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Farmio.ai
Cluj-Napoca, Romania
B
1-10 Employees
-
Key takeaway
FARMIO utilizes AI to provide continuous market monitoring, delivering real-time Buy and Sell signals through a private Telegram Channel. Their AI-powered trading bots perform advanced technical analysis, enhancing trading efficiency and decision-making.
Reference
Core business
header – FARMIO.AI
Farmin
Abu Dhabi, United Arab Emirates
C
1-10 Employees
2019
Key takeaway
Farmin is an Emirati tech company focused on integrating Artificial Intelligence into sustainable development across various sectors in the UAE and MENA Region. They offer AI-powered solutions and utilize advanced geospatial data and remote sensing to enhance productivity and efficiency.
Reference
Core business
Farmin AI - Shaping the future with AI
Shaping the future with AI. The largest Artificial Intelligence Data Center and Server in the MENA Region
AI IT SERVICE LTD
London, United Kingdom
A
1-10 Employees
2011
Key takeaway
AI Services is a farmer-owned company with a strong commitment to agriculture, boasting around 2,500 farmer shareholders.
Reference
Core business
About AI Services Northern Ireland Ltd
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Ullmanna
Opava, Czechia
A
1-10 Employees
2019
Key takeaway
Ullmanna specializes in advanced AI solutions for agriculture, offering innovative technologies for plant detection and efficient weeding. Their systems, designed by farmers for farmers, promise significant cost savings and adaptability for various crops and farming conditions.
Reference
Core business
Ullmanna | Artificial Intelligence for Agriculture
Next generation AI solution and computer vision for weeding machines in agriculture | Helping farmers save 80 % of weeding costs
FarmwiseAI
Chennai, India
D
11-50 Employees
2021
Key takeaway
FarmwiseAI is a geospatial startup focused on transforming agriculture through innovative technology. Their Agri Bureau platform provides farmers and agribusinesses with actionable insights and real-time data on crop health and yield potential, empowering them to make informed decisions and optimize operations for sustainable farming practices.
Reference
Core business
FarmwiseAI
The AI Team
Kajugahawatte, Sri Lanka
C
11-50 Employees
2018
Key takeaway
The AI Team offers a wide range of AI services, including AI strategy development and solutions engineering, which could be integral to advancing AI farming initiatives. Their expertise in delivering industry-standard platforms and training ensures comprehensive support for projects that leverage AI technologies.
Reference
Service
The AI Team | Services
AI Grow LLC
Stillwater, United States
B
1-10 Employees
-
Key takeaway
AI Grow offers custom-developed automation solutions and data collection tools that optimize operations and enhance plant health, making it highly relevant for AI farming. Their system allows for efficient control and monitoring of essential growing conditions through a user-friendly interface, ensuring maximum yields and profitability.
Reference
Core business
Home | AI Grow: Innovative Solutions for Controlled Growing Environments
AI Grow provides integrated automation solutions for controlled growing environments. Streamline your greenhouse or indoor grow using one clean interface.
SmartCloudFarming
Berlin, Germany
A
1-10 Employees
2018
Key takeaway
SmartCloudFarming is a Berlin-based company that leverages advanced AI and deep neural networks to provide agricultural companies with rapid and accurate soil intelligence, significantly enhancing soil analytics and reducing overhead costs. Their innovative approach enables the monitoring of large areas at unprecedented speeds, transforming traditional soil sampling methods.
Reference
Product
Solutions - SmartCloud Farming
Reduce your overheads by a factor of 10.Satellite images, A.I. and our know-how give you the most advanced soil analytics solutions.
AIW - Artificially Intelligent Workforce
Gurugram District, India
D
11-50 Employees
2021
Key takeaway
AIW has significantly enhanced operational efficiency by automating critical processes, allowing employees to focus on more strategic tasks. This automation not only saves time but also enables the company to handle increased transactions effectively, which could be beneficial in the context of AI applications in farming.
Reference
Core business
AIW | Artificially intelligent workforce
AitecServ
Lisbon, Portugal
A
1-10 Employees
-
Key takeaway
AiTecServ offers comprehensive Data Science services that include the development of trained machine learning models, which can be instrumental in enhancing agricultural practices through automation and AI. Their expertise in machine learning for applications like flood and fire detection showcases their capability to utilize advanced technologies for effective problem-solving.
Reference
Product
AiAction | AiTecServ
Technologies which have been searched by others and may be interesting for you:
AI farming refers to the integration of artificial intelligence technologies in agricultural practices to enhance productivity and efficiency. This innovative approach utilizes data analytics, machine learning, and automation to optimize various farming processes. For instance, AI can analyze soil conditions, monitor crop health, and predict weather patterns, enabling farmers to make informed decisions. Furthermore, AI-driven solutions such as drones and autonomous tractors are increasingly being employed to streamline tasks like planting, irrigation, and harvesting. By leveraging AI farming, agricultural providers can significantly reduce costs, minimize environmental impact, and improve yield quality, making it a transformative force in modern agriculture.
AI Farming utilizes advanced algorithms and machine learning to analyze vast amounts of data related to soil health, weather patterns, and crop performance. By leveraging this data, farmers can make informed decisions about planting schedules, irrigation needs, and nutrient management, leading to optimized growth conditions. Additionally, AI-driven tools can predict pest infestations and diseases before they become significant threats, allowing for timely interventions. This proactive approach not only enhances crop resilience but also maximizes yield potential by ensuring that each plant receives the care it needs at the right time.
AI Farming utilizes a combination of advanced technologies to enhance agricultural practices. Machine Learning algorithms analyze vast amounts of data from various sources, improving decision-making regarding crop management and resource allocation. Additionally, Internet of Things (IoT) devices, such as sensors and drones, collect real-time data on soil conditions, weather patterns, and crop health. This data is then processed to provide farmers with actionable insights, ultimately leading to increased yields and sustainable farming practices.
AI Farming significantly enhances sustainability in agriculture by optimizing resource use and minimizing waste. By employing advanced data analytics and machine learning algorithms, AI systems can monitor soil health, crop conditions, and weather patterns in real-time. This allows farmers to make informed decisions regarding irrigation, fertilization, and pest control, ultimately reducing the overuse of water and chemicals. Furthermore, AI Farming facilitates precision agriculture, which ensures that inputs are applied only where needed, leading to higher yields with less environmental impact. The integration of AI tools promotes more efficient farming practices, helping to conserve biodiversity and improve soil quality, making agriculture more resilient to climate change.
AI Farming faces several challenges that can impact its adoption and effectiveness in agriculture.
1. Data Quality and Availability
The success of AI applications in farming largely depends on the quality and quantity of data available. Inconsistent or incomplete data can lead to inaccurate predictions and poor decision-making.
2. Integration with Existing Systems
Many farms rely on traditional methods and legacy systems. Integrating AI technologies into these existing frameworks can be complex, requiring significant investments in infrastructure and training.
3. Cost of Implementation
Implementing AI solutions can be cost-prohibitive for smaller farms. High initial costs for technology and ongoing expenses can deter adoption among farmers with limited budgets.
4. Skill Gap
There is often a lack of technical expertise in the agricultural sector. Farmers may struggle to understand and utilize AI tools effectively, which can hinder the potential benefits of these technologies.
5. Regulatory and Ethical Concerns
As AI technologies evolve, so do concerns about data privacy, security, and ethical use. Navigating these regulatory frameworks can be challenging for providers and farmers alike.
Some interesting numbers and facts about your company results for AI Farming
| Country with most fitting companies | United States |
| Amount of fitting manufacturers | 5458 |
| Amount of suitable service providers | 5468 |
| Average amount of employees | 1-10 |
| Oldest suiting company | 2011 |
| Youngest suiting company | 2021 |
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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 FarmwiseAI, AIW - Artificially Intelligent Workforce
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, Marketing Services, Human Resources
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.
