A hand wrapped in a produce wreath holds a screen with Agsight's plot overview screen.A collage of images showing different stages of assembling an Arduino-powered robotic vehicle with electronic components, wiring, gears, and a pinwheel on grassy terrain.A wide shot of a student outdoors in a park holding a "I matched with Cornell" sign, surrounded by oak trees and autumn leaves on a sunny day.A person wearing a beige sweatshirt, green shorts, and a white cap stands with their back to the camera in a grassy area surrounded by trees, looking out toward open farmland and distant mountains under a partly cloudy sky.
atmosphere
agsight
college
about
agsight
2024 - present
helping 50+ vineyards and orchards respond to environmental threats
learn more
skip to solution
A hand wrapped in a produce wreath holds a screen with Agsight's plot overview screen.
30-second synopsis
I created a geospatial machine learning app to help 50+ vineyards and orchards in 2 countries respond to crop threats, improving average yields by ~12%. Helped 4 Napa Valley winegrowers reduce smoke taint during the 2025 California wildfires and 5 citrus/avocado farms overcome saltwater intrusion. Using this work, I successfully advocated for a new agribusiness course to expand agricultural education in Frisco ISD by petitioning the superintendent and School Board.
52

farms impacted

12%

improvement in yield

36%

decrease in crop stress

98%

as accurate as sensors

01
auditing the current experience
analyzing the problem
To uncover pain points farmers face with existing agtech, I surveyed 150+ specialty crop growers across the US about their daily challenges, resources, and habits with farming technology. I distilled responses into 6 recurring themes.
A scatter plot shows responses for "What has been your return on investment for your agtech solution?" The graph shows an increasing linear trend between yield increase and the price of agtech solutions: As the price increases, yield also increases, but marginally.
unclear ROI
Many farmers found it challenging to justify the high costs of agtech when the outcomes of using it were not immediately evident. One shared that after spending $5K on a precision farming system, their yield only increased by 1%.
Bar chart comparing agtech solution effectiveness across crop types, showing common staples as most supported, heirloom vegetables as moderately supported, and fruits as least effectively supported, with varying levels of perceived ineffectiveness and detriment.
lack of personalized data
Existing tools' lack of location-specific personalization result in data that were not only ineffective but sometimes detrimental. 34% of surveyed farmers reported that agtech solutions frequently overlook the needs of specialty crop farmers, including those growing heirlooms or fruits.
A funnel chart shows the percentage of surveyed farmers who were able to successfully schedule a demo, acquire infrastructure, complete setup, training, and start using an agtech solution. Only 54% of those who scheduled a demo started using the agtech solution.
frictional onboarding
Many farmers reported that onboarding for many agtech solutions is lengthy and complex because it takes several weeks to schedule demos, acquire infrastructure (notably sensors), and finish training sessions. 83% of farmers over 50 reported struggling with a steep learning curve.
A pie chart illustrates responses to the question "What is the primary challenge you face when using your current agtech solution?" with 43% citing irrelevant features, 31% hard to interpret data, 14% limited applicability, and 4% no major issues.
outdated
Many farmers complained about data being presented in cluttered interfaces in a spreadsheet format, which made it challenging to quickly find specific details or parse through complex data. 43% of farmers using agtech software also reported that their current solution had too many features that were not relevant to their specific needs or crops.
A stacked bar chart shows responses to the the question "How often do you find that the data provided by your agtech solution lacks actionable insights?" across four categories: Weather monitoring, soil monitoring, crop health, and pest detection. The majority of farmers report "often" or "always".
lack of actionable data
Farmers reported that most data provided by agtech solutions lacked actionable, farm-specific insights, which made it difficult for them to use in real-time decisions. The data was presented in a vacuum, not applied for recommendations.
Bar chart showing that most users spend $1K–$2K per year on agtech tools, followed by $251–$1K, $0–$250, $2K–$5K, and the fewest spending over $5K.
cost prohibitive
91% of surveyed farmers cited the high price of agtech solutions as a major barrier to adoption. Primarily, high upfront costs and recurring fees put them out of reach for small- to medium-sized farms that typically operate on tight margins, which disincentivizes them from using agtech.
asking the right people the right questions
I interviewed farmers, analyzed 15 competitor platforms, and studied industry trends to identify what growers actually need versus what existing tools provide. By understanding where farmers drop off, I learned which features matter most and which create unnecessary friction.
8

interviews

156

survey responses

15

competitive audits

Which features do you use most often? Why?
What do you find frusturating?
What outcome do you want to achieve?
What do you like about other agtech?
Which features do you use most often? Why?
What do you find frusturating?
What outcome do you want to achieve?
What do you like about other agtech?
How do you diagnose diseases or pests?
Has agtech lacked data you needed?
What farming task takes the longest?
What issues do you face with irrigation?
How do you diagnose diseases or pests?
Has agtech lacked data you needed?
What farming task takes the longest?
What issues do you face with irrigation?
The user journeys of Jessica, Henry, and Michael.
user journeys
I mapped each user archetype to their journey on competitor platforms by tracking their goals and outcomes. This helped me spot pain points, uncover opportunities to improve, and identify which features to prioritize.
Competitive audit sheets highlighting competitors' strengths.
competitive audits
I analyzed 15 top agtech tools by comparing features, user feedback, and gaps to find opportunities for innovation and differentiation. One key insight: the median competitor price was around $750/year.
A spreadsheet evaluates and categorizes the sentiments of App and Play Store reviews of Agsight's competitors.
sentiment analysis
Farmers frequently express frustration with high costs, inaccurate data, and friction during onboarding, while others expressed delight on unique features like smoke taint analyses and a focus on small producers.
A series of interviews and meetings with farmers via Zoom.
interviews
I conducted 8 virtual interviews via Zoom and chose to target Central CA specialty crop farmers of small- to medium-sized farms because they were generally most affected by the inequities posed by current agtech solutions.
defining my audience
I analyzed behavioral patterns to create 3 farmer archetypes representing distinct needs and constraints, then mapped each to their core jobs-to-be-done.
newcomer
traditionalist
smallholder
Early-stage grower building a specialty crop farm with sustainability goals, interested in technology but limited by capital and uncertain where to start.
challenges
  • Overwhelmed by agtech options geared toward large-scale operations.
  • Most products lock them into high upfront costs or infrastructure incompatible with small farms.
Needs
  • A flexible solution with a low barrier to entry.
  • Clear evidence of how insights improve yield, reduce waste, or drive ROI, without requiring sensors, drones, or complicated tech stacks.
A black farmer balancing a peach on her bucket hat.
Long-time specialty crop farmer managing a small family operation and pressured to adopt agtech despite limited technical knowledge.
challenges
  • Finds most agtech overwhelming due to technical interfaces and jargon that don't align with traditional farming.
  • Struggles to justify expensive hardware or subscriptions when ROI isn't immediately measurable.
needs
  • An intuitive solution that requires no new hardware and provides clear, actionable recommendations.
  • Support materials for non-technical users that don't require hours of training.
A farmer stands in his orchard with a grocery tote bag full of fresh produce.
Mid-size farm manager responsible for field operations and administrative decisions, juggling production and labor with minimal support staff.
challenges
  • Don’t have the time to navigate dashboards filled with irrelevant metrics for crops they don’t grow or conditions that don’t apply.
  • The steep learning curve and lack of crop-specific insights lead to underuse or abandonment within a few weeks.
needs
  • Local, crop-specific recommendations in a clean format so they can make quick decisions on the field.
  • Minimal setup, no required hardware, and instant visibility into what matters most: irrigation, stresses, and yield.
An elderly farmer peers into his fields behind his tractor.
02
synthesizing research
eliminate the need for infrastructure
Smaller farms can't afford dozens of sensors, which are expensive, fragile, and often fail mid-season. Although sensor-free precision agriculture has been discussed in research, it's never reached commercial markets. Here, I decided to do something radical: Opt for a sensor-optional solution.
make data actionable
Farmers have access to metrics like evapotranspiration and pest pressure but don't know what to do with them. The real need: Clear, actionable advice like "adjust irrigation by 20 minutes" or "apply treatment to Block 3." Bridging the gap between data and decisions with simple, trusted steps will increase adoption.
make solutions affordable
Cost consistently emerged as a barrier. For farms operating on razor-thin margins, subscription fees compete with fertilizer budgets and sensor repairs become unaffordable mid-season. The opportunity: Build solutions that respect financial constraints without sacrificing functionality.
personalize to improve relevance
With 47% of the surveyed farmers citing the high cost of agtech as a major barrier to adoption and 55% showing a low willingness to pay due to lack of location-specific personalization, there's a lack of personalized solutions that adapt to individual farm conditions and crop types.
reduce friction dramatically
Farmers describe delays to schedule demos, receive sensors, and complete onboarding. Every extra step becomes a reason to abandon technology during harvest season when time is scarce. The opportunity: Build something that works immediately.
smoothen the learning curve
When I asked what prevented continued use of paid agtech, most farmers cited feeling overwhelmed by complex interfaces. With 32% of surveyed farmers over 65 and only 35% holding college degrees, the opportunity is in zero-setup onboarding, interfaces that show only essential information, and eliminating assumptions about technical backgrounds.
automate manual tasks
Many farmers checked soil moisture by hand, walked rows to spot stress, and calculated their crops' irrigation needs. The opportunity: Automation that flags what matters and frees farmers to focus on higher-level decisions.
forming a business
I ideated multiple solution approaches, diverging broadly before converging on a specific direction. I landed on a sensor-free spatial machine learning Android app delivered as affordable SaaS to help specialty crop farmers overcome vegetation stress, water scarcity, and soil infertility.

data in a vacuum

incompatible infrastructure

steep learning curve

no local personalization

reliance on manual labor

unsustainable yield

unaffordable solutions

predicting pests + diseases

focussing the solution
Drawing from user insights, I brainstormed must-have and ambitious features tied to six core experience pillars. With vision and scope defined, I moved into design and engineering.
home
  • fields
  • yields
  • notifications
  • Sspatial agendas
crop growth
  • crop assessments
  • personalized schedule
  • phenology
  • crop rotation
crop threats
  • crop stresses
  • diseases
  • IPM
  • climate threats
water use
  • water needs
  • water/salinity stress
  • irrigation
  • soil moisture
soil fertility
  • health
  • nutrition
  • fertilizer use
  • composting
other
  • IoT automation
  • climate control
  • nutrient dosing
  • hydroponics
03
the final product
meet agsight
Cost-effective, personalized, and scalable. The first sensor-free agricultural machine learning app for specialty crop farmers.
learn more
tour the app
A phone perched on a rock and leaning on an avocado showing a screen with tips and best practices for raising avocado. An avocado branch balances above the tip of the top left corner of the 25-degree tilted phone.

optimize yield with spatial insights.

save big on water: irrigation and stress.

improve soil fertility and nutrients.

diagnose any disease or pest in seconds.

AI-mazing ways to sustain yield
When developing, my biggest priority was speed-to-decision. I built Agsight's AI pipeline to process phenology, growth, and climate data simultaneously and suggest exact next steps: which disease or pest is present, where and why it's spreading, and what to do now.
diagnose and treat any plant disease or pest in seconds.

threats

track your crops' growth with beautifully precise data.

phenology

get instant updates so your crops get attention when they need it.

health

parse through location-specific information with ease.

localization

diagnosing plant diseases, lighting fast
One of Agsight's most powerful features uses machine learning to identify, classify, track, forecast, and manage plant diseases, pest infestations, vegetation stress, and pesticide applications. With 98% accuracy, it provides stress signal details, personalized treatment plans, pesticide recommendations, and development predictions.
Mobile app diagnosis screen displaying apple scab detection with photo of red berries on branches and vegetation stress indicators including leaf discoloration and curling symptoms with accurate/inaccurate feedback buttons.
protecting against threats, ahead of time
Farmers assess threats from air quality, climate events, soil conditions, and pest pressure right at their fingertips. Whether wildfires, frost, heat waves, or insect outbreaks, they know ahead of time.
Mobile app notifications screen showing priority wildfire smoke alert with peanut illustration and red button to see smoke mitigation strategies, with suggestions tab showing 17 unread notifications.
intelligent irrigation
Many farmers told me they wasted time and water because they couldn't identify which field sections needed moisture as weather and crop needs changed week to week. I designed a system where Agsight interprets satellite data by analyzing seasonal patterns, crop type, and weather forecasts to deliver real-time, field-specific irrigation recommendations.
A mobile app screen displays a water assessment for apple crops, showing a recommended irrigation level of 1.1 inches per week and a disease alert warning about apple scab.
apply water where your crops most need it.

water needs

know where, when, and how to irrigate your crops and plots.

irrigation

automating irrigation and climate control
Given the depth of personalization Agsight's AI features provided to trial farms, I extended functionality to allow farmers with existing sensors to fully automate irrigation and climate control, both indoors and outdoors.
climate
irrigation
hydroponics
agsight works indoors, too.
By tracking factors such as temperature and humidity, Agsight helps optimize light conditions for each growth stage to reduce crop stress and lower the risk of disease.
A mobile app screen shows lighting data for Shelf B1 in an indoor farm, with hotspot markers on lettuce crops and a graph tracking chlorophyll concentration over time.
irrigation, automated.
Agsight automates irrigation by using real-time soil moisture data to deliver precise, crop-specific amounts of water, personalized to growth stage and plant type.
A mobile app screen displays collected data from Row B in a vertical farm and shows live camera footage of lettuce and basil under grow lights, moisture sensor status, and irrigation controls.
rich in nutrients, rich in sustainability.
Agsight supports hydroponic systems by tracking changes in water nutrient profiles and adjusting inputs based on the specific needs of each crop. This precision reduces reliance on chemical fertilizers and can increase yields by up to 25% in fast-growing greens like kale, basil, and arugula within weeks.
A mobile app screen displays a lettuce growth overview with a projected harvest time in late June and a line graph tracking electrical conductivity levels from April to August.
04
impacting farmers
impact
After developing my MVP, I initiated outreach to 80+ farms via email. 8 initially agreed to trial Agsight. I've since expanded this pilot program to 50+ orchards and vineyards across California and Texas.
website
I focused on clarity and trust to make sure farmers could immediately understand what Agsight does and why it matters to their daily work.
visit website
The Agsight website homepage promotes an AI farming app with a photo of a hand holding a phone displaying the app, surrounded by vegetables worn as bracelets, and text offering a $12.99/month subscription after a 30-day free trial.
california wildfires
Through Agsight, I helped 4 Napa Valley winegrowers reduce smoke taint during the 2025 California wildfires using sensor-free machine learning algorithms.
learn more
Tilted photo card showing Napa Valley vineyard with grapevines in foreground and wildfire smoke filling the valley between hills at golden hour, displayed with decorative mint green corner accent on beige background.
harvesting
smoke taint
ripeness
selectively harvest your crops overnight.
Using satellite imagery and machine learning models, we help winegrowers identify which grapes are ripe enough for immediate harvest to pick high-risk fruit overnight.
Mobile app plots overview screen showing aerial satellite view of vineyard rows with maturity timeline indicating apples ready for harvest by early August and crop selection toggle between apples and pomegranates.
Smoke taint data at your fingertips.
Agsight provides smoke taint data so winegrowers can forecast where terrain and weather concentrates the most smoke across their vineyard.
Mobile app interface showing aerial view of color-coded agricultural plots with health monitoring tab selected, identify weeds button, and red wildfire smoke risk alert banner below.
Know which crops to harvest during wildfires.
Agsight shows growers which high-exposure rows are ripe enough for immediate harvest and which are underripe areas worth protecting.
Mobile app notifications screen showing priority alert for wildfire smoke risk assessment with peanut illustration and red call-to-action button for smoke mitigation strategies.
salinization
I also helped 5 citrus and avocado farmers in California overcome saltwater intrusion by using satellite imagery to increase their yield by 12%.
learn more
A hand uses a gold kitchen sprayer to rinse fresh vegetables including kale, tomatoes, and lemons in a marble sink.
irrigation
water stress
alerts
Irrigation, made easy.
Our machine learning models calculates precisely when, where, and how to water your crops based on their needs, conditions, and salinity.
Mobile app water irrigation schedule screen showing suggested watering times for apples and pomegranates with Monday's deep watering recommendation of 0.4 inches for 2 hours and Tuesday's follow-up watering details.
never stress about stress again with personalized irrigation schedules.
Smart, sensor-free irrigation schedules are personalized to each plot and prioritize the zones that need water most by factoring in salinity, climate, and crop conditions.
Mobile app agenda screen showing aerial satellite view of farm plots color-coded by priority with day/week/month toggle and general versus plot-specific task views, with numbered red alert badges on specific parcels.
Always be in the know on your crops' water needs.
We send you simple, timely alerts so you can apply soil amendments to high-salinity areas, crop rotation schedules that include salt-tolerant crops to break salinity cycles, and optimal times for leaching.
Mobile app notifications screen displaying water-related alerts including apple scab water stress detection, irrigation alert for squash and cauliflower plot reaching wilting point, and harmful algal bloom reports in Old River and San Joaquin.
educational advocacy
Using Agsight, I successfully advocated for a new agribusiness course to expand agricultural education in Frisco ISD by petitioning the superintendent and School Board.
In the audience: Superintendent Dr. Mike Waldrip, School Board members, and 150+ students and teachers.
learn more
Joon stands alone on stage under a spotlight in front of closed blue curtains, presenting to an audience in a dimly lit auditorium.
more work
about me
A collage of images showing different stages of assembling an Arduino-powered robotic vehicle with electronic components, wiring, gears, and a pinwheel on grassy terrain.
inventing an AI-rover system to make clean air accessible for 2.4K+ dallas students
atmosphere
2024 - 2026