Early-stage venture fund, pi Ventures has secured an undisclosed amount of investment from venture capital fund Accel Partners. The World Bank’s financial arm, International Finance Corporation (IFC) has also proposed to make an equity investment of $3 Mn in the fund. This investment would be made through the IFC Startup Catalyst (ISC) programme.
Commenting on the development, Manish Singhal, Founding Partner, pi Ventures said, “Accel has played a key role as they have been good mentors and go to guys for us. We are working on some investments along with them as well. So, it is good to get them on board as investors in the fund. Also, we are excited that IFC is considering us. The process is still on.”
Earlier this month, the Bengaluru-based fund had announced the first close of their maiden fund at $13 Mn which is expected to attain final close within this year. The fund’s backers include the SIDBI, family offices from the US, Canada, Singapore, and India and entrepreneurs like Mohandas Pai, Binny Bansal, Deep Kalra, Sanjeev Bikchandani, and Bhupen Shah, amongst others.
Co-founded by Manish Singhal and Umakant Soni in 2016, pi Ventures invests in early-stage startups that focus on solving problems in healthcare, logistics, retail, fintech, and enterprise sectors using artificial intelligence (AI), machine learning (ML) and Internet of Things (IoT).
An alumnus of IIT Kanpur, Manish has been an active angel investor in the Indian startup ecosystem from past few years. His love for building products led him to the space of investing in products that he believed in. Some of his personal investments include Locus, Witworks, Adpushup, ApartmentAdda, BetterButter among others.
“I invested in Locus, a machine learning logistics company and started to dive deeper into space and this led me to start pi Ventures – a fund focussed solely on AI, ML, and IoT startups. The tech community is buzzing with how artificial intelligence will change the world. Investors globally have pooled close to $10 Bn in AI startups over the last few years which is likely to continue. The artificial intelligence market is estimated to reach $5 Bn by 2020 globally, and with Indian companies being one of the fastest adopters of AI, there is huge growth potential,” says Manish.
AI: Game-Changer For Venture Funds
If we look at the current scenario, companies have moved from cloud presence to mobile presence to now AI-presence. AI is here to stay and ignoring it for companies is tricky, because it could suddenly change a sector.
According to Manish, this is a great time for AI to evolve and mature in India. All the sectors that apply technology to collect data will be impacted positively by the AI wave. The early ones would be where the data value is highest and this data is easily available to create AI-led products and services.
“Easy adoption of AI will lead to more VCs investing in AI-based startups and create a virtuous cycle. We definitely believe that India is the dark horse in AI and the use cases cracked here can be used to expand in the next 6 Bn markets (SE Asia, Middle East, and Africa) and not just in the US,” adds Manish.
For this growth to take place, a big challenge for AI startups is to acquire enough data so that their AI algorithms become practical.
“We are seeing startups try out various hacks to figure out this initial data need. It also inhibits the growth of AI talent, as for them to try out their experiments, they need data which is not easy to come by. One of the big reasons the AI community grew so well in the US is rooted in the Netflix challenge example. In the US, Netflix threw open their data sets for the AI community to come up with a solution, with the winner taking a big cheque home. We think India needs similar challenges, with bigger companies coming up with “Open Data Vaults” for these startups and the AI community to experiment with and grow,” said Manish.
Consistent regulations with a fair use of rules are also required to increase startup innovation in this space.
Apart from the typical things that any investor would look at, like, the team, market size, defensibility etc. Pi Venture looks at a few more aspects of a startup, for instance, how good their IP is, the real AI algorithm that they have built. Furthermore, they also look at things like data strategy a startup has; how will it acquire data, whom will this data belong to, how will this data grow, what is the cost of the data etc.
“We have internal parameters within which we analyse the data strategy, the specific business case of the startup, as we don’t want to fund any R&D company but only applied-AI companies. All the companies we have funded so far have a business case, which states the problem that they are solving using AI to their advantage,” said Manish.
Till date, pi Ventures has invested in three startups. Two of these are in the healthcare space. The first one, Sigtuple is in the medical diagnostic space and aims to create a data-driven, machine learning, cloud-based solution for detection of abnormalities and trends in medical data, for disease diagnosis. The second company is ten3T, which collects medical data in real-time through its own wearable devices and the third company is Zenatix (data-driven energy efficiency company), which uses advanced machine learning-based models.
The fund is now in the final stages of finalising its fourth investment. The fund, whose corpus is intended to be $30 Mn which they hope to close in the next 12 months, plans to invest in 18-20 companies in a period of three to four years. “We want to get in as early as possible, so, probably at Seed up to Series A level in order to continue to support our companies,” informed Manish.
The future looks bright for the AI sector. As a trend, more product companies will get funded out of India based on real IP tells Singhal. In 2016, a total of 22 AI startups were funded and the sector witnessed 340% growth both in number and funding as compared to 2015. A cautious yet healthy investment scenario was witnessed as funding was down by 30%-40%, as per a joint report by Nasscom & Zinnov.
“The only advice would to be focus on solving a real problem and look at AI as the means and not the end,” concluded Manish.