Fundraising

Fundraising

Series B fundraising: scaling up while focusing on the vision

We are delighted to share that we have strengthened our financial resilience and raised an additional $16M to help execute...

We are delighted to share that we have strengthened our financial resilience and raised an additional $16M to help execute...

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Elad Tsur

I am delighted to share that we have strengthened our financial resilience and raised an additional $16M to help execute our growth strategy and expand our platform capabilities as planned. With our previous $12M series A, we’ve raised a total of $28M to date. As with any fundraising process, it was challenging but critical for implementing our vision. More about that below.

Takeaways from Planck’s series B fundraising

If you’ve ever fundraised for a startup, then you know how stressful it can be. It all started in the fourth quarter of 2019. Before that, I was working 12-hour days. Once the fundraising initiative started, I started working 14-hour days and most weekends. Don’t get me wrong – I absolutely LOVED the process. I love stories and books, and telling the story of our amazing startup to investors felt incredible. When you see so many smart people fall in love with your amazing team, product and vision, it lets you know you’re doing something right!At the beginning of the process, I thought I would meet a couple dozen investors, answer requests for information from nine or ten, and negotiate with two or three to get to a deal with one of them. Here’s what actually happened:

  • I met with 64 investors, most of them financial investors, but a few corporate ventures. Only 5 out of those 64 told me that they weren’t interested. For the remaining 59 who wanted to know more, I’ve met with each about five times, including many information requests. During the process, I gathered all of their questions and compiled them into one document: 26 pages of Q&As.

  • Out of those 59 investors, 17 completed the tech and product diligence, initial business diligence, and continued to the “data room” stage, beginning a financial and legal diligence process. That usually meant about five more meetings.

  • We received a few term sheets and went into our own diligence on the investors. We have spoken with their portfolio companies, peer board members, past colleagues, and many more. After all this thorough research, we eventually picked Team8 to lead the round and two strategic investors to follow: Nationwide Ventures and HDI Group.

  • We continued to work with the three VCs that invested in our series A round (Arbor Ventures, Viola Fintech, and Eight Roads) and on top of that, we had to go to their investment committees to approve their participation in the new round – all of whom used their entire pro-rata rights and participated in our B round as well.

Thinking about Planck as a data vendor is like buying a Mercedes to charge your phone: you can keep your phone connected to the USB charger in your car sitting in a parking lot, but you’re missing the point.

Why did we fundraise and how is that connected to our vision?

Planck has reached a point where we have to support rapid scaling. In 2019, our customer base grew by 5x, the number of machine-learning models we trained and deployed to production grew by 10x, and the average expansion of our existing customers was 4x. We had two options: either slow down and maintain linear growth with our existing staff, or move to an investment round to keep the pace of our exponential growth. We chose the latter. Insurance is all about analyzing data to assess risks. But, there is a flaw in this methodology: the data used to underwrite clients is generated and sent to insurance companies by agents, who in turn have their own incentives and priorities. This has created a situation where the data that insurers receive is neither accurate nor complete. In order to solve this huge pain point, Planck created an AI platform that is able to generate commercial underwriting insights in real time, from public data sources such as the open web. This is not about simply finding a needle in a haystack. The data insurers are looking for is not clearly visible on the web (only about 12% of it is plainly visible and can be returned by aggregating many different sources). In order to return the relevant, accurate data needed, you have to use AI models to create it: spinning gold out of the hay. For example, think about a bar’s percentage of liquor sales out of its total revenue. In order to create this data point, we use a deep-learning model that has been trained on audited data sets, converting intermediate insights into the requested insight. Those intermediate insights (e.g. the number of people standing vs. sitting, the intensity of the light, the number of beer bottles and wine glasses compared to the number of dishes and plates) are created using machine-learning techniques as well.

Imagine crawling and fetching millions of data points, processing them using thousands of machine-learning models to create intermediate insights, then processing those by hundreds of machine-learning models to create accurate and hyper-relevant underwriting insights – all in real time, all for every submission or policy of our customers – and now you understand Planck’s current scale.

Our existing data dictionaries contain thousands of commercial insights available to our customers. But thinking about Planck as a data vendor is like buying a Mercedes to charge your phone: you can keep your phone connected to the USB charger in your car sitting in a parking lot, but you’re missing the point.Planck’s AI platform can return almost any insight underwriters can dream up, up-to-date and in real time. They are no longer limited by existing questionnaires or by what is plainly apparent over the web. When they recognize the opportunities that this presents, their business is transformed. They start by changing their eligibility criteria to more granularly cluster customers, adding new indicative markers to their underwriting models, monitoring all of their existing policies to track any risk changes in real time and alert accordingly, measuring their true exposure by comparing their book with all of the business in the same region, and much much more.Planck’s mission is to enable commercial insurers to grow their new and retained commercial business while reducing their loss and expense ratios. But Planck’s vision is even broader. Our vision is to be the Insights Sage of the Commercial World. Planck will be the oracle that you consult to shed light on any commercial question you have. Our series B fundraising definitely keeps us on track to achieve this vision.

A few words about COVID-19

COVID-19 reached pandemic status toward the end of the round, and like many others, we have changed our business plan accordingly. Planck has always been and will continue to be committed to our customers and their business. We continue to monitor the coronavirus outbreak very closely and are taking appropriate measures concerning our employees, business operations and, importantly, our service to our customers.

In addition to following guidance from international health organizations, local governments as well as our own safety and security protocols, we’ve put in place several measures to ensure uninterrupted service to all of our customers. To date, we’ve had no issues; our teams are 100 percent up and running, and fully capable of continuing to provide contracted support and services.

We’ve also conducted dozens of roundtable discussions with executives from commercial insurance companies, assessing the impact of the pandemic on their business, and also used our platform to analyze the changes in small and midsize businesses’ risk. Our market research team is finalizing our findings and insights, and we look forward to sharing this information with our community soon.

Please don’t hesitate to reach out; these are times when we lean on partners who can help when needed. I wish all of you, your families and business associates all the best, and stay safe.

Elad

CEO and Co-founder at Planck


I am delighted to share that we have strengthened our financial resilience and raised an additional $16M to help execute our growth strategy and expand our platform capabilities as planned. With our previous $12M series A, we’ve raised a total of $28M to date. As with any fundraising process, it was challenging but critical for implementing our vision. More about that below.

Takeaways from Planck’s series B fundraising

If you’ve ever fundraised for a startup, then you know how stressful it can be. It all started in the fourth quarter of 2019. Before that, I was working 12-hour days. Once the fundraising initiative started, I started working 14-hour days and most weekends. Don’t get me wrong – I absolutely LOVED the process. I love stories and books, and telling the story of our amazing startup to investors felt incredible. When you see so many smart people fall in love with your amazing team, product and vision, it lets you know you’re doing something right!At the beginning of the process, I thought I would meet a couple dozen investors, answer requests for information from nine or ten, and negotiate with two or three to get to a deal with one of them. Here’s what actually happened:

  • I met with 64 investors, most of them financial investors, but a few corporate ventures. Only 5 out of those 64 told me that they weren’t interested. For the remaining 59 who wanted to know more, I’ve met with each about five times, including many information requests. During the process, I gathered all of their questions and compiled them into one document: 26 pages of Q&As.

  • Out of those 59 investors, 17 completed the tech and product diligence, initial business diligence, and continued to the “data room” stage, beginning a financial and legal diligence process. That usually meant about five more meetings.

  • We received a few term sheets and went into our own diligence on the investors. We have spoken with their portfolio companies, peer board members, past colleagues, and many more. After all this thorough research, we eventually picked Team8 to lead the round and two strategic investors to follow: Nationwide Ventures and HDI Group.

  • We continued to work with the three VCs that invested in our series A round (Arbor Ventures, Viola Fintech, and Eight Roads) and on top of that, we had to go to their investment committees to approve their participation in the new round – all of whom used their entire pro-rata rights and participated in our B round as well.

Thinking about Planck as a data vendor is like buying a Mercedes to charge your phone: you can keep your phone connected to the USB charger in your car sitting in a parking lot, but you’re missing the point.

Why did we fundraise and how is that connected to our vision?

Planck has reached a point where we have to support rapid scaling. In 2019, our customer base grew by 5x, the number of machine-learning models we trained and deployed to production grew by 10x, and the average expansion of our existing customers was 4x. We had two options: either slow down and maintain linear growth with our existing staff, or move to an investment round to keep the pace of our exponential growth. We chose the latter. Insurance is all about analyzing data to assess risks. But, there is a flaw in this methodology: the data used to underwrite clients is generated and sent to insurance companies by agents, who in turn have their own incentives and priorities. This has created a situation where the data that insurers receive is neither accurate nor complete. In order to solve this huge pain point, Planck created an AI platform that is able to generate commercial underwriting insights in real time, from public data sources such as the open web. This is not about simply finding a needle in a haystack. The data insurers are looking for is not clearly visible on the web (only about 12% of it is plainly visible and can be returned by aggregating many different sources). In order to return the relevant, accurate data needed, you have to use AI models to create it: spinning gold out of the hay. For example, think about a bar’s percentage of liquor sales out of its total revenue. In order to create this data point, we use a deep-learning model that has been trained on audited data sets, converting intermediate insights into the requested insight. Those intermediate insights (e.g. the number of people standing vs. sitting, the intensity of the light, the number of beer bottles and wine glasses compared to the number of dishes and plates) are created using machine-learning techniques as well.

Imagine crawling and fetching millions of data points, processing them using thousands of machine-learning models to create intermediate insights, then processing those by hundreds of machine-learning models to create accurate and hyper-relevant underwriting insights – all in real time, all for every submission or policy of our customers – and now you understand Planck’s current scale.

Our existing data dictionaries contain thousands of commercial insights available to our customers. But thinking about Planck as a data vendor is like buying a Mercedes to charge your phone: you can keep your phone connected to the USB charger in your car sitting in a parking lot, but you’re missing the point.Planck’s AI platform can return almost any insight underwriters can dream up, up-to-date and in real time. They are no longer limited by existing questionnaires or by what is plainly apparent over the web. When they recognize the opportunities that this presents, their business is transformed. They start by changing their eligibility criteria to more granularly cluster customers, adding new indicative markers to their underwriting models, monitoring all of their existing policies to track any risk changes in real time and alert accordingly, measuring their true exposure by comparing their book with all of the business in the same region, and much much more.Planck’s mission is to enable commercial insurers to grow their new and retained commercial business while reducing their loss and expense ratios. But Planck’s vision is even broader. Our vision is to be the Insights Sage of the Commercial World. Planck will be the oracle that you consult to shed light on any commercial question you have. Our series B fundraising definitely keeps us on track to achieve this vision.

A few words about COVID-19

COVID-19 reached pandemic status toward the end of the round, and like many others, we have changed our business plan accordingly. Planck has always been and will continue to be committed to our customers and their business. We continue to monitor the coronavirus outbreak very closely and are taking appropriate measures concerning our employees, business operations and, importantly, our service to our customers.

In addition to following guidance from international health organizations, local governments as well as our own safety and security protocols, we’ve put in place several measures to ensure uninterrupted service to all of our customers. To date, we’ve had no issues; our teams are 100 percent up and running, and fully capable of continuing to provide contracted support and services.

We’ve also conducted dozens of roundtable discussions with executives from commercial insurance companies, assessing the impact of the pandemic on their business, and also used our platform to analyze the changes in small and midsize businesses’ risk. Our market research team is finalizing our findings and insights, and we look forward to sharing this information with our community soon.

Please don’t hesitate to reach out; these are times when we lean on partners who can help when needed. I wish all of you, your families and business associates all the best, and stay safe.

Elad

CEO and Co-founder at Planck


I am delighted to share that we have strengthened our financial resilience and raised an additional $16M to help execute our growth strategy and expand our platform capabilities as planned. With our previous $12M series A, we’ve raised a total of $28M to date. As with any fundraising process, it was challenging but critical for implementing our vision. More about that below.

Takeaways from Planck’s series B fundraising

If you’ve ever fundraised for a startup, then you know how stressful it can be. It all started in the fourth quarter of 2019. Before that, I was working 12-hour days. Once the fundraising initiative started, I started working 14-hour days and most weekends. Don’t get me wrong – I absolutely LOVED the process. I love stories and books, and telling the story of our amazing startup to investors felt incredible. When you see so many smart people fall in love with your amazing team, product and vision, it lets you know you’re doing something right!At the beginning of the process, I thought I would meet a couple dozen investors, answer requests for information from nine or ten, and negotiate with two or three to get to a deal with one of them. Here’s what actually happened:

  • I met with 64 investors, most of them financial investors, but a few corporate ventures. Only 5 out of those 64 told me that they weren’t interested. For the remaining 59 who wanted to know more, I’ve met with each about five times, including many information requests. During the process, I gathered all of their questions and compiled them into one document: 26 pages of Q&As.

  • Out of those 59 investors, 17 completed the tech and product diligence, initial business diligence, and continued to the “data room” stage, beginning a financial and legal diligence process. That usually meant about five more meetings.

  • We received a few term sheets and went into our own diligence on the investors. We have spoken with their portfolio companies, peer board members, past colleagues, and many more. After all this thorough research, we eventually picked Team8 to lead the round and two strategic investors to follow: Nationwide Ventures and HDI Group.

  • We continued to work with the three VCs that invested in our series A round (Arbor Ventures, Viola Fintech, and Eight Roads) and on top of that, we had to go to their investment committees to approve their participation in the new round – all of whom used their entire pro-rata rights and participated in our B round as well.

Thinking about Planck as a data vendor is like buying a Mercedes to charge your phone: you can keep your phone connected to the USB charger in your car sitting in a parking lot, but you’re missing the point.

Why did we fundraise and how is that connected to our vision?

Planck has reached a point where we have to support rapid scaling. In 2019, our customer base grew by 5x, the number of machine-learning models we trained and deployed to production grew by 10x, and the average expansion of our existing customers was 4x. We had two options: either slow down and maintain linear growth with our existing staff, or move to an investment round to keep the pace of our exponential growth. We chose the latter. Insurance is all about analyzing data to assess risks. But, there is a flaw in this methodology: the data used to underwrite clients is generated and sent to insurance companies by agents, who in turn have their own incentives and priorities. This has created a situation where the data that insurers receive is neither accurate nor complete. In order to solve this huge pain point, Planck created an AI platform that is able to generate commercial underwriting insights in real time, from public data sources such as the open web. This is not about simply finding a needle in a haystack. The data insurers are looking for is not clearly visible on the web (only about 12% of it is plainly visible and can be returned by aggregating many different sources). In order to return the relevant, accurate data needed, you have to use AI models to create it: spinning gold out of the hay. For example, think about a bar’s percentage of liquor sales out of its total revenue. In order to create this data point, we use a deep-learning model that has been trained on audited data sets, converting intermediate insights into the requested insight. Those intermediate insights (e.g. the number of people standing vs. sitting, the intensity of the light, the number of beer bottles and wine glasses compared to the number of dishes and plates) are created using machine-learning techniques as well.

Imagine crawling and fetching millions of data points, processing them using thousands of machine-learning models to create intermediate insights, then processing those by hundreds of machine-learning models to create accurate and hyper-relevant underwriting insights – all in real time, all for every submission or policy of our customers – and now you understand Planck’s current scale.

Our existing data dictionaries contain thousands of commercial insights available to our customers. But thinking about Planck as a data vendor is like buying a Mercedes to charge your phone: you can keep your phone connected to the USB charger in your car sitting in a parking lot, but you’re missing the point.Planck’s AI platform can return almost any insight underwriters can dream up, up-to-date and in real time. They are no longer limited by existing questionnaires or by what is plainly apparent over the web. When they recognize the opportunities that this presents, their business is transformed. They start by changing their eligibility criteria to more granularly cluster customers, adding new indicative markers to their underwriting models, monitoring all of their existing policies to track any risk changes in real time and alert accordingly, measuring their true exposure by comparing their book with all of the business in the same region, and much much more.Planck’s mission is to enable commercial insurers to grow their new and retained commercial business while reducing their loss and expense ratios. But Planck’s vision is even broader. Our vision is to be the Insights Sage of the Commercial World. Planck will be the oracle that you consult to shed light on any commercial question you have. Our series B fundraising definitely keeps us on track to achieve this vision.

A few words about COVID-19

COVID-19 reached pandemic status toward the end of the round, and like many others, we have changed our business plan accordingly. Planck has always been and will continue to be committed to our customers and their business. We continue to monitor the coronavirus outbreak very closely and are taking appropriate measures concerning our employees, business operations and, importantly, our service to our customers.

In addition to following guidance from international health organizations, local governments as well as our own safety and security protocols, we’ve put in place several measures to ensure uninterrupted service to all of our customers. To date, we’ve had no issues; our teams are 100 percent up and running, and fully capable of continuing to provide contracted support and services.

We’ve also conducted dozens of roundtable discussions with executives from commercial insurance companies, assessing the impact of the pandemic on their business, and also used our platform to analyze the changes in small and midsize businesses’ risk. Our market research team is finalizing our findings and insights, and we look forward to sharing this information with our community soon.

Please don’t hesitate to reach out; these are times when we lean on partners who can help when needed. I wish all of you, your families and business associates all the best, and stay safe.

Elad

CEO and Co-founder at Planck


Get to know

Frequently

asked

questions

If you have additional questions, we're excited to help you.

What are Planck insights?

What types of processes can Planck automate?

What is AI Underwriting?

How does GenAI enhance Planck’s data and insights?

How can customer receive Planck insights?

Get to Know

Frequently

asked

questions

If you have additional questions, we're excited to help you.

What are Planck insights?

What types of processes can Planck automate?

What is AI Underwriting?

How does GenAI enhance Planck’s data and insights?

How can customer receive Planck insights?

Get to Know

Frequently

asked

questions

If you have additional questions, we're excited to help you.

What are Planck insights?

What types of processes can Planck automate?

What is AI Underwriting?

How does GenAI enhance Planck’s data and insights?

How can customer receive Planck insights?

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