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Animals.ai
Lund, Sweden
1-10 Employees
2019
At Animals Ai, we’re dedicated to empowering farmers with AI-driven solutions for better livestock management. Learn how our services, from feed monitoring to calving, are making a difference in the industry. At Animals AI, we envision a future where every farm animal is given the opportunity to express their natural behaviors, live in comfort, and enjoy good health, all within the bounds of our planet. Our goal is to create a world where farming practices not only respect the five freedoms of animal welfare but also contribute positively to the health of our planet. Our solution provides 24/7 monitoring of your livestock, interpreting your cows’ body language to address their individual needs and optimize resource use. We believe in the power of AI to transform animal-based agriculture, making it more sustainable and humane. Through our AI-driven solutions, we are committed to making this vision a reality, one farm at a time.
Core business
Join us in the AI revolution in farming!
NITARA (GormalOne LLP)
Mumbai, India
11-50 Employees
2017
NITARA is the one-stop artificial intelligence-powered solution for all businesses in the dairy ecosystem and dairy animal management. NITARA transforms businesses in the dairy industry, from farmers to service providers like milk collectors and veterinarians. Our solutions serve dairies, genetics companies, research foundations, NGOs, cattle feed suppliers, and more. Government bodies involved in animal husbandry and farmer development can also benefit from our technology and data intelligence. With our years of research on the Dairy Ecosystem, we realized that dairy farmers face endless difficulties in ensuring a healthy cattle lifecycle, which is directly proportional to the milk yield at their farm and thus the revenue they make from it.
Core business
NITARA | Building AI Led Smart Dairy Farming Platforms | India
AquaEasy Indonesia (A Bosch Company)
Special Capital Region of Jakarta, Indonesia
51-100 Employees
2017
We are pioneers in AIoT Aquaculture, innovating to sustainably feed the world and protect the planet. The existence of AquaEasy technology certainly helps, especially with AI which makes it very easy to determine the actions that can be taken. AquaEasy help to improve productivity due to good water management. AquaEasy has helped us manage our cost better through the monthly subscription model. With AquaEasy, it saves a lot of manual efforts in checking the water quality. We are now able to make better and faster decisions in detecting and providing remedy to the problems. To explore AquaEasy's capabilities, you can request a demo or initiate a conversation with our team through chat. We are here to assist you in making an informed decision regarding AquaEasy pricing.
Core business
AquaEasy - The Best AI Platform for Shrimp Farming
EYC Labs
Denver, United States
11-50 Employees
2017
EYC Labs is the world’s only Agriculture Technology company providing clients with 100% in-house, custom IoT and AI product Design, Development and Manufacturing. Whether you seek to enhance your existing product, bring your prototype to market, or develop a new solution, EYC Labs is your trusted agriculture technology design and engineering partner. Its tailored features cater to the needs of service providers, farmers, and other stakeholders, enabling informed decision making and optimized financial performance. The delivered Active Asset Tracking solution harnesses cutting-edge technologies such as GPS, NB-IoT, BLE, and RFID, to provide real-time insights into asset location and underlying data, providing full visibility into both the physical and digital state of an object- physically living or as a consumer good. The AI Camera-based Quality Control and Real-time Revenue Forecasting product harnesses the power of AI and Camera technology to offer businesses a robust, closed-loop solution for a) viewing the current-state of an observed object and b) making real-time changes in the farm or facility to automate profitability. Combining advanced AI algorithms both on-camera and on-cloud allows for systems real-time product quality analysis and precise revenue control by limiting expense controls such as electricity, water, and nutrients. The Indoor-Outdoor Movable Weather Station solution was delivered fully equipped with advanced sensors and instruments for monitoring and controlling indoor and outdoor environments across a range of conditions.
Product
IoT and AI Smart Farming
Arugga AI Farming
Even Yehuda, Israel
1-10 Employees
2017
Arugga develops ground robots to treat and monitor individual plants in the greenhouse. Meet Polly, Arugga's robotic platform which will support several modules: robotic pollination, plant lowering, non-contact pruning and pest & disease detection. Arugga is proud to bring to the market a solution which will eventually reduce the use of chemicals and the spread of diseases in fruit and vegetable farming, and thus contribute to a healthier and safer planet.
Product
Technology — Arugga AI Farming
Critical Future
London, United Kingdom
11-50 Employees
2014
Healthcare – We are advising a venture capital funds, on their investment strategy, specifically focused on Sustainability & Longevity. We are developing Collective AI, just like how humans are smarter when we form teams, organizations, and nations, so too are machines smarter collectively. Critical Future is the trusted strategic advisor and AI partner of the world’s biggest brands, but we dedicate ourselves equally to social and environmental causes; achieving triple bottom line; economic, ecological and social. Critical Future is passionate about Transforming Tomorrow through our values:. We believe Sustainable Leadership is needed now more than ever:. Reducing carbon emissions is part of it, but it also means linking to:. Critical Future currently helping a charity founded by former gang member, which focuses on helping inner city youth relinquish knife crime, to scale their model across the UK. Critical Future has supported a multitude of innovative healthcare companies to grow, internationalize, and expand.
Service
AI Precision Farming
NeuroSYS
Wrocław, Poland
51-100 Employees
2010
An AR platform for remote collaboration with experts, interactive work instructions, and hands-on training – that you will create with ease.
Service
AI in aquaculture farming
ANOLYTICS
Noida, India
251-500 Employees
2016
We develop AI training data for computer vision systems. Anolytics is recognized for its high-quality, cost-effective, and timely training data delivery with an output accuracy exceeding 99.99%. Anolytics envisions to be of immense help to industries by unfolding the potential of artificial intelligence (AI) and machine learning (ML) with its expertise in analyzing large volumes of unstructured data. Anolytics has been an incredible aid for automating business & industrial processes with AI integration across an array of industries, e.g., manufacturing, food, healthcare, travel, real estate, entertainment, retail & e-commerce, logistics & transportation, and banking & financial services. Our mission is to provide businesses with the needful backing of high-quality and precision-bound AI training data optimized through our data annotation and labeling expertise. We are certified with SOC 2 TYPE 1 Company for maintaining the high standards of data security with privacy while working with our clients to ensure their confidentiality. Anolytics is among the top AI training data companies with a full-stack of developers having a knack for data annotation, labeling and natural language processing (NLP). We are recognized for its high-quality, cost-effective and timely training data delivery with an output accuracy exceeding 99.99%.
Product
Training Data for Agriculture Industry | AI in the farming
Levante Capital
Milan, Italy
1-10 Employees
2020
These opportunities span across three vital verticals, namely Advanced Manufacturing, Life Science, and Energy & Environment. A move marking the company’s continued commitment to leading the frontier of AI-driven innovation and simulation in life sciences.
Product
Cynomys — Levante Capital
XT Hi-Tech
Tel Aviv-Yafo, Israel
- Employees
1997
When partnering, we see it as our mission to make the management teams as successful as possible, supporting them with capital, a broad network of connections, operational knowhow, and 24/7 advice - all based on decades of experience in taking companies from any stage to category leadership. Alongside serving as the Group’s VP HR, Lital supports XT Hi-Tech and its portfolio companies with various aspects relating to recruitment, retention, welfare, career development, and organizational culture. Assif is a serial entrepreneur at heart, with over twenty years of experience in the software and healthcare industries. Prior to Yozma, Yoav served as a project manager at one of Israel's leading commercial banks. Our track record empowers us to invest in those companies we believe will be the next category leaders – even in categories that are still under construction…. We invest only in companies where we are as excited about their mission as the management teams - and we are all super excited. We believe in true partnerships, so before joining we try to learn how we can work together all the way, through highs and lows that are always part of the journey. We believe this is key for a healthy, long-term partnership.
Core business
Plant AI-based digital farming productivity platform
Technologies which have been searched by others and may be interesting for you:
Some interesting numbers and facts about your company results for AI Farming
| Country with most fitting companies | United States |
| Amount of fitting manufacturers | 1236 |
| Amount of suitable service providers | 1117 |
| Average amount of employees | 1-10 |
| Oldest suiting company | 2011 |
| Youngest suiting company | 2020 |
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AI Farming refers to the integration of Artificial Intelligence (AI) technologies into agricultural practices to enhance efficiency, productivity, and sustainability. This innovative approach utilizes data analytics, machine learning algorithms, and IoT (Internet of Things) devices to monitor crop health, manage resources, and predict agricultural outcomes with high precision. By analyzing vast amounts of data collected from various sources, such as satellite images, soil sensors, and weather forecasts, AI algorithms can provide actionable insights for farmers. These insights include optimal planting times, water management strategies, and pest control measures, thereby reducing waste and maximizing yield. AI Farming also plays a crucial role in precision agriculture, enabling farmers to apply the exact amount of water, fertilizers, and pesticides needed, tailored to each plant's requirements. This not only cuts down on costs and resource consumption but also mitigates environmental impact by reducing the excessive use of chemicals and water. The adoption of AI in farming represents a significant shift towards more data-driven and automated agricultural practices, promising to revolutionize the way food is grown, with the potential to greatly improve food security and sustainability in the face of a growing global population and changing climate conditions.
1. Precision and Efficiency
AI farming technologies enable the precise application of water, fertilizers, and pesticides, reducing waste and increasing crop yields. This precision farming approach leverages data analytics and machine learning to optimize resource use, ensuring that crops receive exactly what they need for optimal growth.
2. Reduced Labor Costs
By automating routine agricultural tasks such as planting, weeding, and harvesting, AI farming significantly reduces the need for manual labor. This automation not only cuts down on labor costs but also allows farmers to manage larger areas of land more effectively, leading to increased productivity.
3. Enhanced Crop Monitoring and Management
AI-powered drones and sensors can monitor crop health in real-time, providing farmers with detailed insights into their fields. This information allows for quick identification and addressing of issues such as pest infestations or nutrient deficiencies, ultimately improving crop health and yield.
4. Sustainability
AI farming promotes sustainability by optimizing the use of resources and reducing the environmental impact of farming practices. Through data-driven decision-making, it ensures that agricultural activities are more aligned with environmental conservation efforts, contributing to the long-term health of our planet.
While evaluating the different suppliers make sure to check the following criteria:
1. Technological Expertise
Ensure the supplier has proven experience in AI technologies relevant to agriculture, like machine learning and data analytics, to optimize farming practices.
2. Customization Capabilities
The ability to tailor solutions to fit specific farm needs, including crop types, farm size, and environmental conditions, is crucial for maximizing efficiency and outcomes.
3. Integration Flexibility
Check for compatibility with existing farm equipment and software systems to ensure a seamless integration of the AI solutions into current operations.
4. Scalability
The supplier's solutions should be scalable, allowing for adjustments in operation size or capacity without significant disruptions or excessive costs.
5. Support and Maintenance
A reliable support system for troubleshooting, regular updates, and maintenance services is essential to ensure continuous and smooth operation of AI technologies.
6. Sustainability Focus
Prefer suppliers that emphasize sustainable farming practices through their AI solutions, contributing to environmental conservation and long-term agricultural viability.
AI farming is revolutionizing how businesses in agriculture and beyond approach productivity and sustainability. One significant use case is in precision agriculture, where AI analyzes data from satellite images and sensors in the field to optimize planting, watering, and harvesting. This technology enables farmers to make data-driven decisions, significantly increasing crop yields while reducing water and chemical usage. Another area where AI farming is making strides is in livestock management. By monitoring the health and behavior of animals through AI-driven systems, farmers can detect early signs of illness, improve breeding outcomes, and enhance overall herd management. This not only boosts productivity but also ensures higher standards of animal welfare. In the supply chain and logistics sector, AI farming contributes to more efficient distribution processes. Predictive analytics help in forecasting demand more accurately, managing inventory levels, and optimizing delivery routes. This reduces waste and ensures that perishable goods reach the market in optimal condition, benefiting both suppliers and consumers. Lastly, AI farming supports sustainable farming practices. Through detailed analysis of environmental data, AI can assist in developing farming strategies that maintain or increase productivity without depleting resources, thereby supporting long-term ecological balance. This is crucial for industries aiming to meet sustainability goals while addressing the growing global food demand.
AI farming, a revolutionary approach that integrates artificial intelligence into agriculture, currently hovers around a Technology Readiness Level (TRL) of 6 to 7. This classification is indicative of the technology having been tested in a relevant environment, showcasing its efficacy and potential benefits on a somewhat broader scale. The progression to these levels is primarily due to significant advancements in machine learning algorithms and data analytics, which have proven instrumental in making precise predictions about crop health, weather patterns, and soil conditions. These AI systems are now capable of autonomously adjusting farming parameters for optimal plant growth, demonstrating a high degree of automation that was not previously achievable. However, the reason AI farming has not advanced to the highest TRLs, 8 or 9, which involve actual system completion and full commercial deployment, lies in the existing barriers to widespread adoption. These include the high initial costs of implementing AI technologies, the need for robust digital infrastructure in rural areas, and the ongoing requirement for large datasets to train AI models effectively. Furthermore, there's a significant learning curve and resistance among traditional farmers to adopt such advanced technologies, which also plays a role in its current TRL positioning. Despite these challenges, the technical feasibility and successful pilot programs of AI farming underscore its potential to revolutionize agriculture in the near future.
In the Short-Term, AI Farming is set to experience significant enhancements in precision agriculture. Technologies such as AI-driven drones and sensors will become more widespread, offering farmers real-time insights into crop health, soil moisture levels, and pest presence. These advancements aim to improve immediate decision-making on the farm, optimizing resource use and increasing crop yields with minimal environmental impact. The Mid-Term phase will witness the integration of AI with robotic systems for automated planting, weeding, and harvesting. This period will see AI algorithms becoming more sophisticated, capable of learning and adapting to various farming conditions and crop requirements. The fusion of AI with robotics will not only reduce the reliance on manual labor but also push the boundaries of precision in farming operations, ensuring each plant receives exactly what it needs to thrive. Looking into the Long-Term, AI Farming will evolve towards fully autonomous farm ecosystems. AI will manage entire operations from sowing to harvesting, powered by advanced machine learning models that can predict weather patterns, crop diseases, and market demands with high accuracy. These smart farms will operate in a near-autonomous manner, significantly enhancing food security and sustainability by optimizing every aspect of the farming process, from resource management to distribution logistics, based on real-time data and long-term environmental considerations.
Some interesting questions that has been asked about the results you have just received for AI Farming
What are related technologies to AI Farming?
Based on our calculations related technologies to AI Farming are Big Data, E-Health, Retail Tech, Artificial Intelligence & Machine Learning, E-Commerce
Who are Start-Ups in the field of AI Farming?
Start-Ups who are working in AI Farming are
Avega Capital Management S.A.,
Aether Intelligence
Which industries are mostly working on AI Farming?
The most represented industries which are working in AI Farming are IT, Software and Services, Other, Agriculture, Finance and Insurance, Marketing Services
How does ensun find these AI Farming Companies?
ensun uses an advanced search and ranking system capable of sifting through millions of companies and hundreds of millions of products and services to identify suitable matches. This is achieved by leveraging cutting-edge technologies, including Artificial Intelligence.
