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Tony Kramer: Hi, I’m Tony Kramer, your host of the Agriculture Technology Podcast, and I’m sitting down with agriculture technology and equipment experts to help you enhance your operation for today, tomorrow, and into the future. In this episode, I talk with Eric Taipale and Kevin Friedenberg about Sentera drones and sensors.
With that, let’s dive into the show. Like I said, we are going to be talking about some Sentera drones and sensors in this episode. Before we get into it, I want to learn a little bit about our guests, Eric and Kevin. So Eric and Kevin, why don’t you introduce yourselves? Tell us a little bit about who you are, what you do, and how you got to where you are today.
Eric Taipale: Hi, Tony. Thanks very much for having us. I’m Eric Taipale. I was most recently the CTO of Sentera, and way back 10 years ago, I was part of the founding team. My background is in product and engineering. I’ve been doing unmanned systems of one type or another for about 28 years, which starts to make me feel more old than experienced. But I was really fortunate to grow up in the defense industry at a time when these were becoming prevalent, so I’ve worked on unmanned systems that swim under the water, fly in the air, big systems, small systems.
As an engineer, my interest is more so in the various streams of data — the sensor systems, the actual information that flows off of these systems, and the tools that have been developed, principally software tools, to make sense of different types of data, bring it together, and understand as quickly as possible the state of the environment that the system is observing.
Kevin Friedenberg: My name is Kevin Friedenberg. Earlier this year, with the acquisition, I became the General Manager at Sentera. My history with John Deere — I’ve been here a little over nine years — and my background is predominantly in the product development space. I also spent some time in shop floor operations at our Harvester Works factory in East Moline, and more recently with our Intelligent Solutions Group in Urbandale, Iowa, really focused on technology product management.
So my background and my interest are really about understanding customer problems and how we create a product and create an offering that helps our customers address those needs across different parts of the production system.
Tony: It is, once again, great to have both of you on the show. Obviously, Eric, we’ve got you — one of the originals with the Sentera product. And then Kevin, we bring you in with the acquisition. We’ll talk a little bit more about that towards the end.
So to get started, Eric, tell us a little bit about the history and background of Sentera and how it got up and going to where it is today.
Eric: Every startup has a pretty entertaining origin story, and Sentera is no exception. Full disclosure, it didn’t always seem all that entertaining at the time, but it’s a great story. We had a team — really the core of the product and engineering team — that understood a lot about how to build drone systems and how to produce imagery, especially imagery from these unmanned systems.
We had a head start because we’d been doing this for a long time in another vertical. Ten years ago, we could really see the convergence of a bunch of technologies and the cost profile of those technologies coming down: low-cost imagers, low-cost electronics, and controllers. We knew there was going to be a commercial future for the drones that we had been using in other applications.
When we started Sentera, we were going to take a really broad brush with sensor and drone technology. We fielded a basic set of imaging capabilities and a couple of drone platforms and tried to serve really everybody. We had customers imaging mobile phone towers, we had customers imaging railroad tracks, and we tried to serve them full stack.
The only place where we felt like there was really strong traction for us was agriculture. We had experience in that vertical, close connections to partners like RDO Equipment Co. and John Deere, access to growers, and we could understand those customer use cases a bit better than we could in other verticals.
So we really, as a business, decided after maybe the second year that it’s great we make sensors — and we make great sensors that get sold into distribution channels and used in lots of places (sometimes even surprising us when we see them at a trade show). But the full-stack solution — where we are looking at customer problems and developing deep learning platform software to solve those problems completely — really only occurred in agriculture.
That’s because we thought there was so much connectivity and so much richness in what we could do throughout the season. Agriculture makes it a really unique place for the application of these technologies.
Tony: So, as you stated there, it’s really the focus on agriculture, but you also talked about some of those other industries you were dabbling in. Tell us a little bit more about those industries, those use cases, and if those solutions still stand out today. Of course, with the John Deere acquisition — John Deere’s got their hands in construction, forestry and many other industries — tell us a little bit about what you saw in those industries and why you kind of landed back in that ag space after those couple of years.
Eric: The first thing that was unique about agriculture is that there are so many problems to be solved. There’s such a variety of challenges to address, and that really wasn’t true in some of the other verticals, as far as we could see.
When we look at where our sensors are used today in applications like road construction, there’s a lot of imaging in rights-of-way, some land-use analysis, and construction activities that range from inventorying materials to verifying that land use is correct according to permitting and planning. I mentioned infrastructure before — vertical tower inspections and building inspections. These are great businesses. Like I said, we sell a lot of sensors. Sentera sensors are made in the United States, people trust them from a data security perspective, and they are high-performing. So we sell a lot of hardware to customers that have built vertical solutions.
From our perspective, and with the relationships we had, we didn’t feel fully prepared to go beyond being just a really good hardware partner to those who already deeply understood the vertical. Being in the Upper Midwest, in Minneapolis, we’re close to the heart of where strong innovation is happening, especially in row crop agriculture. We had good partnerships that could point the way.
We felt much more comfortable focusing on areas where we could really make an impact, because we had great partners literally right outside our door. We had places to test and growers who would tell us whether the problems we were solving were relevant or not. It was just clear to us that the best and highest use of our capabilities really lay in agriculture, in terms of providing a full vertical solution.
Tony: Yeah, so let’s dive into that a little bit more now on the agriculture side. You guys have a couple of different offerings. Let’s start by discussing the DGR system. Tell us a little bit about that.
Eric: DGR stands for Direct Georeferencing. It’s related both to the platform — the drone itself — and to the sensor, which is usually an imaging platform, typically a camera. Direct georeferencing is really cool technology because, for those familiar with drone workflows, one of the most time-consuming, costly, and bandwidth-heavy steps is something called image stitching.
Here’s what that means: when I fly a drone today without this technology, and I want to capture a large area, like a farm field, I have to take a bunch of overlapping images. Only about 25–30% of each image is actually new; the rest overlaps with the previous image. This overlap is necessary for image stitching, which finds common elements across the images to correct for imprecision in knowing exactly where the drone is and what direction the camera was pointed. That precision is critical for plant-by-plant management or zone-based management.
Everyone in the drone space used this method. Up until three years ago, we were bound by it too. But it wastes a lot of time and resources. You end up capturing maybe nine images of each spot on the field to make the stitching accurate — nine times more data than needed.
Based on experience in defense and aerospace, we knew there was a better way. At Sentera, we have both software — deep learning capabilities — and hardware — sensor engineering expertise. We brought them together to develop Direct Georeferencing, a four-year effort that’s now integrated across all of our enterprise-grade multispectral and high-resolution RGB imaging platforms.
The results are dramatic: a true 9x reduction in data volume, because we eliminate overlapping imagery. We only need to capture each point once. This also speeds up field coverage — not just along the flight path but across the lanes the drone flies — allowing us to cover three times more acres in the same amount of time. Upload times are nine times faster, and data can be processed right in the field.
We’ve even experimented with AI at the edge this year, which further improves efficiency. The result is a revolution in the unit economics of grower data collection — it’s now a fraction of the cost. It’s not about the sensor itself, but rather an adjunct that makes the sensor far more productive and delivers answers to the grower much faster.
Tony: I will say, anyone who’s experienced the traditional orthomosaics and image stitching knows how painful it can be. Having used some of the early Sentera offerings, this technology is amazing. One of the biggest pain points has always been the sheer amount of data collected. You mentioned all those overlapping images — only a small portion is actually used in stitching, so this is a great improvement.
Is the DGR system an end-to-end solution with aircraft, sensor, and the technology, or how does that work in terms of Sentera?
Eric: It’s really tightly integrated with the sensor because the timing of the image capture has to be synchronized precisely with the drone’s positioning and orientation. But the drone itself doesn’t matter as much. Sentera takes the approach that we want to be platform-agnostic — we don’t depend on whether the drone comes from manufacturer A or B. That holds true with DJI. We have three or four officially supported platforms, and several others that could integrate us as an OEM.
To give context, five or six years ago, we introduced our Weeds product that could fly over fields, localize, and find weeds. The first time we demonstrated it, it took three days to process the super high-resolution imagery before it could be actionable. Yes, we could find weeds from a drone, but three days was too long. Now, with DGR, it’s four hours, which is much more reasonable for growers and agronomists.
Tony: Yeah, and that’s exactly where my mind went, Eric — to some of the weed-sensing and weed-mapping capabilities. Before, because of the data volume and the time it took to process it, it was a long, kind of painful wait. Now, with the DGR system and its capabilities, that’s gone away. We’ve made it to the next level with quick turnaround, and we can really utilize this data. Very exciting, very cool technology to bring into the industry.
Along with the DGR system, obviously Sentera has a lineup of sensors. You mentioned they’re made in the U.S., they’re very reliable, and they’re trusted. Tell us a little bit about the different sensor offerings and why a customer might choose one sensor over another.
Eric: It really comes down to the customer use case and the job to be done. At the very highest end, we have customers doing phenotyping for plot trials, breeding, and seed production. These customers track plant-by-plant, want to understand biomass development curves, and examine specific frequencies of light that plants reflect — sometimes in very precise combinations.
These applications have extremely demanding requirements for spatial accuracy — to get down to individual plant level — and radiometric accuracy, meaning how precisely we represent that frequency of light. We have products like the 6X or custom-engineered systems augmented by ground-based calibration tools. These are state-of-the-art, no-compromise multi-spectral and RGB sensors that allow nearly leaf-level surveillance.
That level of precision isn’t necessary — and isn’t even desirable — for many crop production systems. For a grower managing thousands of acres, it’s more about understanding uniform emergence, emergence percentages, disease detection, or where scouting is needed. They may want to apply a variable-rate fertility prescription. Those use cases don’t require extreme precision.
For that category, we have sensors like Double 4K, a multi-spectral product that’s smaller, lighter, and more affordable. These fly on smaller drone platforms and are tuned for scouting rather than full-season, high-resolution tracking of individual plants. They’re perfect tools for retail agronomists or precision specialists from equipment dealers who need to assess equipment performance and field conditions.
So, essentially, we have two families of sensors: multi-spectral and thermal, and standard visual-band sensors. Within those families, there’s a range of capabilities — from high-end phenotyping down to large-scale operational scouting — all designed to support agronomic decision-making at different scales.
Tony: And like you said, Eric, it really comes down to what you’re trying to do — a basic scouting operation or a scientific, diagnostic-level multi-spectral analysis. It’s awesome to see that Sentera offers all of those options. You’re not limited to one sensor for an NDVI image, nor just the high-grade 6X offering. That range is fantastic for addressing different needs across agriculture.
Now, of course, once you collect data with the DGR system or any of these sensors, you have to do something with it. Talk to us a little about Field Agent software from Sentera.
Eric: Yeah, that is the piece the piece… And I wish I could say, looking back 10 years ago, I that this was all part of a grand strategy we have on the whiteboard: first hardware, then analytics, then software. That’s not true, and it was our customers that drove the product progression that led to the full stack that Sentera has today.
Field Agent actually started because of a Ziploc bag. A customer walked into our office with a one-gallon Ziploc bag full of USB drives. Normally, he’d label them with a marker, but somehow they’d gotten wet. He didn’t know which images went with which field. That was 10 years ago. We realized: every image is stamped with GPS location and time. Why not write software to organize it? That was the origin of Field Agent. At its core, it was a tool to sort thousands of images from multiple fields and dates, to organize data for stitching and analysis.
Over 10 years, Field Agent has grown. It now has API connectivity, so results — like weed maps or NDVI maps — can be pushed to John Deere Operations Center, Climate FieldView, or other integrated partners. It has machine learning orchestration, running analytics for emergence, disease detection, weed pressure, and harvest timing. It’s a cloud-based engine that handles massive high-resolution data while making it useful to growers, agronomists, and retailers.
Field Agent also interoperates with other data sources — soil data, weather data, satellite imagery — to make all this information actionable. And it all started because of one obvious customer problem: a bag of disorganized images.
Tony: I would have to agree — a customer walking in with a gallon bag full of flash drives and images is hard to ignore. That’s exactly what you did at Sentera: you created a solution for that customer. One of the coolest parts of Field Agent early on was the API connectivity. A lot of imagery and massive amounts of data lived in Field Agent, but it could be easily sent to John Deere Operations Center and visualized there without jumping back and forth. That made it easy for customers or ag service providers to leverage the platform and integrate it into their existing workflows. It’s great to see how Field Agent has grown from that early version into what it is today.
Eric: You’re totally right. I think we were one of the very first API-integrated partners with Operations Center, and I think we were actually the first to send in drone data — and maybe even non-John Deere originated imagery. It was trailblazing. Like you said, I remember the first product we did was a basic stand count. We would sample the whole field and show the stand in a 30-yard by 30-yard grid. It was cool — you could bring it into Operations Center and see the stand. But then one of the engineers on the Operations Center team down at ISG in Urbandale, Iowa, overlaid the as-planted map with our stand count. Suddenly, it wasn’t just stand count — it was the percentage of seed the farmer put in the ground that actually emerged. That’s what the farmer really cares about. That was one of those “wow” moments for us about the power of a platform that brings together all of these relevant data streams — machine data, weather data, Sentera data — to provide the agronomist and grower with meaningful insights.
Tony: Exactly. You bring together the machine data, the as-applied machine data, and pair it with what the UAV is seeing as an emerged stand count. Connections can be made because one piece is the planter, the other is the seed. The planter might report one thing, but the actual seed or weather may tell another story. Being able to utilize all those data layers and draw conclusions helps growers, agronomists, and ag service providers improve operations. It’s all about making operations more efficient, productive, and profitable.
Now, I know there’s something coming down the pipe that I’m really excited to talk about — and it ties into the John Deere acquisition. Kevin, we’re not forgetting about you. We’ll bring you in here. But before we dive into the acquisition, let’s talk a little about SmartScripts Weeds.
Eric: Sure. We’ve talked about direct georeferencing technology, the efficiency it brings to field coverage, and Field Agent as the platform. Sentera has, I’d say, 10–15 really relevant analytics products across the growing season. SmartScripts stands out because of its potential economic value and value creation.
Here’s how it works: we fly the field and capture very high-resolution imagery — roughly 1.5 mm per pixel — across every square inch of the field. The data is processed through a pipeline that segments crop versus weed, and can even differentiate between broadleaf and grass weeds. Within broadleafs, it can identify species like amaranth. All of this processing happens in less than four hours. So, less than four hours after arriving at a 100-acre field, the agronomist or grower gets a map showing the exact location of every weed at ¼-inch size or larger.
It’s precise enough to load a prescription into an ExactApply sprayer, turning it into a selective application system. There’s less herbicide used, and the agronomist knows exactly the right mix and volume for that field. This early access program has been rolling out over the last two years, and we’re seeing spectacular results — both in grower outcomes and in cost savings.
People often ask how See & Spray fits in with SmartScripts. See & Spray is a vision-based, machine-selected application system — one of the best for minimizing chemical use in the field. SmartScripts complements it by helping the retailer or agronomist know exactly how much to put in the tender to keep that sprayer running efficiently. Think of it like Southwest Airlines keeping a 737 in the air 18 hours a day — SmartScripts keeps the machine productive, making every pass more precise. SmartScripts Weeds is the first of many products like this, but it’s the one I get most excited about because it differentiates Sentera technology, complements John Deere systems, and — most importantly — improves grower profitability and agronomic outcomes. So I just love the product.
Tony: Yeah, this is another one of those things that I — and that is the question we get. John Deere has See & Spray, and I'm coming to you next, Kevin, for the burning question that we always get. But adding SmartScripts to whether it's a See & Spray sprayer or not, this is another one of those tools. And I like to think of it like— we in the ag industry, or our customers, or the industry in general— we always like to think that there's a Swiss Army knife, a one-size-fits-all or one-tool-answers-all solution. But it's really not the case. We need more tools to be able to do more things. So SmartScripts being an awesome complementary tool to See & Spray, or for the customers that don't have See & Spray, being able to use this technology — Yeah, everything you said, Eric, is great to hear, and it's very exciting to see SmartScripts being tested, being rolled out.
Now I want to go to Kevin, and this is from the John Deere side of things. The question we always get — or we got back in May of this year, 2025, when John Deere announced this acquisition — SmartScripts kind of teases it a little bit. But the question we always got was: Why did John Deere purchase a drone company or a sensor company? What is the story behind this?
Kevin: Tony, it's a great question. And when you think about it—Eric alluded to it before—but one of the things that makes this space so interesting, so compelling as it relates to AgTech, is just the huge number of problems customers face, the enormous complexity of the decisions they need to make every growing season, and then just the sheer number of variables around weather and terrain and all of these different things that come together. One of my favorite conversations when we start talking with customers is the: How do I know that? And it's a: How do I know that taking a specific action would improve my profitability, or make me more efficient, or more sustainable? And the: How do I know that I took that action and I actually did a better job? So when we step back and think about that space and those challenges, from a John Deere perspective, we are constantly striving to bring tools to the toolkit of our customers and their trusted advisors—to be able to capture and use data and insights to make better decisions that allow them to whittle away at those variables and drive the outcomes they're looking for. And for us, when we look at Sentera—and Eric mentioned it—we’ve had a long history of working with Sentera, both as a customer and a partner over a variety of years. Really getting a deep understanding of the people, the product, and the technology helped us understand how we can use this high-resolution, highly precise data to empower growers and their advisors to make better decisions.
Eric mentioned a couple of these use cases. You look at: How do I know if I should deploy this piece of equipment to a field? Or: Is this field ready for a field-specific application? Or: How do I know that I used this technology in a field and got a better outcome—a better approach and a more uniform stand? We feel that this is the kind of technology—specifically from Sentera—that’s another tool in the grower's toolkit to be able to rapidly capture that data, get it into a format that can be visualized and interpreted in the Field Agent and Operations Center, and ultimately drive better decisions and outcomes for customers.
Tony: So that brings me to my next question. Eric, from your side — being one of the originals with Sentera — what goes through your head when, obviously, you guys have had that connection, that partnership with John Deere for many years leading up to the acquisition?
But what does Sentera think when a company like John Deere — someone you've been working with, someone you've partnered with — says, Hey, we are interested in this acquisition. What goes through your mind on: Okay, where do we take this from here?
Eric: Probably don’t want to make this into a commercial for John Deere, but I can’t help myself. Honestly, for our team — our team had such a strong belief in the power of this flavor of data augmenting and interoperating.
Tony: Yeah, and this acquisition — I know when it was announced back in May of 2025 — it just really goes to show John Deere’s mission to provide more solutions, more tools, more technology.And the one thing I love about being a John Deere dealership is — John Deere is not taking their foot off the gas. It makes us excited from a dealer standpoint to see these technologies, see these solutions, and see these partnerships that — in this case — turned into an acquisition. Because it shows the drive, the effort, the want, and the desire to bring more solutions to the ag industry, to the John Deere customers of the world. So it’s very exciting on our end of things.
The last question I want to leave — and I actually want to get both of your takes on this — and let’s go back to you, Kevin first: Where does it go from here? Now we’ve got John Deere acquires Sentera. John Deere has solutions like SmartScripts, the See & Spray, everything like that. Where do John Deere and Sentera take UAV-based imagery, and where do we go into the future?
Kevin: Yeah, it’s a great question. And as you heard Eric mention, there is no shortage of interesting and challenging problems that this technology can be applied to. I think for us, as we look toward the future, we’re looking very hard at a few different things. One of which is — again — how can we continue to expand the capability set and the data sets that we provide to customers, so that they can make more informed decisions about upcoming production steps. And also think about using this industry as a way to assess work that has been done at a very high-resolution level — to understand, quantify, and attribute value to the decisions that they make. That can apply across a variety of product and production decisions and production sets. We also think — as we look toward the future — of a world where this technology continues to become more accessible, continues to become easier to use, and more integrated into the daily workflows of customers. How can we continue to harmonize not only the place where they look at, find, and interact with this insight, but also the way that data is captured?
We’re thinking about ways in which this technology can improve — to continue making it easier, simpler, and remove friction from the process — to have high-resolution, highly accurate, multispectral geospatial RGB imagery taken of a field, and ultimately convert that into a decision that can be taken today on what to do.
Tony: I think you summed it up very well there, Kevin, on where John Deere wants to take this into the future. Eric, from a data-driven mindset and from being on the original Sentera team — do you have anything else to add on where this goes in the future, and what you are most excited about going down this path as a member of the John Deere team?
Eric: Yeah, I just echo what Kevin said — the power of the Operations Center, the integrated platform — to bring all of this power to the grower. To give the grower the best near real-time ability to manage their fields, understand exactly what’s going on, plan their job sets, optimize their job steps, and do it all with the best data available.
That’s our mission. We’re going to take cost, we’re going to take complexity out of that, and we’re going to give the grower just that vision of near-continuous surveillance of their growing operation — and the tools to make the most profitable and the best agronomic decisions. That’s our mission.
Tony: Kevin, I’ll leave this last question for you. We talked a lot about the different Sentera offerings. We talked about what’s coming with SmartScripts and how it pairs so well with the John Deere sprayers on the market. Where can someone go — if they want to learn more, maybe they’re interested in some of the solutions for a purchase? Where can they go, who can they talk to?
Kevin: I would encourage folks who are interested to learn more — visit Sentera.com, where you can find a variety of information. Not only about the SmartScripts offering that Eric talked through, but also our FieldAgent platform and the analytics that can be provided through it, as well as a link to our sensor portfolio for a more in-depth look at the specific sensors we offer and how to purchase those.
As you described — there’s a wide array of applicability of this onto Deere equipment and really helping meet customers where they’re at. So we would always encourage folks to go to their John Deere dealer as well, to learn about ways in which they can use the Sentera Insight — for example, with a SmartScript offer — and take advantage of technology they may already have on their equipment, or talk about new equipment as well.
Tony: Eric and Kevin, thank you both for taking the time to sit down and chat about everything Sentera and John Deere have to offer with UAV and aerial imagery. I really appreciate it.
Eric: Thank you, and anytime.
Kevin: My pleasure, Tony. Thanks.
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Tony Kramer
Tony Kramer is the Product Manager of Planting Technology and a Certified Crop Advisor at RDO Equipment Co. He is also the host of the Agriculture Technology podcast. If you have any questions for Tony or would like to be a guest on the podcast, email agtechpodcast@rdoequipment.com, or connect with him on LinkedIn.
