertise in deep tech as well as connectivity with the global deep tech ecosystem. 

When I established ICT Fund I, we were the only enterprise tech focused fund in the region – as there was a big opportunity to create a specialised investment platform supporting deep tech companies in the $1 to 10 million bucket (the sector was under invested with early stage typically being catered to by family offices and some generic VC funds). At least in Singapore, that gap has diminished because of specialised funds like us as well as the tremendous government support provided to early stage deep tech companies, be it in the form of financing schemes (like ESVF, which we are a part of) or the provision of technology test-beds etc.

As the deep tech eco-system develops the next big opportunity we see is specialised platforms that can lead Series B and C deals and are able to write checks in the range of $10 to 50 million. Our aim with ICT Fund II, is to expand into this area as a natural extension of supporting our companies through to later financing rounds. There are large global funds focusing on investment sizes of at least $50 million, who have deep tech expertise, but the $10 to 50 million bucket for enterprise technology companies is still not easy to come by. This definitely does result in some enterprise tech companies funding themselves through internally generated cashflow. Deskera for instance, did its first institutional financing almost 8 years after being established. 

What about the smaller rounds? SGInnovate recently told us that in deep tech, the VC allocations aren’t growing proportionately with the number of deep tech companies entering the ecosystem.

I believe SGInnovate is likely referring to the seed and pre-series A stages. This is largely a function of what I have mentioned before that it is not easy to understand deep tech risk (and assess the capability of these companies to be able to compete globally). The earlier the stage, the greater the degree of tech risk and not many platforms are specialised to dissect these risks. Whilst we are comfortable with the technology risk, platforms like ours have deliberately stayed away from very early stage, as given the size of our fund, we do not invest less than $1 million (which rules out seed stage opportunities).

As mentioned earlier, there is a lot of effort put in by the government (including by SGInnovate) to ensure significant public sector capital to support the very early stage enterprise tech companies, which again makes Singapore a logical choice for early stage deep tech entrepreneurs. I don’t see many funds focusing on seed stage enterprise tech and as such, organisations like SGInnovate will continue to play a pivotal role in supporting the $50,000 to $500,000 deep tech investment bucket, at least in the near future.

There is some progress in this area though as some large tech companies have set up platforms in Asia including the likes of Cisco and Oracle (who also look at seed stage investments). Even ST Engineering has launched an accelerator to support very early stage investments.

When it comes to LPs, not everyone will understand your space since you’re a niche fund. How will this work out when it comes to fundraising?

Some of the best performing early stage VCs tend to have a very narrow focus. This is because early stage investments require a lot of technology and operational expertise in addition to financial support. Our LPs are actually appreciative of our focused approach because they know we are investing in a sector in which we have both financial and operating expertise. So we haven’t really found it challenging to convince LPs on the need to be so focused.

Whilst we don’t publicly disclose our performance numbers we are definitely one of the best performing VC funds in the region. We will be capping our second fund at $100 million as given our focused strategy, we are not yet confident of the market maturity to be able to successfully deploy a lot more than this number. We haven’t started marketing Fund II yet, but the early indications lead us to believe that we will be oversubscribed as almost all our LPs will re-up in Fund II and a number of new LPs have expressed strong interest to partner with us.

On Fund I, the area we had to spend the most time was in convincing our LPs is that there is an enterprise tech opportunity in Asia (specifically in Singapore). Given our Fund I performance and ongoing pipeline, we see this as less of a challenge when marketing Fund II.

What about AI? There’s a significant level of capital that has gone into AI companies in China. Many of the large companies in Hong Kong and China are also entering Singapore. Do AI companies here stand a chance to compete?

A few weeks ago we had representatives from the government asking us the same thing. Can Singapore be relevant in the AI space? In short, we do think there is an opportunity to relevant in certain verticals but we need to continue making investments in R&D as well as attracting more AI companies.

We definitely think that AI is the next frontier and the global powers of tomorrow will be the ones who have taken leadership in AI. There is an enormous amount of capital being invested by the US and China in this segment. In fact, China is now filing more AI patents than even the US. However, there is an element of distrust around “big brother” watching both American and Chinese start ups. For US and Chinese tech companies it can become very difficult to sell into or operate in countries which are not naturally affiliated with them (the recent news on Huawei is one such example).

In the backdrop of this distrust, I do believe that there is opportunity for a country like Singapore to take leadership in certain niches of AI, as we are not seen as a someone who has a geo-political agenda in exporting our technologies. We also have the right ingredients to attract global human capital specialising in AI and Singapore provides a ready test bed for many AI technologies. If we are able to incubate AI companies specially offering solutions in areas like robotic process automation, security/ surveillance, authentication/ encryption and data analytics – we do have an opportunity to compete in the AI arena.

I do note however, that there are very few true AI start ups in our part of the world. It is rare to meet a startup these days who does not mention AI in their pitches. However, most companies we meet in Asia still equate machine learning with AI. There are other disciplines to AI like NLP, knowledge representation, robotics, speech recognition, voice recognition and to build truly world class AI solutions, one needs to have expertise in the broader field of AI (and not just machine learning). Specifically in Singapore, one of our promising companies, Taiger, is still the only prominent AI company that leverages NLP and knowledge representation as opposed to machine learning.

Where do you see some of your highly specialised portfolio companies progress in terms of exits?

We are already talking to a few industry majors regarding our portfolio companies. We are likely to have one or two exits in 2019. Given our companies have patented core technologies, we will most likely exit via trade sales other than Deskera, which is likely an IPO candidate.

Where do you think a company like Deskera will list? 

It is difficult to make a case to list a tech company in Singapore because tech company valuation multiples and market liquidity would still be a concern relative to other listing venues. Nasdaq would be an ideal venue – especially as Deskera’s US story starts to build out. To be listed in Nasdaq, you probably want a market cap in excess of $1 billion. Deskera is already a $100-million revenue company. The other traded companies in Deskera’s space are trading at multiples of 10 to 12x EV/Sales – so we are approaching those levels already. We are fairly confident that in the next year or two, Deskera is a potential listing story.

Anything else you’re picking up from the market?

The three most commonly talked about things these days seem to be fintech, blockchain and AI. Most fintech or blockchain startups we meet in our part of the world are still focusing on process innovation – as opposed to technology innovation – and hence don’t fit into our investment mandate. There is a fair amount of money going into these areas and I expect a rationalisation after a year or two when the market realises that scaling process innovation businesses is closer to the risk profile of consumer internet startups (which require a lot of capital to scale). In AI, as mentioned, we see few true AI companies and hope to find more exciting companies like Taiger setting up operations in Singapore.