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5,677
Our Lean Launchpad Journey
Then Now
Optimizing nutrients for
orchards using computer
vision
Crop counting for
specialty cr...
Alex Kolchinski Rachel Luo Sami Tellatin Jonathan Kuck Edward Silva
PhD Candidate,
Learning Sciences
& Tech Design
PhD Can...
Almond Board workshop in
Central Valley
1
2
3
4
5
6
7
8
9
10
AgEmerge: Growers are confident
in their current practices.
1
2
3
4
5
6
7
8
9
10
1
2
3
4
5
6
7
8
9
10
Almond crop count is important,
but farmers can play the market.
1. Specialty crop
farmers and/or
farm managers
2. Specialty crop
farmers with
perishable, multi-
harvest per-
season crops...
1
2
3
4
5
6
7
8
9
10
Berry farmers harvest every acre
3x per week, 8 months per year.
Largest global berry company in
the needs better forecasting.
“The biggest tech opportunities Driscoll’s sees are
automati...
1
2
3
4
5
6
7
8
9
10
Not all berry counting is desired equally,
and size of the farm/shipper matters.
Better crop counting can help avoid money
being ‘left on the table.’
1
2
3
4
5
6
7
8
9
10
“Last week alone, based on one f...
TAM of Crop Counting in Berries
Globally
● $15-60m per year
● Doesn’t include other specialty crops
(i.e. Processing tomat...
Zoom in and zoom out in parallel:
Specialty & Row Crops
Zoom Out & ExploreZoom In & Dominate
1
2
3
4
5
6
7
8
9
10
We start exploring bigger markets
Hypotheses: we can add
value with computer vision
for
● Plant breeding
● Winemaking
● Co...
0/4 winemakers could quantify revenue
benefit of yield prediction; costs low.
Yield prediction is a significant
problem fo...
World Ag Expo: More learning in one day
than in most other weeks!
1
2
3
4
5
6
7
8
9
10
Out of dozens of farmers we asked, none
said that better aerial data was a top need.
Nobody wants to pay for information!
...
But 6/6 corn and soy growers indicate
weeds either #1 concern or very important.
“Our biggest problem -
weeds!”
-Steve and...
A product vision emerges...
1
2
3
4
5
6
7
8
9
10
The robot:
● Autonomous
● Jets of fire, not herbicide
● Computer vision f...
And reception is very favorable
“A [non herbicide weeding robot]...
will be the ultimate gold standard greatest creation
i...
It looks feasible, too.
“A works-like prototype of the weed
burning robot will take $2-3000 to build”
-Dr. Andrew Gillies,...
Total and beachhead market sizes are
promising
Weeding market size (US):
● Conventional corn and soy: $40/acre *
180M acre...
2/2 organic farmers have already signed up
for the paid pilot at $20/acre.
You’re singing our song - sounds like a dream c...
1. Organic corn
and soy growers
2. Conventional
corn and soy
growers
1.Initially: direct sales
and support
2
4
1.Farmer an...
What is next
Crop counting as a beachhead
to Ai in specialty crops.
“Fire Roomba” for weeds;
Alex Full Time.
If you know a...
Thank you!!
V.1 Slides
Appendix/Extra
Slides are below this
slide
Clone market type
now focused on specialty crops. [not exclusively]
Week 8: 10 interviews this week. 114 total
Alex Kolchi...
Current Status
For large growers and distributors of berries & wine grapes, who
seek to optimize pricing via more accurate...
Who we talked to:
5 Agriculture technology experts | 1 VC in agtech |
1 Winemaker | 3 Agtech startup founders
What we expe...
Potential Partners
Forecasters Industry Associations
Why do we
need them?
Major influence on farmers prices
Event hosters,...
Potential Partners
7
8
1 3
45
1.Distributor/farmer
relationships.
2. Hardware for data
collection.
3. Software: crop counting.
4. Agricultura...
What we are trying to figure out before
class ends...
1. Build a list of exactly who would pay for more accurate crop coun...
AgAi: LLP Exploration Map
Weeks of LLP
PhysicalLevelofPlant-Data-Capture
Drone/ Satellite-
Level
Perspective
Plant-level p...
Appendix of past slides
Minimum
Viable
Product
v0.03
1. Interview actual in-
field berry/grape
forecasters
Next Steps: Before Next Class, We
Will...
2. Send
grower/shipper our...
1. Growers and distributors of continually-harvested produce experience high error rates in crop
count estimates.
2. Error...
And Finally, Make This Matrix Full...
Modified Wish List Driscolls California
Giant Berry
Farms
Naturipe Well-Pict Church
...
● Seek roboticists to help develop mechanisms to move camera through fields.
● Recruit Certified Crop Advisor/Forecaster i...
Key Resources & Partners
Physical ● [short term] Stanford Venture Studio
Software
● Cloud computing
● Machine learning lib...
Income Statement
2020 2021 2022
Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4
Active Acres 5000 7500 11250 16875 25312.5 37968.75 56...
Nonetheless, our main focus remains:
Crop Counting
Diagram of Crop Counting
Per acre crop
count of $35
Initial hardware
cost of $TBD
+
Amount saved/revenue
realized by Drisc...
Fundraising & Operations Plan
Q1 Q2 Q3 Q4
2019 2020 2021 2022
Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4
Cashreserves
5M
10M
20M
...
Next Steps: Before Next Class, We
Will...
2. Current Yield
Prediction Accuracy
1. Financial Model for
Our Potential
Busine...
One harvest per season per crop Multiple harvests per season per crop
Generally non-
perishable
product
i.e. time to marke...
LEARNING GOAL SCORE
R/Y/G
COMMENTS EXPLAINING YOUR SCORE AND/OR
WHAT YOU WILL CHANGE
1. Form hypotheses Past: Have created...
Input Suppliers
- Advisors, Agronomists, CCAs, PCAs
Landowners
Farm/Land Management Companies
Independent Advisors
Univers...
Customer Acq. Cost
Direct to Shipper
Maintenance2
$2.00 p/yr per
1000 acres
Estimate
Farm Trials1
$1500 p/1000
acres
$2500...
● Pending questions:
a. What could our technology do in
terms of reducing error rates?
b. Value added by AgAi per forecast...
Recurring Value
- Maintenance
- New insight into their data
- Cheaper the more you run the
technology
Berry Grower/Shipper...
One harvest per season per crop Multiple harvests per season per crop
Generally non-
perishable
product
i.e. time to marke...
Channels: Strawberry Produce Seller
Direct (B2B) Fixed Revenue +
Variable Revenue
= Life-Time Value
(LTV)
$TBD
Channel Par...
Our Value Proposition:
Increase revenue captured (by
optimizing price) and decrease labor
costs by counting crops that wil...
Gains Creators
● Reducing costs.
● Increasing yields
Pains
● Yield uncertainty.
● High labor cost
● Potential yield not
ca...
Products / Services
● Field crop
count/health
monitor
Pain Relievers
● Greater insight into
crop status
throughout season
...
% of farmers that say yes
If you knew exactly how many fruits/nuts
were on your trees at any point in the year
that you wa...
% of farmers that say yes
If you had perfect information about your soil
and plant moisture levels everywhere in your
spre...
% of farmers that say yes
Over the past 5 growing seasons, has the
amount you’ve spent on pest
identification and control ...
% of farmers that say yes
Over the past 5 growing seasons, would
you have been able to significantly save
costs if you had...
Past and present mascot
% of yield increase due to precision
fertilization or irrigation.
Find 5 real cost analysis/operation
budgets showcasing p...
Ask suppliers and salespeople of
precision fertilizer solutions for %
market share of almond farmers.
% of the people that...
% of farmers that express
dissatisfaction with the imprecision
of their yield estimates.
Survey 10 farmers about their
imp...
Competitor Leaf Diagram
General Competitive Area:
Precision agriculture that can predict
yield and then create direct fert...
Total Addressable Market, per year: $47.58M
(1.33M acres of almonds in California) * ( 119 avg. # of trees per acre) * ($0...
Clone market type,
now focused on specialty crops.
Week 2: 12 interviews this week. 25 total
Alex Kolchinski Rachel Luo Sa...
For large US farmers who seek to optimize input costs,
AgAi is software+hardware system that counts crops ahead of
harvest...
7
8
1. Specialty crop
farmers and/or farm
managers/operators
2. Certified Crop
Advisors (CCAs) &
agronomists in
specialty ...
Who we talked to:
7 Almond growers
2 AgTech founders (1 also a row crop farmer)
1 Soil sensor researcher
1 Pest consultant...
Gains Creators
● Reducing costs.
● Increasing yields
Pains
● Yield uncertainty.
● High labor cost
● Potential yield not
ca...
Products / Services
• Field crop count/health
monitor
Pain Relievers
• Greater insight into crop
status throughout season
...
Minimum
Viable
Product
v2.0
% of farmers that say yes
If you knew exactly how many fruits/nuts
were on your trees at any point in the year
that you wa...
% of farmers that say yes
If you had perfect information about your soil
and plant moisture levels everywhere in your
spre...
% of farmers that say yes
Over the past 5 growing seasons, has the
amount you’ve spent on pest
identification and control ...
% of farmers that say yes
Over the past 5 growing seasons, would
you have been able to significantly save
costs if you had...
Next Steps: Before Next Class, We
Will...
Test these hypotheses:
• Real-time crop count would allow for significantly incr...
Appendix of past slides
% of yield increase due to precision
fertilization or irrigation.
Find 5 real cost analysis/operation
budgets showcasing p...
Ask suppliers and salespeople of
precision fertilizer solutions for %
market share of almond farmers.
% of the people that...
% of farmers that express
dissatisfaction with the imprecision
of their yield estimates.
Survey 10 farmers about their
imp...
Competitor Leaf Diagram
General Competitive Area:
Precision agriculture that can predict
yield and then create direct fert...
Total Addressable Market, per year: $47.58M
(1.33M acres of almonds in California) * ( 119 avg. # of trees per acre) * ($0...
AgAI engr 245 lean launchpad stanford 2019
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AgAI engr 245 lean launchpad stanford 2019

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AgAI engr 245 lean launchpad stanford 2019

  1. 5,677
  2. Our Lean Launchpad Journey Then Now Optimizing nutrients for orchards using computer vision Crop counting for specialty crops AND Precision weeding for corn and soy
  3. Alex Kolchinski Rachel Luo Sami Tellatin Jonathan Kuck Edward Silva PhD Candidate, Learning Sciences & Tech Design PhD Candidate, EE Stanford Vision Lab, AI Lab MBA 20’ Stanford GSB PhD Candidate, CS Stanford AI Lab MBA 20’ Stanford GSB Helping farmers know more of what they grow Mentor: Todd Basche 129 Interviews Total
  4. Almond Board workshop in Central Valley 1 2 3 4 5 6 7 8 9 10
  5. AgEmerge: Growers are confident in their current practices. 1 2 3 4 5 6 7 8 9 10
  6. 1 2 3 4 5 6 7 8 9 10 Almond crop count is important, but farmers can play the market.
  7. 1. Specialty crop farmers and/or farm managers 2. Specialty crop farmers with perishable, multi- harvest per- season crops. 3. Specialty crop farmers with non-perishable, single-harvest per season crops. 1.Trust: Ongoing data analysis that produces reliable, usable data. 2.Insight: Analysis tools for strategic management. 2 4 1.Farmer relationships. 2.Proprietary hardware for data collection. 3.Proprietary software for crop counting. 4.Agricultural+AI SME. 6 1.Sell analysis via platform for a subscription OR 2.Charge a % of revenues (to be proved out) 1.Development costs of technology, including testing. 2.Hardware and prototyping costs. 3.Customer acquisition costs, especially upfront. 1.Reduced costs through targeted water/fertilizer application). 2.Increase captured revenue through optimized pricing. 3.Reduce labor costs previously needed to count/estimate crop count. 1.Development of AI for image recog. & counting of crops 2. Analysis of crop count for price optimizing. 3.On-demand data collection. 1.USDA and public university extension (i.e. UC Davis Extension). 2.Certified Crop Advisors (example). 3.Specialty crop farmers* 4.Industry Associations (i.e. Almond Board of California). 1.Direct (trade shows) 2. Through crop advisory board workshops/monthly grower meetings 3. Top down from farm contract holders17 8 3 5 9
  8. 1 2 3 4 5 6 7 8 9 10 Berry farmers harvest every acre 3x per week, 8 months per year.
  9. Largest global berry company in the needs better forecasting. “The biggest tech opportunities Driscoll’s sees are automatic harvesting and yield prediction. Yield forecasting right now is done manually and is very speculative and error prone. Small errors can shift large amounts of revenue.” -Michael Christensen, R&D Director, Driscoll's 1 2 3 4 5 6 7 8 9 10
  10. 1 2 3 4 5 6 7 8 9 10 Not all berry counting is desired equally, and size of the farm/shipper matters.
  11. Better crop counting can help avoid money being ‘left on the table.’ 1 2 3 4 5 6 7 8 9 10 “Last week alone, based on one forecast, we lost $20k on a 100 acre farm because we manually overestimated yield after a bad storm. Had we estimated correctly, it would have been a different story.” ~David Lawrence, President, Red Blossom Berries
  12. TAM of Crop Counting in Berries Globally ● $15-60m per year ● Doesn’t include other specialty crops (i.e. Processing tomatoes: 12m acres) Strategy: ● Get a prototype into the field. ● Win for this customer. ● Iterate, then expand to new markets. 12/16 Berry Interviews said yes to crop counting, including 4 biggest companies. Zoom in & dominate for your customer in a smaller market first, then expand. 1 2 3 4 5 6 7 8 9 1 2 3 4 5 6 7 8 9 10
  13. Zoom in and zoom out in parallel: Specialty & Row Crops Zoom Out & ExploreZoom In & Dominate 1 2 3 4 5 6 7 8 9 10
  14. We start exploring bigger markets Hypotheses: we can add value with computer vision for ● Plant breeding ● Winemaking ● Corn and soy (aerial/satellite imaging?) 1 2 3 4 5 6 7 8 9 10
  15. 0/4 winemakers could quantify revenue benefit of yield prediction; costs low. Yield prediction is a significant problem for Foley [a major winery]...but only spending $50,000/yr on predictions. -Al Wagner, VP Vineyards, Foley 1 2 3 4 5 6 7 8 9 10
  16. World Ag Expo: More learning in one day than in most other weeks! 1 2 3 4 5 6 7 8 9 10
  17. Out of dozens of farmers we asked, none said that better aerial data was a top need. Nobody wants to pay for information! -Dennis Donohue: Innovation Lead, Western Growers 1 2 3 4 5 6 7 8 9 10
  18. But 6/6 corn and soy growers indicate weeds either #1 concern or very important. “Our biggest problem - weeds!” -Steve and Connie Swan, Conventional Corn and soy farmers 1 2 3 4 5 6 7 8 9 10
  19. A product vision emerges... 1 2 3 4 5 6 7 8 9 10 The robot: ● Autonomous ● Jets of fire, not herbicide ● Computer vision for targeting ● Cameras and nozzles mounted on vertical bars to penetrate below leaf canopy
  20. And reception is very favorable “A [non herbicide weeding robot]... will be the ultimate gold standard greatest creation in production agriculture that we’ll ever see” -Justin Bruch, AgFunder Board Chairman; Major corn and soy grower 1 2 3 4 5 6 7 8 9 10
  21. It looks feasible, too. “A works-like prototype of the weed burning robot will take $2-3000 to build” -Dr. Andrew Gillies, roboticist 1 2 3 4 5 6 7 8 9 10 Autonomy on a farm is a much easier problem than on streets -Russell Kaplan, Sr. Research Scientist at Testla Autopilot
  22. Total and beachhead market sizes are promising Weeding market size (US): ● Conventional corn and soy: $40/acre * 180M acres = $7.2B/yr ● Organic corn and soy: $150/acre * 1M acres = $150M/yr. a. Growing exponentially! 1 2 3 4 5 6 7 8 9 10
  23. 2/2 organic farmers have already signed up for the paid pilot at $20/acre. You’re singing our song - sounds like a dream come true! Sign me up for the paid pilot! -Jim Wirtz, Organic Corn and Soy Grower (6000 acres) 1 2 3 4 5 6 7 8 9 10
  24. 1. Organic corn and soy growers 2. Conventional corn and soy growers 1.Initially: direct sales and support 2 4 1.Farmer and weed control specialist relationships. 2.Proprietary hardware 3.Proprietary software 6 1.Sell robots per-unit and charge for service OR 2.Charge per acre as a service 1.Development costs of technology, including testing. 2.Hardware and prototyping costs. 3.Customer acquisition costs, especially upfront. 1.Reduced weeding cost 2.“Automatic organic” 1.Hardware platform development and manufacturing 2. AI software development 3.Farmer facing sales, support and testing 1.Manufacturers 2.Ag supply dealerships 3.Weed control specialists 4.University test farms, field days etc. 1.Direct sales and trade shows 2. Ag programs at universities 3.Weed control specialists 17 8 3 5 9
  25. What is next Crop counting as a beachhead to Ai in specialty crops. “Fire Roomba” for weeds; Alex Full Time. If you know a good roboticist/mechanical engineer, please reach out! yakolch@stanford.edu
  26. Thank you!!
  27. V.1 Slides
  28. Appendix/Extra Slides are below this slide
  29. Clone market type now focused on specialty crops. [not exclusively] Week 8: 10 interviews this week. 114 total Alex Kolchinski Rachel Luo Sami Tellatin Jonathan Kuck Edward Silva Picker Hacker Hustler Hacker Hustler PhD Candidate, Learning Sciences & Tech Design PhD Candidate, EE Stanford Vision Lab, Stanford AI Lab MBA1, Stanford GSB PhD Candidate, CS Stanford AI Lab MBA1, Stanford GSB Helping farmers know more of what they grow Mentor: Todd Basche
  30. Current Status For large growers and distributors of berries & wine grapes, who seek to optimize pricing via more accurate and lower cost forecasts, AgAi is a computer vision system that counts crops to determine how many will be ready for each sales cycle at multiple periods before harvest. Unlike our competitors, we don’t guess, we count! Leading crops of focus: wine grapes, berries, lettuce, broccoli
  31. Who we talked to: 5 Agriculture technology experts | 1 VC in agtech | 1 Winemaker | 3 Agtech startup founders What we expected: Satellite imagery would have limited uses in providing farmers interventions and not just more information, which they are overloaded with. What we learned: Satellite images are not quite good enough today to provide much info beyond crop ID and some yield prediction for some crops. However, satellite images seem to be improving rather dramatically, to the point where they may be challenging the need for sensors. Robotics is the most promising avenue. Interviews & Insights “Wherever there is a field trial in ag, there is the need for more efficient expert eyes. If computer vision could help with this, we could do more with less.” --Jonathan Diniz Manager, TS&L Seeds “Farmers are overloaded with information and data. You must make it useful and tied to an ROI.” -- Dennis Donahue, Leader of Western Growers Innovation
  32. Potential Partners Forecasters Industry Associations Why do we need them? Major influence on farmers prices Event hosters, want to showcase products at their events Why might they need us? Allow them to be more efficient/accurate They provide growers data; we could make that more accurate Risks May see our technology as adversarial Lack of trust Costs Initial upfront costs for hardware, plus processing costs Buying booth space at events
  33. Potential Partners
  34. 7 8 1 3 45 1.Distributor/farmer relationships. 2. Hardware for data collection. 3. Software: crop counting. 4. Agricultural+AI SME. 9 1. Development costs of technology, including testing. 2. Hardware and prototyping costs. 3. Customer acquisition costs, especially upfront. 4. Operating costs to continuously collect and process data. 1.Development of AI platform for image recog. & counting of crops 2.Analysis of crop count for price optimization. 3.On-demand data collection. 1. USDA and public university extension (i.e. UC Davis Extension). 2. Certified Crop Advisors (example). 3. Specialty crop farmers* 4. Industry Associations (i.e. California Strawberry Commission). 5. Technical partnerships (i.e. robotics and agricultural data) 1. Provide an in-field service of computer vision=crop count 2. Sell analysis via platform for a subscription 3. Charge a % of revenues gained (TBD) 1.Direct (trade shows) 2.Crop-specific advisory board workshops/ grower meetings 3.Top down from farm contract holders i.e. distributors 1. Trust: Ongoing data analysis that produces reliable, usable data. 2. Solution= easy AgAi Week [5] 1. Berry distributors who need to set prices before harvest time. 2. Berry farmers with perishable, multi- harvests-per - season crops. 3. Vegetable distributor with per unit crops (i.e. lettuce and broccoli) that harvest all at once. 1.Increase captured- revenue through optimized pricing. 2.Increase quality by more optimal harvesting time. 3.Reduce labor costs previously needed to count/estimate crop count.
  35. What we are trying to figure out before class ends... 1. Build a list of exactly who would pay for more accurate crop counting and why 2. Can satellites imagery do what we want to do cheaper/easier and would people pay for that from us 3. Which 3 competitors offer the closest value proposition, and what do at least 3 current users think about it. 4. How much value add is there to an autonomous scout+smart sprayer? 5. How hard will it be to design and build an autonomous scout+smart sprayer?
  36. AgAi: LLP Exploration Map Weeks of LLP PhysicalLevelofPlant-Data-Capture Drone/ Satellite- Level Perspective Plant-level perspective PotentialMarketSize + -
  37. Appendix of past slides
  38. Minimum Viable Product v0.03
  39. 1. Interview actual in- field berry/grape forecasters Next Steps: Before Next Class, We Will... 2. Send grower/shipper our understanding of their ROI on better forecasting.
  40. 1. Growers and distributors of continually-harvested produce experience high error rates in crop count estimates. 2. Errors in crop count estimates cause errors in yield prediction, which have a significant and measurable economic impact for growers and distributors of continually-harvested produce. 3. Large business size, short produce shelf life, and continuously harvested nature of a crop are the key factors in making precise crop counting compelling to growers and distributors. 4. Growers and distributors of continually harvested produce incur significant and measurable labor costs when making crop count estimates. 5. We could build a system at reasonable cost that significantly outperforms the current approaches distributors/growers of continuously harvested produce use for making crop count estimates. 6. Wine grape growers would benefit from a pricing standpoint if they had more accurate yield counts. Next Week: Test These Hypotheses...
  41. And Finally, Make This Matrix Full... Modified Wish List Driscolls California Giant Berry Farms Naturipe Well-Pict Church Brothers Greens Babe Farming Mazzi Farming Veg Crop Company X Director, Technical Services, Global Research and Development x x X Director of Forecasting x x Forecasting Analyst x In-Field Forecaster Sales Person Shippers (if not the same company) x x x Growers (x5) xxxx xxx
  42. ● Seek roboticists to help develop mechanisms to move camera through fields. ● Recruit Certified Crop Advisor/Forecaster in our specific crop as an advisor, have them lead sales team development. ● Development of AI platform for image recog. & counting of crops. ● Analysis of crop count for price optimization. ● On-demand data collection (unless partnering with imagery companies). Key Activities Product Development Customer Development & Selling ● Create sales channel with forecasting, pricing, harvesting teams [need to decide on one]. ● Build pilots to prove out the concept with shippers/growers. ● Create marketing campaign around more accurate forecasting insight. Internal Capacity Building ● Early sales from initial customers. ● Pre-seed funding to prove this out to different crops.Fundraising
  43. Key Resources & Partners Physical ● [short term] Stanford Venture Studio Software ● Cloud computing ● Machine learning libraries Human ● Machine learning researchers and engineers ● Potentially roboticists/mechanical engineers IP ● Brand/trademark/logo ● Machine learning models and data Partners ● Ag dealerships for distribution, support and repairs
  44. Income Statement 2020 2021 2022 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Active Acres 5000 7500 11250 16875 25312.5 37968.75 56953.125 85429.6875 128144.5313 192216.7969 288325.1953 288325.1953 New Acres 0 2500 3750 5625 8437.5 12656.25 18984.375 28476.5625 42714.84375 64072.26563 96108.39844 0 Forecasting Fee p/acre $35 $35 $35 $35 $35 $35 $35 $35 $35 $35 $35 $35 Gross Revenue $350,000 $525,000 $787,500 $1,181,250 $1,771,875 $2,657,813 $3,986,719 $5,980,078 $8,970,117 $13,455,176 $20,182,764 $20,182,764 Net Revenue $350,000 $525,000 $787,500 $1,181,250 $1,771,875 $2,657,813 $3,986,719 $5,980,078 $8,970,117 $13,455,176 $20,182,764 $20,182,764 Product Dev Costs $250,000 $250,000 $250,000 $250,000 $250,000 $250,000 $250,000 $250,000 $250,000 $250,000 $250,000 $250,000 Operating Costs $45,000 $54,000 $64,800 $77,760 $93,312 $111,974 $134,369 $161,243 $193,492 $232,190 $278,628 $334,354 Cash Burn -$295,000 -$304,000 -$314,800 -$327,760 -$343,312 -$361,974 -$384,369 -$411,243 -$443,492 -$482,190 -$528,628 -$584,354 Cash Balance $645,000 $829,000 $1,102,300 $1,509,010 $2,115,187 $3,019,787 $4,371,088 $6,391,321 $9,413,609 $13,937,366 $20,711,392 $20,767,117 Assumptions: Starting Acres 5000 Growth Rate 50% Number of forecasts per yr p/acre 2 Operation cost growth q/q 20% Price per acre $35
  45. Nonetheless, our main focus remains: Crop Counting
  46. Diagram of Crop Counting Per acre crop count of $35 Initial hardware cost of $TBD + Amount saved/revenue realized by Driscoll’s: TBD
  47. Fundraising & Operations Plan Q1 Q2 Q3 Q4 2019 2020 2021 2022 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Cashreserves 5M 10M 20M 30M OperationsSoftware/ Hardware development Lean Launch pad Build hardware prototype Test hardware & software prototype Disc. PMF TBD Analyze Results Acquire training set for ML Field test software Partnerships with large shippers, pilot
  48. Next Steps: Before Next Class, We Will... 2. Current Yield Prediction Accuracy 1. Financial Model for Our Potential Business Model 3. Evaluate opportunity size of phenotyping
  49. One harvest per season per crop Multiple harvests per season per crop Generally non- perishable product i.e. time to market is less crucial ● Almonds ● Corn ● Processing tomatoes ● Rice ● Raisins ● Wine grape growers ● Pomegranates ● Cannabis Generally perishable product i.e. time to market is crucial ● Bell peppers ● Stone fruit ● Potatoes/onions ● Berries ● Broccoli ● Lettuce Low willingness to pay High willingness to pay BOLD=interviewed Last week on AgAi...Revisit Customer Segments: Specialty Crop Farmers Where we are exploring: Crop Curious: ● Corn ● Cannabis ● Soy ● Wine Grapes Task Curious: ● Phenotyping ● QA ● BRIX counting
  50. LEARNING GOAL SCORE R/Y/G COMMENTS EXPLAINING YOUR SCORE AND/OR WHAT YOU WILL CHANGE 1. Form hypotheses Past: Have created a wide range of hypotheses Future: Will be more focused 2. Design and conduct customer, partner, and supplier interviews Past: Quantity has been high Future: Moving towards conducting interviews in a repeatable, scientific manner. 3. Design and build minimum viable products (MVPs) Past: Iterated on MVPs that illustrate the concept Future: Building functional demos 4. Design and run experiments Past: During need finding, interviews resembled conversations more than experiments Future: Will run repeatable experiments as we move past need finding 5. Determine if hypotheses are true or false based on interview and experimental results Past: Have ruled out hypotheses using interview data Future: Will utilize experimental results 6. Work effectively in teams under pressure Past: Teamwork has been effective 7. Communicate your progress in weekly presentations Past: Team communication through structured and informal presentations has been effective 8. Form new hypotheses based on learning Past: Have created new hypotheses after invalidating past hypotheses 9. Pivot (adapt strategy) based on new data Past: Pivoted from almonds to berries 10. Achieve (or know you have not achieved) product-market fit Past: Have successfully identified the lack of product-market fit Future: Are working to achieve product-market fit Learning Goals: Midpoint Self-Assessment
  51. Input Suppliers - Advisors, Agronomists, CCAs, PCAs Landowners Farm/Land Management Companies Independent Advisors University Extension Employees USDA Field Staff FARMERS GROWERS OPERATORS PRODUCERS Advisors, Input Suppliers Information, Land, Inputs Aggregators, Processors & Distributors Retail, Restaurants, Consumers Large commodity traders, like Cargill and ADM, who often also process and distribute goods from farmers For strawberries, Driscoll is a major aggregator and distributor Aggregators/Processors also can be input suppliers (like Cargill) Capital Providers Banks Farm Credit Agencies Crop Insurance Providers USDA grants and subsidies Some farmers do sell direct to restaurants or consumers; usually these are players in local/regional economies
  52. Customer Acq. Cost Direct to Shipper Maintenance2 $2.00 p/yr per 1000 acres Estimate Farm Trials1 $1500 p/1000 acres $2500 p/1000 acres Customer Acquisition Cost Annual Subscription Pay per acre per year for 1000 acre farm A. YEARLY REVENUE at $25 per acre free p/yr $2500 B. YEARLY CHURN 2% C. CAC $1500 D. GROSS LTV A*(1-B) / (B) $122,500 E NET LTV GROSS LTV - CAC $121,000 Customer LTV ● Pending questions: ○ Churn rate for agtech? ○ CAC for farm trials for new agtech
  53. ● Pending questions: a. What could our technology do in terms of reducing error rates? b. Value added by AgAi per forecast? c. Costs saved by AgAi per forecast? d. The differences of strawberry value saved/created vs. other berries? e. Other benefits to making forecasters more efficient/effective? Unit Economics for Forecasting (in progress) A. Cost of labor per acre to forecast per year $50 B. Berry acres in the U.S. 289,000 C. Current error rates for Driscoll’s Forecasters +30% D. Acres “overseen” per forecaster ~1000 E. Value added by AgAi per forecast TBD F. Cost saved by AgAi per forecast TBD
  54. Recurring Value - Maintenance - New insight into their data - Cheaper the more you run the technology Berry Grower/Shipper Funnel Workshops and Shows - Farm shows - Berry workshops - Industry associations Upsell - Provide PCA services - Sell additional tools Referrals - PCA/CCAs - Shippers to growers Acquire Activate Keep Customers Up-Sell Next-Sell KEEP Cross-Sell Referrals GROWGET
  55. One harvest per season per crop Multiple harvests per season per crop Generally non- perishable product i.e. time to market is less crucial ● Almonds ● Corn ● Processing tomatoes ● Rice ● Raisins ● Wine grape growers ● Pomegranates ● Cannabis Generally perishable product i.e. time to market is crucial ● Bell peppers ● Stone fruit ● Potatoes/onions ● Berries ● Broccoli ● Lettuce Low willingness to pay High willingness to pay Customer Segmentation: Specialty Crop Farmers [hypothesis] BOLD=interviewed
  56. Channels: Strawberry Produce Seller Direct (B2B) Fixed Revenue + Variable Revenue = Life-Time Value (LTV) $TBD Channel Partner Interests: ● Working with Pest Control/Certified Crop Advisors ● Working directly with shippers/sellers/traders of product Potential Revenue Model Fixed Revenue Variable Revenue Current variable costs to forecast: $30/ppl/hr x 10 hr/ppl/wk x 5 ppl 1% increased revenue from being able to sell more produce at higher pre-committed prices Total: $1500 per week x 7 months = $42k p/yr Total: TBD $XYZ Variable costs based on size of farm $ABC Testing and farm trials $XYZ Profit
  57. Our Value Proposition: Increase revenue captured (by optimizing price) and decrease labor costs by counting crops that will be ripe up to 6 weeks before harvest. Customer #1: Produce Seller 1. Customer ​Archetype - Medium to large strawberry seller/distributor (US based) - Needs to set price in advance of each harvest to sell, but not oversell, each crop 2. Workflow ​Today Plant strawberry → Monitor crop size and ripening approximately with humans → 6 weeks before harvest, sign contracts for ~50% of crop → Continue to monitor crop → Sell more in 3 weeks→ Monitor → Sell more in 1 week → Harvest and sell any surplus (or deal with undersupply!) 3. Current Solutions for Crop Counts - Human labor counts small sample of field, extrapolates - Use historical data to predict strawberry count
  58. Gains Creators ● Reducing costs. ● Increasing yields Pains ● Yield uncertainty. ● High labor cost ● Potential yield not captured. Customer Jobs ● Decide how much fertilizer/irrigation to apply. ● Plan their expenses 7-9 months ahead based on the potential of yield. ● Stay in the black with unpredictable cash flow. ● Develop contracts with buyers based on projected yields Products / Services ● Crop counting for yield prediction, and cost reduction. ● Providing insight on how much to irrigate/fertilize. Value Proposition: Customer Segment: Farmers Value Proposition Canvas - Farmers Gains ● Staying profitable. ● Visibility into crop health to get ahead of issues ● Reducing input costs Pain Relievers ● Providing yield insight as early as possible. ● Reducing operational costs.
  59. Products / Services ● Field crop count/health monitor Pain Relievers ● Greater insight into crop status throughout season Gains Creators ● Better data for optimizing agricultural decisions ● Better data for optimizing marketing decisions Value Proposition: Customer Segment: Agronomists Pains ● Accuracy is difficult to obtain (in yield estimates and nutrient recommendations), leading to uncertainty and risk Gains ● Advice is accurate and reliable ● Clients come back and refer ● Clients trust you Customer Jobs ● Advising farmer clients on nutrient application amounts and timing throughout the season Value Proposition Canvas - Agronomists
  60. % of farmers that say yes If you knew exactly how many fruits/nuts were on your trees at any point in the year that you wanted, would your operations costs change? Test 001: Crop Count HYPOTHESIS OUR TEST METRIC WE’RE RIGHT IF Real-time crop count would allow for significantly increased optimization in operations costs. >50% say yes RESULT TBD NOW WHAT [1] TBD [2] TBD Test Card ONGOING
  61. % of farmers that say yes If you had perfect information about your soil and plant moisture levels everywhere in your spread all of last growing season, would you have saved money on water/ increased yield? Test 002: Crop Count HYPOTHESIS OUR TEST METRIC WE’RE RIGHT IF The limiting factor in precision irrigation/fertilizer is the right hardware >50% say yes RESULT TBD NOW WHAT [1] TBD [2] TBD Test Card ONGOING
  62. % of farmers that say yes Over the past 5 growing seasons, has the amount you’ve spent on pest identification and control been a major cost for you? Test 003: Pest Control HYPOTHESIS OUR TEST METRIC WE’RE RIGHT IF Farmers are currently experiencing high costs from labor of identifying pests and/or controlling them. >50% say yes RESULT TBD NOW WHAT [1] TBD [2] TBD Test Card ONGOING
  63. % of farmers that say yes Over the past 5 growing seasons, would you have been able to significantly save costs if you had real-time maps of tissue sample data over your entire spread? Test 004: Tissue sampling HYPOTHESIS OUR TEST METRIC WE’RE RIGHT IF Farmers could significantly improve their operations with data from granular, fast tissue sampling. >50% say yes RESULT TBD NOW WHAT [1] TBD [2] TBD Test Card ONGOING
  64. Past and present mascot
  65. % of yield increase due to precision fertilization or irrigation. Find 5 real cost analysis/operation budgets showcasing precision fert./irrigation has led to more yield. Test 001: Compelling Value Prop. HYPOTHESIS OUR TEST METRIC Perfectly targeted irrigation/ fertilization would increase yields/ decrease costs enough. WE’RE RIGHT IF Growers see average increase in yield > X% per acre (X is TBD) Test Card RESULT Haven’t been able to find those cost analysis of precision irrigation/fertilization. NOW WHAT [1] Reach out to precision fertilizer sales people. [2] Reach out to hardware manufacturers of precision irrigation. ONGOING
  66. Ask suppliers and salespeople of precision fertilizer solutions for % market share of almond farmers. % of the people that tell us that >75% of their customers do precision fertilizer through irrigation hardware Test 002: Precision Irrigation HYPOTHESIS OUR TEST METRIC WE’RE RIGHT IF Precision fertilizer is primarily done by precision irrigation systems. >75% tell us that >75% of their customers use irrigation systems for precision fertilizer RESULT Depends on crop! Row crops use variable rate spreaders, many specialty crops use fertigation NOW WHAT [1] TBD [2] TBD Test Card ONGOING
  67. % of farmers that express dissatisfaction with the imprecision of their yield estimates. Survey 10 farmers about their impression of their own yield prediction process. Test 003: Yield Estimation HYPOTHESIS OUR TEST METRIC WE’RE RIGHT IF Yield estimation would allow for significantly increased optimization in operations costs. >50% are dissatisfied RESULT Asked 8 farmers NOW WHAT [1] TBD [2] TBD Test Card ONGOING
  68. Competitor Leaf Diagram General Competitive Area: Precision agriculture that can predict yield and then create direct fertilizer and irrigation optimization opportunities for farmers. AgAi
  69. Total Addressable Market, per year: $47.58M (1.33M acres of almonds in California) * ( 119 avg. # of trees per acre) * ($0.10 per tree) * (3 “fruit counts” per year) Served Available Market, per year: $37.98M (80% of 1.33M acres of almonds comfortable actually use demand based irrigation, proxy for being open to new yield prediction technology) * ( 119 avg. # of trees per acre) * ($0.10 per tree) * (3 “fruit counts” per year) Target Market, per year: $8.73M 23% of the California almond acreage, which is self-opted into California Almond Sustainability Program, which we use as a proxy for the target market initially. Y1-Y3 Revenue: $357K, $1.43M, $3.57M Estimating $0.10 per tree * 119 trees per acre * 3x “fruit counts” a year * subscribed acreage (10,000; 40,000; 100,000) Market Size Sources: USDA NASS Almond Board 1 Almond Board 2
  70. Clone market type, now focused on specialty crops. Week 2: 12 interviews this week. 25 total Alex Kolchinski Rachel Luo Sami Tellatin Jonathan Kuck Edward Silva Picker Hacker Hustler Hacker Hustler PhD Candidate, Learning Sciences & Tech Design PhD Candidate, EE Stanford Vision Lab, Stanford AI Lab MBA1, Stanford GSB PhD Candidate, CS Stanford AI Lab MBA1, Stanford GSB Helping farmers know more of what they grow
  71. For large US farmers who seek to optimize input costs, AgAi is software+hardware system that counts crops ahead of harvest, allowing farmers to adjust fertilizer needs in real-time and make important marketing decisions heading into harvest, thus decreasing costs and increasing revenue. Unlike our competitors, we provide plant level data that farmers can act on to reduce costs and uncertainty. Current Status
  72. 7 8 1. Specialty crop farmers and/or farm managers/operators 2. Certified Crop Advisors (CCAs) & agronomists in specialty crops in the U.S. 1.Trust: Ongoing data analysis and precise recommendations for farmers. 2.Insight: Analysis tools for strategic management to increase value as a Certified Crop Advisor. 2 1.Direct (trade shows) 2.Through crop-specific advisory board workshops/monthly grower meetings 3.Through existing agrochemical/fertilizer sales channels1 3 45 1.Farmer relationships. 2.Proprietary hardware for data collection. 3.Proprietary software for crop counting. 4.Agricultural+AI SME. 6 9 1.Sell analysis via platform for a subscription/per usage fee.1.Development costs of technology, including testing. 2.Hardware and prototyping costs. 3.Customer acquisition costs, especially upfront. 1.USDA and public university extension (i.e. UC Davis Extension). WHY: To evangelize and validate tech to farmers. 2.Certified Crop Advisors (example). WHY: To evangelize, as they are in direct communication with farmer buying decisions. 3.Specialty crop farmers* WHY: Primary end user, potential buyer. 4.Industry Associations (i.e. Almond Board of California). WHY: To evangelize and validate technology to farmers. AgAi Week [2] 1.[gtm] Development of AI platform for image recog. & counting of crops 2.[on-going] Analysis of crop growth trends for farm owners/ managers 3.[on-going] On-demand data collection. 1.Reduced costs through targeted water/fertilizer application). 2.Increased revenue through increased yield from optimized fertilizer, and other tests. 3.Increased revenue from refined harvest screening and QA (esp. for tomatoes). 4.Increased revenue through increased quality of insight of a farmer’s field, leading to more targeted, higher-return marketing efforts and more referrals (esp. in a word-of-mouth industry).
  73. Who we talked to: 7 Almond growers 2 AgTech founders (1 also a row crop farmer) 1 Soil sensor researcher 1 Pest consultant 1 Industry-wide board member What we expected: Real-time crop count would allow for increased optimization in operations costs. What we learned: Research proves that the technology exists to accurately count fruits as they grow, but adoption is seemingly scarce. Crop counting will benefit farmers’ marketing efforts as well as their cost reduction efforts. Water supply (irrigation) remains the most pressing issue for almond growers--few solutions are provided by existing firms. Real-time crop counting would “help farmers make marketing and nutrient decisions.” - Almond Grower Interviews & Insights
  74. Gains Creators ● Reducing costs. ● Increasing yields Pains ● Yield uncertainty. ● High labor cost ● Potential yield not captured. Customer Jobs ● Decide how much fertilizer/irrigation to apply. ● Plan their expenses 7-9 months ahead based on the potential of yield. ● Stay in the black with unpredictable cash flow. ● Develop contracts with buyers based on projected yields Products / Services ● Crop counting for yield prediction, and cost reduction. ● Providing insight on how much to irrigate/fertilize. Value Proposition: Customer Segment: Farmers Value Proposition Canvas - Farmers Gains ● Staying profitable. ● Visibility into crop health to get ahead of issues ● Reducing input costs Pain Relievers ● Providing yield insight as early as possible. ● Reducing operational costs.
  75. Products / Services • Field crop count/health monitor Pain Relievers • Greater insight into crop status throughout season Gains Creators • Better data for optimizing agricultural decisions • Better data for optimizing marketing decisions Value Proposition: _______ Customer Segment: Agronomists Pains ● Accuracy is difficult to obtain (in yield estimates and nutrient recommendations), leading to uncertainty and risk Gains ● Advice is accurate and reliable ● Clients come back and refer ● Clients trust you Customer Jobs • Advising farmer clients on nutrient application amounts and timing throughout the season Value Proposition Canvas - Agronomists
  76. Minimum Viable Product v2.0
  77. % of farmers that say yes If you knew exactly how many fruits/nuts were on your trees at any point in the year that you wanted, would your operations costs change? Test 001: Crop Count HYPOTHESIS OUR TEST METRIC WE’RE RIGHT IF Real-time crop count would allow for significantly increased optimization in operations costs. >50% say yes RESULT TBD NOW WHAT [1] TBD [2] TBD Test Card ONGOING
  78. % of farmers that say yes If you had perfect information about your soil and plant moisture levels everywhere in your spread all of last growing season, would you have saved money on water/ increased yield? Test 002: Crop Count HYPOTHESIS OUR TEST METRIC WE’RE RIGHT IF The limiting factor in precision irrigation/fertilizer is the right hardware >50% say yes RESULT TBD NOW WHAT [1] TBD [2] TBD Test Card ONGOING
  79. % of farmers that say yes Over the past 5 growing seasons, has the amount you’ve spent on pest identification and control been a major cost for you? Test 003: Pest Control HYPOTHESIS OUR TEST METRIC WE’RE RIGHT IF Farmers are currently experiencing high costs from labor of identifying pests and/or controlling them. >50% say yes RESULT TBD NOW WHAT [1] TBD [2] TBD Test Card ONGOING
  80. % of farmers that say yes Over the past 5 growing seasons, would you have been able to significantly save costs if you had real-time maps of tissue sample data over your entire spread? Test 004: Tissue sampling HYPOTHESIS OUR TEST METRIC WE’RE RIGHT IF Farmers could significantly improve their operations with data from granular, fast tissue sampling. >50% say yes RESULT TBD NOW WHAT [1] TBD [2] TBD Test Card ONGOING
  81. Next Steps: Before Next Class, We Will... Test these hypotheses: • Real-time crop count would allow for significantly increased optimization in operations costs. • The limiting factor in precision irrigation/fertilizer is the right hardware -- the information piece is easy to obtain while the action/hardware piece is the bottleneck. • Farmers are currently experiencing high costs from labor of identifying pests and/or controlling them. • Farmers could significantly improve their bottom line by optimizing operations with data from granular, fast tissue sampling. Create an “MVP” to show customers: • Fake images and/or video to show: – Turning an image of a tree/trees into a count of fruits/nuts – A map showing crop counts, nutrition/pest status over a field
  82. Appendix of past slides
  83. % of yield increase due to precision fertilization or irrigation. Find 5 real cost analysis/operation budgets showcasing precision fert./irrigation has led to more yield. Test 001: Compelling Value Prop. HYPOTHESIS OUR TEST METRIC Perfectly targeted irrigation/ fertilization would increase yields/ decrease costs enough. WE’RE RIGHT IF Growers see average increase in yield > X% per acre (X is TBD) Test Card RESULT Haven’t been able to find those cost analysis of precision irrigation/fertilization. NOW WHAT [1] Reach out to precision fertilizer sales people. [2] Reach out to hardware manufacturers of precision irrigation. ONGOING
  84. Ask suppliers and salespeople of precision fertilizer solutions for % market share of almond farmers. % of the people that tell us that >75% of their customers do precision fertilizer through irrigation hardware Test 002: Precision Irrigation HYPOTHESIS OUR TEST METRIC WE’RE RIGHT IF Precision fertilizer is primarily done by precision irrigation systems. >75% tell us that >75% of their customers use irrigation systems for precision fertilizer RESULT Depends on crop! Row crops use variable rate spreaders, many specialty crops use fertigation NOW WHAT [1] TBD [2] TBD Test Card ONGOING
  85. % of farmers that express dissatisfaction with the imprecision of their yield estimates. Survey 10 farmers about their impression of their own yield prediction process. Test 003: Yield Estimation HYPOTHESIS OUR TEST METRIC WE’RE RIGHT IF Yield estimation would allow for significantly increased optimization in operations costs. >50% are dissatisfied RESULT Asked 8 farmers NOW WHAT [1] TBD [2] TBD Test Card ONGOING
  86. Competitor Leaf Diagram General Competitive Area: Precision agriculture that can predict yield and then create direct fertilizer and irrigation optimization opportunities for farmers. AgAi
  87. Total Addressable Market, per year: $47.58M (1.33M acres of almonds in California) * ( 119 avg. # of trees per acre) * ($0.10 per tree) * (3 “fruit counts” per year) Served Available Market, per year: $37.98M (80% of 1.33M acres of almonds comfortable actually use demand based irrigation, proxy for being open to new yield prediction technology) * ( 119 avg. # of trees per acre) * ($0.10 per tree) * (3 “fruit counts” per year) Target Market, per year: $8.73M 23% of the California almond acreage, which is self-opted into California Almond Sustainability Program, which we use as a proxy for the target market initially. Y1-Y3 Revenue: $357K, $1.43M, $3.57M Estimating $0.10 per tree * 119 trees per acre * 3x “fruit counts” a year * subscribed acreage (10,000; 40,000; 100,000) Market Size Sources: USDA NASS Almond Board 1 Almond Board 2

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