StarZero All shows Try the podcast clipper →

Mar 1, 2019 · 15m · top-founders

1315 Her Best Friend Died From Terminal Cancer, She Launches MedTech SaaS Raising $2.5m on $10m Pre

Kim Walpole · 8m spoken Nathan Latka · 5m spoken
0:00 / 0:00

gold bands on the timeline = statements, start to end. Hover to read, click to jump. CC turns on captions

In this episode of The Top Entrepreneurs Podcast, host Nathan Latka interviews Kim Walpole, founder and CEO of Trials.ai, about how she transformed personal tragedy into an AI-powered MedTech SaaS platform. Walpole details her company's enterprise pricing structure, 0% customer churn rate, and ongoing efforts to raise a $2.5 million funding round at a $10 million pre-money valuation.

How this conversation actually went

Every chapter scored 0–10 on four independent dynamics. Hover any point for the reasoning behind the score. Nathan holds 37.7% of the talking time here. How this is scored →

Nathan as informed peer 4.3 Guest teaching 2.5 Guest disagreement 1.3 Nathan pushing back 2.8
05100:0010:001:21–4:31 · Nathan as informed peer 3/10 Introducing Kim Walpole and How Trials.ai Operates Nathan introduces the company and brings up medtech skepticism like Theranos. Kim explains the AI workflow navigation system and clarifies that her friend Paul was male and passed away before clinical trials could begin.4:31–7:10 · Nathan as informed peer 4/10 SaaS Business Model and Enterprise Contract Pricing Kim details their SaaS per-trial pricing model of roughly $200k annually per trial. She also gently corrects Nathan on the timeline when he assumes the company began five years prior in 2013 rather than 2016.7:11–10:57 · Nathan as informed peer 6/10 Seed Capital and Current $2.5M Fundraising Round Nathan does the math on their $25k MRR ($300k ARR) versus their $10M pre-money valuation target, highlighting a high 33x multiple and probing for potential valuation risks. He also catches the mathematical tension between $200k ACV and $25k MRR, which Kim attributes to early pilot discounting.10:58–14:31 · Nathan as informed peer 4/10 Team Growth, Software Stickiness, and Unit Economics Kim discusses zero churn and workflow stickiness, prompting Nathan to suggest the product might be underpriced. The segment shifts to standard Famous Five questions where Nathan expresses disbelief over Kim sleeping only 3 to 4 hours per night.1:21–4:31 · Guest teaching 3/10 Introducing Kim Walpole and How Trials.ai Operates Nathan introduces the company and brings up medtech skepticism like Theranos. Kim explains the AI workflow navigation system and clarifies that her friend Paul was male and passed away before clinical trials could begin.4:31–7:10 · Guest teaching 3/10 SaaS Business Model and Enterprise Contract Pricing Kim details their SaaS per-trial pricing model of roughly $200k annually per trial. She also gently corrects Nathan on the timeline when he assumes the company began five years prior in 2013 rather than 2016.7:11–10:57 · Guest teaching 2/10 Seed Capital and Current $2.5M Fundraising Round Nathan does the math on their $25k MRR ($300k ARR) versus their $10M pre-money valuation target, highlighting a high 33x multiple and probing for potential valuation risks. He also catches the mathematical tension between $200k ACV and $25k MRR, which Kim attributes to early pilot discounting.10:58–14:31 · Guest teaching 2/10 Team Growth, Software Stickiness, and Unit Economics Kim discusses zero churn and workflow stickiness, prompting Nathan to suggest the product might be underpriced. The segment shifts to standard Famous Five questions where Nathan expresses disbelief over Kim sleeping only 3 to 4 hours per night.1:21–4:31 · Guest disagreement 1/10 Introducing Kim Walpole and How Trials.ai Operates Nathan introduces the company and brings up medtech skepticism like Theranos. Kim explains the AI workflow navigation system and clarifies that her friend Paul was male and passed away before clinical trials could begin.4:31–7:10 · Guest disagreement 1/10 SaaS Business Model and Enterprise Contract Pricing Kim details their SaaS per-trial pricing model of roughly $200k annually per trial. She also gently corrects Nathan on the timeline when he assumes the company began five years prior in 2013 rather than 2016.7:11–10:57 · Guest disagreement 2/10 Seed Capital and Current $2.5M Fundraising Round Nathan does the math on their $25k MRR ($300k ARR) versus their $10M pre-money valuation target, highlighting a high 33x multiple and probing for potential valuation risks. He also catches the mathematical tension between $200k ACV and $25k MRR, which Kim attributes to early pilot discounting.10:58–14:31 · Guest disagreement 1/10 Team Growth, Software Stickiness, and Unit Economics Kim discusses zero churn and workflow stickiness, prompting Nathan to suggest the product might be underpriced. The segment shifts to standard Famous Five questions where Nathan expresses disbelief over Kim sleeping only 3 to 4 hours per night.1:21–4:31 · Nathan pushing back 1/10 Introducing Kim Walpole and How Trials.ai Operates Nathan introduces the company and brings up medtech skepticism like Theranos. Kim explains the AI workflow navigation system and clarifies that her friend Paul was male and passed away before clinical trials could begin.4:31–7:10 · Nathan pushing back 2/10 SaaS Business Model and Enterprise Contract Pricing Kim details their SaaS per-trial pricing model of roughly $200k annually per trial. She also gently corrects Nathan on the timeline when he assumes the company began five years prior in 2013 rather than 2016.7:11–10:57 · Nathan pushing back 5/10 Seed Capital and Current $2.5M Fundraising Round Nathan does the math on their $25k MRR ($300k ARR) versus their $10M pre-money valuation target, highlighting a high 33x multiple and probing for potential valuation risks. He also catches the mathematical tension between $200k ACV and $25k MRR, which Kim attributes to early pilot discounting.10:58–14:31 · Nathan pushing back 3/10 Team Growth, Software Stickiness, and Unit Economics Kim discusses zero churn and workflow stickiness, prompting Nathan to suggest the product might be underpriced. The segment shifts to standard Famous Five questions where Nathan expresses disbelief over Kim sleeping only 3 to 4 hours per night.

speaking balance: gold is Nathan, purple is the guest (3 minute bins)

0:00 · Nathan 69.3% · guest 30.7%0:00 · Nathan 69.3% · guest 30.7%3:00 · Nathan 18.9% · guest 81.1%3:00 · Nathan 18.9% · guest 81.1%6:00 · Nathan 16.3% · guest 83.7%6:00 · Nathan 16.3% · guest 83.7%9:00 · Nathan 34.4% · guest 65.6%9:00 · Nathan 34.4% · guest 65.6%12:00 · Nathan 47.6% · guest 52.4%12:00 · Nathan 47.6% · guest 52.4%15:00 · Nathan 85.2% · guest 14.8%15:00 · Nathan 85.2% · guest 14.8%
Sharpest disagreement ▶ 9:48 Defending high valuation multiple with pipeline data

When Nathan presses on the risk of raising at a 33x multiple, Kim pushes back by pointing out that investors evaluate forward-looking enterprise pipeline volume rather than backward MRR.

 Hardest push from Nathan ▶ 10:34 Challenging customer revenue math

Nathan directly highlights the numerical discrepancy between having four customers paying $200k annually and currently reporting only $25k in MRR.

 Biggest teaching moment ▶ 6:54 Correcting the founding timeline

Kim straightforwardly corrects Nathan's mistaken assumption that the company started in 2013 five years earlier, setting the record straight that it was founded in 2016.

 Nathan holds their own ▶ 9:33 Instant multiple calculation

Nathan rapidly annualizes Kim's $25k monthly recurring revenue to $300k and frames her $10M pre-money ask as a steep 33x multiple.
the scores for every segment, with the reasoning behind each
ChapterTopicNathan as informed peerGuest teachingGuest disagreementNathan pushing backWhy
Introducing Kim Walpole and How Trials.ai Operates 3311 Nathan introduces the company and brings up medtech skepticism like Theranos. Kim explains the AI workflow navigation system and clarifies that her friend Paul was male and passed away before clinical trials could begin.
SaaS Business Model and Enterprise Contract Pricing 4312 Kim details their SaaS per-trial pricing model of roughly $200k annually per trial. She also gently corrects Nathan on the timeline when he assumes the company began five years prior in 2013 rather than 2016.
Seed Capital and Current $2.5M Fundraising Round 6225 Nathan does the math on their $25k MRR ($300k ARR) versus their $10M pre-money valuation target, highlighting a high 33x multiple and probing for potential valuation risks. He also catches the mathematical tension between $200k ACV and $25k MRR, which Kim attributes to early pilot discounting.
Team Growth, Software Stickiness, and Unit Economics 4213 Kim discusses zero churn and workflow stickiness, prompting Nathan to suggest the product might be underpriced. The segment shifts to standard Famous Five questions where Nathan expresses disbelief over Kim sleeping only 3 to 4 hours per night.

Statements from this episode (10)

Disclosure
Walpole: Trials.ai trained algorithms on historical trial data and medical journals
“So we are, you know, we started by training our algorithms on historic data from trials that were both successful as well as not successful, medical journals, basically anything we could get our hands on.”
Kim Walpole Mar 1, 2019 ▶ 2:13
Assertion Not checkable as stated
Walpole: Trials.ai cuts study design time from 9–12 months to weeks
“On the study design side, you know, it takes anywhere from nine to 12 months to do that. We're cutting that down to weeks and eventually days.”
Kim Walpole Mar 1, 2019 ▶ 4:01
Disclosure
Walpole: Average phase two trial generates about $200K annually for Trials.ai
“For us, an average trial, maybe a phase two trial of 350 users would generate about 200 K on average annually.”
Kim Walpole Mar 1, 2019 ▶ 5:40
Disclosure
Walpole: Trials.ai raised $750k in December and is raising $2.5M
“And we raised 750,000 back in the end of December, and now we're doing a 2.5 million dollar raise.”
Kim Walpole Mar 1, 2019 ▶ 7:48
Disclosure
Kim Walpole: Trials.ai in fundraising talks at $10M pre-money valuation
“We're conversations we're having is at a ten million pre.”
Kim Walpole Mar 1, 2019 ▶ 8:58
Assertion Not checkable as stated
Kim Walpole: Trials.ai generates about $25,000 MRR
“Currently we're at about 25 K MRR.”
Kim Walpole Mar 1, 2019 ▶ 9:06
Assertion Not checkable as stated
Kim Walpole: Trials.ai works with 4 customers across 5 studies
“We actually have two trials that are completed. We're working with four customers. We've got five studies total. And like I said, we've got seven coming up. We're rolling one out right now.”
Kim Walpole Mar 1, 2019 ▶ 10:23
Assertion Not checkable as stated
Kim Walpole: Trials.ai closed $250,000 in new bookings over two months
“Over the last two months you know, we've closed about 250,000 in new bookings.”
Kim Walpole Mar 1, 2019 ▶ 10:51
Assertion Not checkable as stated
Walpole: Trials.ai cut a customer's data errors by 20%
“We've got one customer that came to us, they ran their first trial, they liked it so much, we saved them three hours on admin tasks per day, per person And then decrease their data errors by 20%.”
Kim Walpole Mar 1, 2019 ▶ 11:20
Assertion Not checkable as stated
Walpole: Trials.ai has experienced zero paying customer churn
“No, we haven't lost anyone yet.”
Kim Walpole Mar 1, 2019 ▶ 11:56
Made with StarZero

Turn any episode into a week of clips.

This entire site, over 2,600 episodes transcribed, diarized, checked and made playable, runs on the StarZero media pipeline. Drop in your own episode and the podcast clipper finds the moments worth sharing, cuts them, captions them, and reframes them for every feed.

Try the podcast clipper Learn more