Optimal Ag Solutions at Tech Hub LIVE 2026 — Transcript

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1. 0:06So I'd like to introduce to you today
2. 0:08optimal a solutions um very intently
3. 0:13named optimal a solutions. One of the
4. 0:16key things that we um have always built
5. 0:19in our previous companies is identifying
6. 0:22a farmer problem. And if we can identify
7. 0:27a problem that's causing some angst um
8. 0:30uncertainty or concerns, can we actually
9. 0:33solve that problem and can we build a
10. 0:36solution around that problem and
11. 0:39ultimately build a company to provide
12. 0:41that solution. Some previous ventures uh
13. 0:44we created Crop One Insurance. We grew
14. 0:47that company to $300 million and the
15. 0:50solution we identified was could we be
16. 0:54more efficient as an insurance company
17. 0:56and provide a savings to the American
18. 0:58farmers. We did that. We started with
19. 1:01zero and rapidly grew that company
20. 1:04always with an eye towards helping our
21. 1:06farmers grow. Well, with optimal a
22. 1:09solutions, we understood that the
23. 1:12marketplace is changing. There's a lot
24. 1:14of new products coming out. We hear
25. 1:16about biologicals and adivants and new
26. 1:20new maybe prescriptions or practices and
27. 1:25as a farmer and looking at it from a
28. 1:27farmer's lens,
29. 1:29how are we able to give that farmer
30. 1:32confidence that this particular solution
31. 1:36or practice or combination is going to
32. 1:40work and a very kind of a simple idea.
33. 1:43We were like, well, what if we could
34. 1:45provide a backs stop that in the event
35. 1:49the particular product or practice did
36. 1:52not yield the outcome that was being
37. 1:55projected, we would provide a guarantee,
38. 1:59a financial guarantee.
39. 2:02So the idea is pretty simple. Hey, try
40. 2:04my new product so we can help a
41. 2:06retailers, a manufacturers grow. And if
42. 2:10that particular product doesn't achieve
43. 2:14the claimed improvement, which could be
44. 2:16maybe a lower CI score, maybe an
45. 2:19increased yield, maybe um another
46. 2:22benefit that we would then underwrite
47. 2:26it, mitigate the risk and provide a
48. 2:29actual financial payment to the
49. 2:32distributor or and ultimately to the
50. 2:35farmer.
51. 2:36So, thus the name Optimal Egg Solutions,
52. 2:40we work with any egg manufacturer, any
53. 2:43egg retailer, all with the goal to help
54. 2:46them get what? Greater market share, get
55. 2:51penetration,
56. 2:52uh maybe incell more per acre and more
57. 2:56acres per farmer to help their ROI on
58. 3:00their particular company too.
59. 3:04We like to look at our company as a
60. 3:07three-legged chair. The first leg starts
61. 3:10with what we call our yield labs. This
62. 3:12is probably one of the most important
63. 3:14legs of the chair. We need really good
64. 3:17data that can confirm that that
65. 3:20particular product or prescription or
66. 3:22practices work. So, you're going to hear
67. 3:25today a little more about our yield
68. 3:27labs. We have a facility up outside of
69. 3:29Ames, Iowa. It's actually one of the
70. 3:31oldest testing facilities. Um it was
71. 3:34founded by a guy you may know, Henry
72. 3:36Wall Wallace of the Pioneer fame and so
73. 3:40we contract with those and other CRO
74. 3:43across the Midwest and we perform
75. 3:47extensive amount of trials. Running
76. 3:50trials you think would be very easy. You
77. 3:52just go plant it, compare the
78. 3:54difference. But when you want high
79. 3:57quality data, scientific data, it's a
80. 4:00whole different game and we'll talk a
81. 4:01little more about that. But what do we
82. 4:04do with this data? This data then feeds
83. 4:07over to our yield optimizer. We've built
84. 4:10an AI machine learning tool that allows
85. 4:13you to drop a pin on any field in the
86. 4:16Midwest and we're going to be able to
87. 4:20identify 20 years worth of weather
88. 4:22history over it, identify the soil, set
89. 4:25your relative maturity range, is it
90. 4:27irrigated, non-errigated, and we because
91. 4:30of our yield labs testing every major
92. 4:34seed manufacturer. Think about that for
93. 4:37a second. all the different hybrids and
94. 4:39varieties. We test them all and we
95. 4:43simply let our farmers and and
96. 4:46distributors and seed dealers and
97. 4:48manufacturers drop a pin on the field
98. 4:50and we rank from best to worst what are
99. 4:54the best performing seeds for that
100. 4:57particular field. And then we also have
101. 5:00built in throughout the years in our
102. 5:04yield optimizer tool the ability to do
103. 5:06sideby-side comparison. As a farmer I
104. 5:09always have my particular brands I like
105. 5:11my varieties I like. Well now we allow
106. 5:14them to see the why. Why is your your
107. 5:18particular favorite maybe not as good as
108. 5:20what the model recommended?
109. 5:22And the kicker here is that this is all
110. 5:25backed by a guarantee. So, it's just not
111. 5:28marketing. And for maybe some of the um
112. 5:31older people in my generation that
113. 5:33remember the magazine Consumer Reports,
114. 5:36guys remember that? Well, yeah, you do,
115. 5:39right? We still look at Consumer
116. 5:40Reports. And with that, you know, why do
117. 5:43you look at it? Because it's a
118. 5:45independently tested, right? Unbiased
119. 5:48hopefully. And you can see what is the
120. 5:51best, you know, phone or whatever it
121. 5:53might be. That's what Yield Labs is all
122. 5:56about. We independently test. We are not
123. 6:01uh we pay, it's a very expensive line
124. 6:03item for our company. Um certain
125. 6:05manufacturers will provide us their
126. 6:08products, but we do not take any money
127. 6:11from any of the manufacturers or
128. 6:12distributors. And we take all of that
129. 6:16information, we cleanse it, we organize
130. 6:19it, and we run it through our machine
131. 6:22learning models, which you're going to
132. 6:24see a little example of with and called
133. 6:26the yield optimizer.
134. 6:28So that's the second leg of our company
135. 6:30is what do you do with all this yield
136. 6:33lab data? How do you organize it so it
137. 6:36can become actionable that you can make
138. 6:39a decision based on that yield optimizer
139. 6:43output?
140. 6:44The next is we also take um the same
141. 6:49data set and our company uh because
142. 6:51we're also an insurance company. We have
143. 6:54data scientist and actuarial team. Um
144. 6:58which is very different from your data
145. 7:00scientist on an aronomist. I kind of
146. 7:03call it like the Reese's peanut butter
147. 7:05cup. You know, you mix the chocolate and
148. 7:07the peanut butter and you get a great
149. 7:08combination. Well, that's what our
150. 7:10company's team is like. We have the
151. 7:12insurance side and we have the aronomy
152. 7:14side. But they come together and we take
153. 7:17all those data sets and we put it into a
154. 7:20stocastic model. And in that model, this
155. 7:23is how reinsurers who back insurance
156. 7:26companies like to see all the data
157. 7:28presented. And we will run what's called
158. 7:31EP curves, expected loss ratio, standard
159. 7:33deviation, standard means. And all of
160. 7:36this is to do what? so that we can bring
161. 7:39in the largest reinsurers in the world
162. 7:42who backs stop our programs. So, we're
163. 7:46an insurance company, but we're backed
164. 7:48by AM Best, which is a rating agency, a
165. 7:51rated or better reinsurers,
166. 7:55but they have to do the same
167. 7:57underwriting that we do. Where did your
168. 7:59data come from? Can I trust this data?
169. 8:02Well, now that you have the data and
170. 8:03it's cleansed, can you put it in into a
171. 8:07model? stochastic model that generates
172. 8:10an exceedence probability curve that we
173. 8:12can then rate the risk. So that's what's
174. 8:15going on in the yield guarantee.
175. 8:18So we take those three legs of the chair
176. 8:21and we go to our a retailer friends, we
177. 8:23go to our a manufacturers and we say we
178. 8:26believe in certain products. We're big
179. 8:28fungicide fans. For instance, there's a
180. 8:32lot of biologicals out there. Which ones
181. 8:34can I trust? which ones can I not trust?
182. 8:37When we talk to our farming friends, I'm
183. 8:39from Dyerville, Iowa, Field of Dreams.
184. 8:42My school bus actually went on that
185. 8:44particular gravel road two times a day.
186. 8:46I rode it. Um, truth be told, I probably
187. 8:48um had my first beer on that gravel road
188. 8:50and maybe kissed my first girl on that
189. 8:52gravel road. Okay, too much detail, I
190. 8:54know, but um you we have to be able to
191. 9:01help our egg manufacturers and retailers
192. 9:04convince farmers who are receiving, you
193. 9:07know, sometimes they'll get 10 guys come
194. 9:09down their farm lane in the last two
195. 9:11weeks and they're all saying, "What?
196. 9:14Try my product and your yield's going to
197. 9:16increase."
198. 9:18Well, if I believed every guy who came
199. 9:19down my lane for the last two weeks, my
200. 9:22yields would be up to 400 bushels per
201. 9:24acre, right? Just not going to happen.
202. 9:27So, we we empathize with our farming
203. 9:30friends. It's very hard to determine
204. 9:33what to do. And sometimes, especially
205. 9:35under a financial pressure that we've
206. 9:37been under in this horrific cycle for
207. 9:39the last three years, is how can I make
208. 9:42a decision when the banker saying, "Hey,
209. 9:45you're eroding your balance sheet. You
210. 9:47know, we're going to give you this
211. 9:48operating note again this year, but we
212. 9:51really need to see things turn around."
213. 9:53So, what's the natural instinct for a
214. 9:56farmer? He's going to want to close.
215. 9:58He's going to want to reduce his cost.
216. 10:02And instead, what if we can show them
217. 10:05light in a different way of if you did
218. 10:07try this,
219. 10:09this should get a better yield, a better
220. 10:10ROI, and thus you're going to make more
221. 10:12money. So, I see that I'm getting a one
222. 10:15minute warning. Okay, I'm going to go
223. 10:17real quick here. This is just um showing
224. 10:19our four row planters, two row zer
225. 10:21combines. This is where the data comes
226. 10:23from, the yield labs. It's very
227. 10:25important to us. Um this is the yield
228. 10:28optimizer. You can see the rankings.
229. 10:30It's very simple. We have every field in
230. 10:32the US. You drop a pin and we kick out
231. 10:35the answer. And our north star is G by
232. 10:38C, genetics by chemistry. We do all of
233. 10:42the seed. And now we've been doing our
234. 10:44testing, combining different chemistry
235. 10:46in order to get to what is the best
236. 10:48solution. And sometimes just getting
237. 10:50increasing yield is not the the right
238. 10:53goal. You want to make sure that you're
239. 10:54increasing the yield, but being
240. 10:56sensitive to what? Your cost and your
241. 10:59ROI.
242. 11:01The next thing and the last leg of that
243. 11:03chair is that yield guarantee.
244. 11:05Providing the ability to tell your
245. 11:08customer that if this does not work, I
246. 11:11got your back. That's what we do. So,
247. 11:15real quick, we do it um not by looking
248. 11:17at AP records. I come from the crop
249. 11:20insurance industry. Um we always judged
250. 11:23everything on the rolling 10-year
251. 11:24average. But what we actually do is we
252. 11:27ignore that and we say, "Let's go put
253. 11:30what we call our yield stations out
254. 11:31there and compare the treated to the
255. 11:33untreated." And that delta guarantee
256. 11:37between this new biological in the green
257. 11:40and the not in the red, we're going to
258. 11:42measure that difference in multiple
259. 11:43replications. And if the performance
260. 11:45comes in short, we write you a check. We
261. 11:48really want the performance to come in
262. 11:50great and you're going to get a strong
263. 11:52ROI.
264. 11:54So that's the key difference on our um
265. 11:56how we actually measure the results.
266. 12:00So uh together we provide the growers
267. 12:03that clarity and the financial
268. 12:04confidence to really unlock their yield
269. 12:07potential.
270. 12:10Again um if anyone has any questions I
271. 12:12can address them. Our booth is right
272. 12:14down on the entrance and we thank you
273. 12:16for your time.