We backed Pecan’s recent $35M fundraising, and here’s why
Pecan.ai is a rapidly-growing startup that provides an easy-to-use Artificial Intelligence tool for business users and analysts, helping them analyze and optimize customer journeys and consumer behavior. Businesses such as retailers, consumer packaged-goods companies, mobile app developers, gaming companies, and even insurance companies, can start driving value from using Pecan’s AI solutions.
Pecan’s journey templates enable predicting demand forecasting, conversion, lifetime value, next best offer, upsell and cross-sell, churn, retention and additional sales analytics, much better than before. The platform connects to various data sources and automatically extracts the relevant data for the specific use case or template. Then, the engine automatically reconstructs the data for the predictive modeling algorithms. Pecan uses its unique automated feature engineering and selection algorithms, followed by autoML algorithms that – when combined – enable Pecan to achieve the maximal predictive accuracy in the minimal effort and time possible.
As an investor in VC funds and a co-investor in late stage startups, I know there are many key elements to take into consideration when choosing the right startup to invest in. After all, it is not a decision to be taken lightly. Some of the factors that supported our investment hypotheses at Vintage were the team, the product-market-fit and the technology. In this post, I will focus on the first two.
1) A Winning Team
- The CEO
Throughout my career of over 25 years I have interacted with tens of thousands of people in different geographies and professions. I have worked closely with corporate executives, service providers, entrepreneurs and startups from all over the world. I have seen thousands of startup CEOs in action and I can spot an outlier when I see one. Zohar Bronfman is an example of one.
As part of the Value-Added-Services we provide to our portfolio companies, we have organized 1,506 face-to-face meetings between corporates and startups in our office in the past five years. Too many times I have seen interactions between corporates and startups that are a one way pitch: a 20-30 minute monologue with slides explaining ‘what our startup does’. This is a one way street, which does not open up the opportunity for a dialogue.
A first sales meeting is sometimes more of an art than a science, but one thing should always happen – a conversation. I often find that the skill of listening is missing in these interactions. But not for Zohar. His ability to get anyone in front of him to say ‘yes’ and ask for a second meeting was almost second to none. He was able to convert most meetings to PoCs or POs, and to expand Pecan’s business with some of the largest organizations in the world, later on.
His combination of deep domain knowledge (Zohar is a double major PhD in Computational Neuroscience and Philosophy) together with his deep caring for people around him, including his potential customers, is unique. The result is a company culture of professionalism instilled with genuine customer care, which attracts customers and talent.
- Co-Founder Dynamics
Running a startup with a co-founder is like getting married and running a household together. To survive and succeed, co-founders need to be patient, have a lot of respect for one another, and understand how to make decisions in times of conflict without stepping on each other’s toes. This isn’t an easy thing to achieve and is essential for the success of a startup.
The co-founders of Pecan, Zohar Bronfman and Noam Brezis (who is also a double major PhD in AI-related topics) share such a bond, as well as a long history together. In addition to studying together at Tel Aviv University, they conducted joint academic research and were there for each other’s significant life events. It’s beautiful to see the harmony and respect between them when they speak about Pecan. It gives confidence in their ability to execute as a leadership team.
- Team Members
Zohar and Noam were able to recruit incredible talent to help grow the company. Their technology was built by an advanced data engineering team including PhDs in AI-related fields from Tel Aviv University, the Technion, and from Berlin. The team is diverse and includes outstanding talent from Google, Facebook, eBay, DataRobot and other companies, as well as an amazing VP Product who led Billing and Payments at WeWork.
2) The Product Market Fit – The Burning Need for Predictive Business Analytics in a Quick-Time-To-Model
Through our Value-Added Services, we work with corporate executives every day to understand their pain points and match the right startups to them. This is a free service, based on our portfolio of more than 2,250 companies. Our wide reach enables us to offer various solutions for a large number of business needs in a non-biased way. The result is a quadruple win – for our startups – bringing them qualified customer leads, for our funds – helping their startups, for the corporations – helping them with their digital transformation, and for ourselves – helping optimize our portfolio and bringing us high-quality insights and additional information about the startups.
In the past three years, multinational corporations have been continuously asking us for simplified AI-based predictive tools. Everyone is talking about AI and want to use it to predict business metrics and customer journey metrics that can help them boost their top line and reduce expenses. Based on several research reports, the market size is estimated to reach between hundreds of $B to single digit $T by 2025.
But not everyone has, or is ready to have, a massive data team. This is mainly the case with non core-tech enterprises such as CPG companies, retailers and insurance companies. Data teams can also be occupied with different tasks and priorities. We often hear from executives that they would like to leverage AI, but they have to wait in line for other projects that the data teams are busy with. As a result, they are stuck.
These recurring requests spyked our “VAS gauge”, a data model that anonymizes all business requests and indicates global trends. The strong product-market fit of Pecan.ai comes from the need for a quick time-to-model. There is a real need from enterprise clients that are looking for an impactful solution and are willing to pay for one, which is exactly what Pecan provides. We have seen Pecan’s engagement and expansion metrics matching and proving our thesis. We believe (strongly based on conversations with potential and existing customers) that Pecan is a strategic tool that helps move the needle and has the potential to save organizations millions of dollars.
Looking forward, we see there is still a gap between the potential of the AI market size and businesses’ ability to implement it on their own and with the existing tools available. We are excited about the opportunity to partner with Pecan together with the other investors. We’re here to support their efforts of closing that gap and becoming a leader in predictive AI solutions.
Written by Orly Glick. Partner
For more details about the round read here: