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Agtech report
Executive summary
The past two years were very exciting years for Agtech. Farming is going through a rapid evolution
with the integration of innovative technologies that significantly increase productivity on farm
operations. Technology offers great opportunities to the agriculture landscape, especially on the data
and cloud computing aspects. This is the best time for disruptive acceleration in agriculture innovation,
one that can empower new players in the supply chain to participate, benefit and significantly enhance
crop performance. Therefore, a growing number of startups have taken this opportunity to transform
agricultural processes and create value for farmers.
Today, the Agtech space is fragmented. There are no clear standards in place, and technologies are
generally addressing a unique need. Yet, consolidation is expected in the coming years. Large industry
players such as Monsanto are showing a growing appetite to acquire new technologies. This
consolidation will increase the need for a systematic technology, a foundational layer that allows
increasingly large enterprises to develop new solutions in an efficient way.
This report looks at the current dynamics of the Agtech ecosystem and identifies emerging technologies
which support innovation in the industry
Market overview
A. Definitions
Agtech is commonly defined as the convergence of technology and agriculture.
Over the past 30 years, Agtech mainly consisted of agricultural machinery. The 'First Wave' of modern
Agtech was the rapid and widespread adoption of biotech seed in the 1990s which was mainly driven
by yield boost. The 'Second Wave' expressed an even faster adoption of GPS steering which was driven
by cost savings. Other technologies, like irrigation hardware, were typically bundled with Clean-tech
and so were not considered part of Agtech.
Today, technology has given us the means to change the dynamics of the agricultural sector and tackle
issues that were earlier thought to be inevitable. Increased accuracy in weather prediction along with
timely availability of production and crop data has transformed the way agriculture is practiced in
developed countries.
In this report, we will focus on three Technology Clusters (referred to as “Tech clusters”):

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1. Decision Support Tech, which encompasses predictive data analytics (including weather
forecasting, pest and disease monitoring), satellite data and imagery analytics, farm management
softwares, ERPs, collaborative data platforms and cloud ag biology.
2. Smart equipment and Hardware, which includes soil sensors, IoT and precision irrigation.
3. Drones and Robotics, with harvest automation robots and agricultural UAVs.
These Tech clusters represented 25% of the broader number of Agtech deals in 2015. Their business
potential was estimated at $1.4b, which accounts for about 30% of the total investment in Agtech.
B. Why now?
Various stakeholders actively participate in the Agtech ecosystem, as shown in the graph below.
Figure 1: Impact of new technologies at each step of the agribusiness value chain
Today, advancements in big data, cloud computing, machine learning and computer vision enable new
players throughout the supply chain to participate, benefit and significantly enhance crop performance.
Our ability to generate, collect, and analyze large amounts of data - along with the scalable access to
computing provided by cloud computing services - allows farmers to leverage their complex data sets
in an affordable and easy manner. Therein lies an opportunity to disrupt a legacy value chain that is
now becoming obsolete. Traditional agricultural processes are not relevant anymore and must be
reinvented to meet a growing global production demand.
C. Challenges and Opportunities
We are talking about a multi-trillion dollar global market that is ripe for improvement, with new
agricultural needs developing at all levels. Innovative technologies are emerging, which lets small
players have a space in the field.

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The modern generation of farmers is looking for ways to be profitable, productive, and environmentally
sustainable, despite falling farm-gate prices. Farmers need to gather and extract relevant data about their
production in a cost-effective manner to understand what affects the crop in relation to the yield. Data
on weather patterns, fertilizer regime, crop disease is necessary for daily survival. Yet, one of the biggest
obstacles that companies in the Agtech space need to overcome is the opposition from farmers who are
set in their ways, and often skeptical of technology. The adoption rate of new technology by farmers is
indeed notoriously slow: self-steering tractors and combines, for example, are less than 20 percent
adopted after a decade of effort. Thus, adoption is one of the key challenges facing these Agtech
companies, new and old alike. To be a viable digital ag disruptor, companies need to ease the mounting
burdens on today’s farmers by helping them make better use of their time while driving better
performance on their farms. Moreover, the lack of wireless connectivity in many rural areas is still a
big drag on digitizing agriculture. The greatest potential may be in the developing world where tapping
into global communications networks and bringing big data to the world’s most information-poor
regions may have a significant impact on the crop yields.
D. Emerging Technologies
New technologies take part of a global trend toward increasingly data-driven agriculture, which is
mainly driven by precision agriculture technologies. The latter refers to technologies that make it easier
for farmers to observe, measure and respond to field variability in crops. Below are some examples of
how such emerging technologies are used today.
Drones with advanced sensors and imaging capabilities are giving farmers new ways to increase yields
and reduce crop damage by observing and mapping the agricultural land. Drones provide farmers with
a low-cost aerial camera platform that is controlled by a software on the ground, which can plan the
flight path (“autopilot”), take aerial shots and translate them into a high-resolution maps. The low-
altitude view gives a perspective that farmers have rarely had before. Compared with satellite imagery,
these UAVs are much cheaper and offer higher resolution. Most importantly, maps can reveal patterns
of irrigation problems, soil variation, pest and fungal infestations that are not apparent at eye level. They
can also create a view of the crop that highlights differences between healthy and distressed plants over
time, revealing trouble spots and opportunities for better crop management.
Agricultural robots and smart machinery are designed to grow more food with less labor, which allows
farmers to automate part of the planting and harvesting processes. Tractors can now autonomously plant
seeds with a high accuracy level, while GPS-guided harvester robots reap the crops. On top of reducing
the human resources required for production, these robots can navigate plant rows and send relevant
data to farmers to optimize the seed breeding or pesticide dosage.
Soil sensors change the way water and irrigation processes are managed in farms. These sensors can be
self-installed and calibrated, as well as buried below ground to keep track of what is going on in the
soil. They connect to intelligent adaptive algorithms that customize irrigation prescriptions on existing
drip hardware. Indeed, the sensor’s data is sent instantly via the cloud and it allows to calculate the
amount of water necessary to produce the maximum yield in each irrigation zone. The computer passes

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back the results to the farm’s irrigation system to adapt the level of irrigation, and prevent over-
watering. Such adaptive irrigation has the potential to save billions of gallons of water each year while
driving better outcomes for farmers. Many of these companies are also introducing a business model
that is new to agriculture - adopting a SaaS solution to allow farmers to pay on a subscription basis
instead of upfront hardware purchases.
Decision support technologies assist farmers in understanding the data they collect in their farm, and
using it to drive performance. Weather prediction technologies for example allow farmers to optimize
their crop yields in a significant way. Indeed, weather heavily influences the decisions made around
fertilizing, crops maintenance, fields irrigation, harvesting and transportation. If farmers know they will
have heavy rain the next day, they may decide not to put down fertilizer since it would get washed
away. During the harvesting phase, the soil needs to be dry enough in order to support the weight of the
harvesting equipment - if it is humid and the soil is wet, the equipment can destroy the crop. What is
more, when this weather data is coupled with satellite imagery maps that show crop maturity over time,
farmers can easily make proactive decisions and increase their yields based on accurate simulations. To
complete the picture, the generated data about crop yields is now collected not only on individual farms,
but as an aggregate from farm operations with similar climates and soil types. Thanks to collaborative
platforms that process data from various farms in real time, growers can perform benchmarks and make
better decisions with regard to planting, fertilizing and harvesting crops.
Figure 2: Mapping of emerging technologies in Agtech
Overall, such new technologies target a wide array of issues for farmers and therefore impact the
complete farming lifecycle - from pre-planting and planting to farm management, post-harvesting and
processing. The appendix provides a list of specific companies in each category.
D. Agtech startups overview
The capital invested in agriculture Tech clusters has quadrupled each year since 2013, reaching $1.5
billion in 2015 invested across 132 companies, as shown in the graph below.

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Figure 3: Number of deals (left axis) and capital invested (right axis) in Tech clusters, 2013-2015
Ever since the acquisition of the first “Ag Unicorn” (Climate Corp. by Monsanto), a flood of new digital
agriculture startups has been trying to turn investor interest into market traction.
The United States received the majority of Agtech investments during Q1 and Q2 2015 roughly $1B.
Israel came in second with about $500 million - mainly due to a large boost from Netafim’s funding.
Figure 4: Top 10 countries receiving Agtech funding ($ millions), first half of 2015
The following chapters provide an overview of the most interesting startups that operate in this field.
Imagery technologies for agricultural purposes are expanding with major players in geospatial, UAV
and sensor-based imagery / analytics services. They fall into four categories:
• Satellite imaging services: the most significant player in this category is Planet Labs, a Data
Collective and AME Cloud Ventures backed company that raised $158 million in equity funding.
• Satellite imagery analytics tools: Orbital Insights (backed by Sequoia Capital, $28 million total
equity funding), or A.I. company Descartes Labs ($8 million, backed by Data Collective)

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• End-to-end services including drone/satellite imagery capture, imagery analytics, and business
intelligence for farmers: major players include Precision Hawk ($29 million, backed by Intel Capital
and Verizon Ventures), Sentera ($8 million series A), DroneView Technologies ($2 million seed),
Mavrx Imaging (undisclosed series A), Cropio or Skycatch.
• Ag sensor-based imagery analytics such as Resson (Monsanto-backed, $13 million) or Prospera ($7
million series A led by Bessemer Venture Partners)
Other decision support tech include farm management software such as Farmers Edge Laboratories
($44 million capital funding - provides various agronomic services like farmland optimization, field
agronomy, farm laboratory, yield analysis); Granular ($24 million, Andreessen Horowitz-backed -
helps farmers using less water and less fertilizer); Taranis ($2 million seed, a precision agriculture
intelligence platform including satellite imagery, weather forecasts, and farm management); or
Farmlogs ($15 million - forecast and measure farm profits, track farming expenses, and manage risk).
This category also encompasses farmers network platforms and benchmarking tools like Farmers
Business Network (GV backed, $43 million,) or Farmlink ($64 million, an independent yield
benchmarking tool). Weather prediction tools include Understory Weather ($9.5 million, backed by
Monsanto), Booster Agtech (seed), and awhere ($14.4 million). Food tracking and compliance software
include Conservis ($12 million) or Lotpath (seed). Regarding BioAg cloud platforms, TraceGenomics
($4 million, Refactor Capital) uses artificial intelligence to predict agricultural diseases. In addition, an
interesting farm assets management startup is Filament ($7 million) - an IoT device that connects
existing machinery, equipment, and assets to a wireless sensor network and monitors them.
Drone technologies are split between:
5) Autonomous drones: 3DRobotics ($126 million funding), Airobotics ($28 million), DJI, Ehang,
CyPhyWorks ($22 million, BVP)
6) Operating systems for commercial drones: Airware ($70 million), Skyward, Drone Deploy ($9
million, backed by Data Collective)
7) Drone guidance tools: Swift navigation (precision & accuracy for aerial surveying, device guidance
& autonomous vehicle) or Trimble navigation
Accel Partners partnered with China’s DJI to launch Skyfund, a $10 million fund that aims at investing
into early-stage around drone, robotics, machine intelligence, computer vision and navigation.
Specifically, this fund focused on backing developers that build software and hardware using DJI’s
development kit. It is therefore relevant for ag imagery and field mapping startups. Similarly, Airware
announced a new Commercial Drone Fund to invest in early stage startups from the enterprise drone
ecosystem.
Automation & robotics are mainly computer vision systems that integrate with ag machinery. The
goal is to automate the harvesting process and reduce human resources needed in the farm. Such
companies include BlueRiver Technologies ($30 million, backed by Monsanto and DataCollective);
Harvest Automation ($25 million); FFFrobotics (robotic arm on board of a Clearpath Robotics robot -
Together, the robot autonomously navigates apple orchards and picks fruit from trees). Include also
novel fruit gripping technologies like Soft robotics (a Harvard spin-off, $5 million).
Soil sensors include CropX ($10 million backed by Innovation Endeavors), an ag-analytics company
that develops a cloud based software integrated with wireless sensors to boosts crops yields; Arable
Labs ($5.5 million in seed round) which provides a solar-powered IoT device with advanced sensors to
handle in-field crop monitoring; Aquaspy ($6.5 million), a sensor and web-based software that help
growers become more efficient with water, fertilizer and energy; FarmDog (seed), advanced sensors
for pest and disease detection; Saturas ($1m seed), miniature stem water sensors embedded in the trunks
of trees, vines, and plants to optimize irrigation and increase production.

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Smart Irrigation technologies include Netafim, a leading player in drip and micro-irrigation solutions,
and Hortau ($21.5 million, backed by BDC Capital), a wireless and web-based irrigation management
system.
4) General insights about Agtech startups activity
When looking at the bigger picture, startups form the Tech clusters raised $333 million during the first
half of 2016, slightly more than half of what was raised during all of 2015 ($661m). There was a slight
shift in the make up of this segment in Q1 and Q2 2016 compared to 2015: drones represented a smaller
portion of the precision ag segment (34% vs 49%) while investors continued to favor decision support
tech. Indeed, decision support software startups represented 28% of precision ag funding compared to
11% during 2015. Hardware and sensors startups also grabbed a larger size of the pie raising from 3%
to 8%. Satellite imagery went down from 27% to 17%, while weather prediction analytics tools grew
from 1% to 2%. So far, major investors and venture capital firms enabled a strong M&A activity in the
AgTech field. According to AgFunder 2016 report, the number of investors coming into Agtech
climbed 52% between 2015 and 2016, suggesting that investors are getting more comfortable with the
sector. This strong M&A activity spurred entrepreneurial activity and gave entrepreneurs the startup
funding and support they need to bring new technologies to light.
F. Potential exit routes and current state of IPOs
So far, the best exits are those that have had corporate investors. The most exciting exits have been
strategic trade sales, namely Monsanto’s acquisition of The Climate Corporation in 2013 for $1 billion,
followed by acquisitions by “the Big 4” bio-space players (BASF, Bayer CropScience, Dupont, Dow
Chemical Company, and Syngenta). The major ag players view the ability to offer new products and
services to fill their pipeline as the key to their future growth. That said, with growing numbers of
complementary technologies, and even more consolidation opportunities, private equity firms will have
an important role to play to contribute to the dynamics of the industry.
E. Benchmark of large Tech players
General Tech corporations are more and more involved in the Agtech industry. These major
corporations include Microsoft, IBM, Google, Amazon, Cisco, Intel, Oracle, GE, SAP, HP, Verizon,
AT&T, Orange, Telefonica. Here are the key findings:
1) Boom in Agtech collaboration between general Tech players. Microsoft recently announced a
partnership with Monsanto in a bid to invest in Brazilian agricultural technology startups. Earlier
this year, Intel and AT&T agreed to work together to improve the performance of the LTE networks
for drones in high-altitude, with a focus on Agtech applications. A few months later, IBM signed
a deal with Cisco to bring Watson IoT technology into Cisco’s architecture, providing analytics
services for networks of UAV’s remote control. On a larger scale, Google is developing the Farm
2050 project - a cross-industry collaboration with companies ranging from fertilizer producer
Dupont to supply chain management software company Flextronics, in order to increase farm
production by 70 percent by 2050. On the telecom side, Telefonica has partnered with Israeli IoT

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company Bacsoft’s to provide remote field monitoring and control for all critical data such as
temperature, humidity and irrigation flow.
2) Expansion of Agtech research projects. Given the huge potential for research and development
in the agricultural sector, corporate partnerships are likely to gather momentum in the coming
years. New startups will gain from this momentum, as corporate partnerships will back new startups
in this particular sector. Research projects include Deep Thunder by IBM, an initiative which aims
to improve short-term local weather forecasts through the use of high-performance computing.
Another research project includes Intel’s work with the University of California and the World
Food Center, a collaboration which tackles California’s water problems by applying big data and
satellite imagery techniques to precision farming. Orange Silicon Valley, the Bay Area innovation
division of French telecommunications company Orange, also launched the Agstudio initiative to
research needs of Californian farmers, and support innovations.
3) Launch of specific solutions for Agtech. Verizon plans to launch an AgTech IoT software
platform in Q3 2016 to improve the connectivity of sensors - and other data-capturing devices - on
the farm, helping farmers to turn this data into actionable insights. AT&T has already introduced
M2X, which provides data services for smart agriculture IoT, farm sensors, driverless tractors, and
farm info management. On supply chain software side, SAP launched a Digital Farming
Machinery Insights Solutions and Vistex Farm Management to support the full life cycle of farm
operations. Oracle offers JD Edwards EnterpriseOne application for “Food & Beverage
Producers”, providing growers with real-time information that covers the entire crop-to-product,
block-to-bottle cycle. Finally, Google partnered with Basecamp Networks to build Intelliscout, an
AR farming app for Google Glass.
4) Emerging local Agtech centers. Microsoft and Monsanto partnered together to invest in
agricultural technology startups in Brazil to help foster new startups in the agricultural sector in
Latin America. Cisco invested $15 million in a new “Internet of Everything” center in Sydney,
aiming at making Australia the epicenter for IoT R&D in agriculture. GE initiated new projects in
the Japanese agriculture sector by launching an indoor farm at Miyagi Fukko Park - one of the
world's largest plant factories which uses LED lighting throughout.
5) Active role of tech players in Agtech investment & acquisition scene. Google led two major
investments: $18.7m in Granular, and $15m in the Farmers Business Network. IBM acquired the
Weather Company and runs them on IBM cloud data centers. Verizon invested in PrecisionHawk,
Filament, and Skyward.
6) Support by major Cloud platforms of open agricultural data projects. CGIAR, a consortium
of international agricultural research centers, made its data accessible and available for addressing
critical food security challenges using the Amazon Web Services Cloud. Microsoft launched an
innovation challenge with the U.S. Department of Agriculture, by providing contestants with
USDA open data sets (hosted on Microsoft Azure) to develop online tools that help make the
American food supply more resilient in the face of climate change.

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Appendix: Agtech market map US and Israel, mid-year 2016