Ikigai Labs’ Generative AI Platform Now Available in AWS Marketplace
Read announcement

Data, Operations, AI, and People [DOAP] Podcast: Ashu Garg

CEO and co-founder Vinayak Ramesh chats with Ashu Garg — GP at Foundation Capital as well as an Ikigai Labs investor and board member.

Sep 19, 2022
15 minutes to read

Episode 1 Synopsis. In the inaugural episode of Data, Operations, AI, and People [DOAP], Vinayak Ramesh, Ikigai Labs’ CEO and co-founder, chats with Ashu Garg — the GP at Foundation Capital as well as an Ikigai Labs investor and board member. Together, they discuss a brief history of AI applications, the current landscape of enterprise AI, and exactly how you can utilize Ikigai as a tool today to empower your existing employees to transform your business. Curious about data operators? Read more here.

Episode cover art: photo and names of speakers

Episode Transcription

Vinayak Ramesh (00:00): Hi, everyone. Thanks for listening. My name is Vinayak Ramesh. I’m the CEO and one of the co-founders here at Ikigai Labs. Super excited to have our first inaugural episode of our podcast here with Ashu Garg. Ashu is a GP at Foundation Capital. He just led Ikigai’s latest round of funding and is one of our board members. So I’m here to his perspective on enterprise AI, where it’s heading, and why he thinks Ikigai is so interesting. Thanks, Ashu, for joining us. Would love if you could give us a quick intro about yourself.

Ashu Garg (00:32): First of all, thank you for having me on the podcast. And thank you for having me as an investor at Ikigai. I’m one of the general partners at Foundation Capital. It’s my 14th year at the firm, I lead our enterprise investing efforts, and I’d spent 15 years in a variety of operating roles, most recently at Microsoft before this.

Vinayak Ramesh (00:50): Thanks, Ashu. It’s been awesome to be working with you so far. And one of the things I wanted to really jump into is there’s a zoo of tools and approaches when it comes to this buzzword of enterprise AI. And really wanted to understand a little bit more, one, about your investment thesis when it comes to this area. And two, what made Ikigai so interesting for you?

Ashu Garg (01:13): Let’s start with my thesis around enterprise AI. At some level, AI is a buzzword for a broad set of technologies. The opportunity really is to both automate business processes that are currently being done by humans and to create new experiences and processes that humans cannot do or accomplish on their own, so both are great opportunities for AI. And I look at companies that are providing applications for that. And so I have companies like Eightfold that automate recruiting and talent management. Now, if you’re going to have AI applications being built, you need to have tooling to enable those applications. There’s companies like Arise, Anomalo, and others that are in the tooling layer to enable engineers and data scientists to build applications. And then you need infrastructure to enable people to build these models at scale, to be able to build models a 100 X faster than they can do today. And we’ve invested in companies like Cerebras and Anyscale at the infrastructure level. So as a firm and personally, I invest across the stack.

Vinayak Ramesh (02:20): Like you mentioned, there’s so many different parts of the stack when it comes to AI. There’s tools for technical users, there’s tools enabling certain departments to work more efficiently and achieve more. In your perspective, how does Ikigai fit into all of this?

Ashu Garg (02:36): If you look at the first wave of AI applications, they were about solving specific problems. Eightfold did that for recruiting. You can find companies that are doing AI automation in CRM and so many other business processes. And that’s a great category and I think a lot of very large companies are going to get created. The reality is large enterprises have hundreds of business processes, maybe thousands. The vast majority of which will not have a dedicated AI for block. There’s not going to be a unique company for each of those. And what I saw in Ikigai was a company that was a horizontal platform that enables business users, not technical users, business users, people who are data aware, who know how to handle data, what we call data operators, but aren’t necessarily engineers or technically sophisticated. Ikigai enables such people to create their own AI application, and that’s what makes it so powerful.

Vinayak Ramesh (03:36): A big part of our thesis at Ikigai is to really enable these, what we call data operators, because they know their business process the best. So our philosophy is really to give them really, really powerful tools to automate what needs to be automated. Now, when it comes to AI in different use cases, sometimes people are scared. Is it going to completely replace people? And there might be use cases where it has. One of the things that we believe is, AI’s not about replacing people. It’s about augmenting people to really do their best and giving them the insights to work better and removing manual tasks. And I’m curious for you between investments that you’ve seen, what you’re hearing about from different executives, are you seeing things trend one way or the other, or are there certain areas that you’ve been seeing AI be more successful in?

Ashu Garg (04:27): I think as you rightly pointed out, the answer is both. A lot of the first generation of AI apps really automated repetitive and somewhat easy to automate tasks where human intervention or manual judgment wasn’t required. And I think that’s absolutely a very large opportunity, but it’s the tip of the iceberg. The vast majority, arguably 90% of business processes do and will continue to acquire humans in the loop because they require some human oversight or human judgment. And that’s what makes Ikigai so unique. It has the power of an AI platform with the ability to have human oversight and humans in the loop as the process is being executed.

Vinayak Ramesh (05:10): Let’s say, there are different executives, managers, individuals, and a lot of people are curious about AI, how would you describe the business benefit that they can gain from looking into these sorts of technologies?

Ashu Garg (05:23): AI has become such a big buzzword that literally every executive wants to have an AI thing in their toolkit, or they want to have demonstrated that they’ve used AI to solve a problem. The challenge is, pulling together an AI application is incredibly hard. Most corporations forward or attract the engineering and technical talent required to build an AI application. And that’s where Ikigai fits in. It brings the power of a Databricks-like platform, which is what startups use to build AI applications, but presents it to a business user in the form of a spreadsheet-like interface. So it has the ease of a spreadsheet and all the power of an army of data scientists and engineers.

Vinayak Ramesh (06:10): I think that there are a lot of different use cases for AI. What we are seeing at Ikigai is, we’re taking things like financial reconciliations or month-end closes that take weeks and multiple accountants and reducing it to minutes. We’re helping companies better forecast their supply chain demand in the midst of this global supply chain crisis. There are a lot of tangible benefits to AI, so why do so many people struggle to realize those?

Ashu Garg (06:36): As you rightly pointed out, the power of AI to automate routine and mundane tasks and free human beings to supervise and do the more creative task is a mess. The challenge is, you have to build models. You then have to put these models in production. You have to monitor them. You have to deal with a ton of infrastructure. And for most companies, the cost of all of this can very quickly add up to a few million dollars a year just to get started. And that’s not a realistic solution for most companies. And that’s what really attracted me to Ikigai. You can get the power of a multi-million dollar a year data science and machine learning team, all packaged in the form of a product that your existing employees can use. Employees that are smart, they know your business, but they’re not data scientists. The benefit of bringing that power to your existing employees is what makes the Ikigai special.

Vinayak Ramesh (07:34): Thanks, Ashu. And so now that we’ve talked a little bit about the benefit that Ikigai should provide, and maybe why different folks should utilize technology like this, what advice would you give them for both getting started with AI and advice for getting started with Ikigai to really transform their business?

Ashu Garg (07:52): I think it’s a great question. The research shows that most, maybe as much as 80%, of AI projects fail. And so the trick I think is to get started small and solve a specific problem and go from there. And Ikigai has, as you know, templates in packaged solutions for four or five really strong use cases that help you get started. One of them is finance. In finance, you have to forecast cash flows, you have to close the books every month, you have all kinds of other reconciliation-related processes. And I think that’s a great starting point for Ikigai, can take the work of multiple accountants for multiple weeks and compress it into minutes. In other areas around the supply chain, whether it’s forecasting demand or doing scenario analysis are looking at bottlenecks across the supply chain, the area of supply chain and demand forecasting is another really big bucket of opportunity for Ikigai. And it’s particularly relevant in current times, given all the things going on in the supply chain more broadly.

Vinayak Ramesh (08:54): Thanks, Ashu. Thanks so much for taking the time to chat about Ikigai. We hope our audience got a sense of what AI can do for them and really how to get started. We love helping anyone who’s curious to really first understand how to transform their business with Ikigai and AI, and to actually help them get started and be successful. Not one of those 80% of AI projects that fail. Thanks so much for joining us on this episode of our podcast.

Ashu Garg (09:21): Thank you for having me.

About the Speakers

Guest: Ashu Garg (General Partner, Foundation Capital)

The Rubik’s Cube has 43 quintillion combinations — but only one solution. At age 11, Ashu found that solution in 25 seconds flat. Although Ashu hasn’t picked up a Rubik’s Cube in quite a while, he still takes great pleasure in solving complex business challenges.

To give just one example, in 2010, an early stage Berkeley-based company that specialized in analytics wanted to get into the media-buying platform business. Ashu helped their small team reach the growing number of brands that were migrating their television advertising to the web. That company, TubeMogul, soon became the leading video-advertising platform for brand advertisers, went public in 2014, and was acquired by Adobe in 2016.

What he invests in: Ashu works with startups across the enterprise stack. He is particularly excited about how machine learning and deep learning are reinventing existing software categories and creating new consumer experiences. Ashu has invested in AI-enabled business applications (such as marketing technology and HR technology), data platforms, data center infrastructure, security & privacy, as well as online video.

Ashu serves on the boards of Anvilogic, Arize, Coefficient, Cohesity, Conviva, Eightfold, Fortanix, Ikigai Labs, Layer9, Levo, OpsMx, Stacklet, Skyflow, and Turing. In addition, Ashu was responsible for our investments in Aggregate Knowledge (acquired by Neustar), Custora (acquired by Amperity), FreeWheel (acquired by Comcast), TubeMogul (acquired by Adobe), and Tubi.tv (acquired by Fox).

Ashu has led seed investments in HipDot, Next Force Technology, Oliv.ai, Radiance Labs, Robin Systems, Testim, and has personally invested in Databricks, Falcon Computing, G2 Esports and VPS.

Ashu is passionate about helping technical founders find product-market fit, and scale as CEOs. His podcast B2B a CEO has featured Eric Yuan, Jennifer Tejada, Aaron Levie, and Tien Tzuo.

Before joining Foundation Capital in 2008, Ashu was the general manager for Microsoft’s online-advertising business and led field marketing for the software businesses. Previously, Ashu worked at McKinsey & Company, helping technology companies scale their go-to-market efforts. Earlier in his career, Ashu founded TringTring.com, one of the first search engines in Asia, set up Unilever’s Nepal operations, and led the marketing and pre-sales teams at Cadence Design Systems.

Ashu has a bachelor’s degree from the Indian Institute of Technology (IIT) in New Delhi and an MBA from the Indian Institute of Management at Bangalore, where he received the President’s Gold Medal.

Ashu has lived in India, Nigeria, and the Sudan, and today makes his home in California with his wife, Pooja (an entrepreneur), and their two sons.


Host: Vinayak Ramesh (Co-founder and CEO, Ikigai Labs)

Vinayak previously co-founded Wellframe ($45MM+ funding to date) to help leading health plans utilize A.I. to manage their complex patient populations.

He is an MIT-trained computer scientist and was selected to the Forbes 30 under 30 list in recognition of his entrepreneurial work. He received his S.B. and M. Eng degrees from MIT.

Originally published on medium.com

In this article:


Vinayak Ramesh

Recommended articles

Ikigai Labs Announces $25M in Series A Funding to Bring Generative AI for Tabular Data to All Enterprises
If AI Skills Are Not on Your Resume, You’re Already Behind
AI Academy
AI for the People, by the People
AI Competition

Subscribe to Ikigai Blog

Don't miss the latest updates from the Ikigai team.
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.