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AI Agricultura Inteligente  


AI-Enabled Smart Irrigation:

People use irrigators to water plants or spray chemicals, but today, more modern irrigation systems with integrated ML technology can distinguish weeds from crops and spray the former with herbicides. That means less herbicide is applied and therefore lower costs and safer food.


Key Features

  • Robust & flexible system for Farm Management

  • Traceability & Output Predictability

  • Accountable & Efficient Operations

  • Standard package of practices

  • Alert Log & Management (pest infestation, diseases etc.)

  • Incorporates end-to-end solutions

  • Satellite and weather input based advisory

  • Crop reports & insights – easy reporting on-the-go

  • Geo tagging for accountability & accurate predictability

  • Adherence to Compliance & Certification

Satellites with AI:

With AI we can analyze satellite data and predict corn yields, through a proprietary machine learning algorithm that can identify the general condition of plants. As our society moves closer and closer to smart farming, the benefits and benefits are theoretically unlimited. The current results of smart farming applications are quite good. However, through artificial intelligence and mixed reality, we can go further.

  • Sensors: soil, water, light, humidity, temperature management

  • Software:  specialized software solutions that target specific farm types or use case agnostic IoT platforms

  • Connectivity: cellular, LoRa, etc.

  • Location: GPS, Satellite, etc.

  • Robotics: Autonomous tractors, processing facilities, etc.

  • Data analytics: standalone analytics solutions, data pipelines for downstream

Smart farming" is an emerging concept that refers to managing farms using technologies like IoT, robotics, drones and AI to increase the quantity and quality of products while optimizing the human labor required by production


Agricultural bots are specifically designed robots to implement automation in agriculture. In simple terms, they are efficient laborer's who work without sweating too much (or any sweat, actually). They are a blend of mechanics and software implementation that eliminates the need of manpower in the area of implementation.

Agriculture bots have been applied in every step of farming in recent times. From harvesting, weeding, potting, picking and spraying, the agri-bots have made life a little more easier for the farmers.


Self-driving combines are automated tractors that can function autonomously and most commonly known as ‘Driverless Tractors’. They deliver a high tractive effort without the presence of a human inside the tractor. They are programmed to be self observant, decide speed, and avoid obstacles such as people, animals, or objects in the field while performing their task.

Some of the driverless tractors work on supervised autonomy. They are automated tractors but with a supervisor and they use Vehicle-to-Vehicle (V2V) technology for communication and control. AI implementation into these self driving combines ensure safety in applications and to ensure they learn constantly through self observational data they collect.



This reduces accidents related to unmanned vehicles and increases productivity through technological intervention. Now, imagine empowering these autonomous vehicles with the power of artificial intelligence. AI-based algorithms would make them self evolving, self learning and self developing in terms of efficient decision making.


The farm management solutions, when combined with AI powered automation will result in wonders for farmers. While AI-based automation will ensure higher levels of productivity and create a self evolving system, the farm management solution will provide these systems with accurate data to make decisions on and monitor the entire process. Additionally, the farm management system will also act as a knowledge repository for the farmers and the actuators as well. An entire AI-based sustainable AMIGO IQ ecosystem can be created and the results on the farmland would be outstanding to say in the least.

Harnessing AI technology into farm machinery is what AMIGO IQ has been consistently working on, AMIGO IQ has leveraged its smart solutions to leading farm machinery enterprise giants to provide farmers digital tools and agricultural insights along with the farm machineries.


This will not only boost their productivity, but also educate them on better agricultural practices and provide quick aid and advisories on taking timely actions against unforeseen situations. AMIGO IQ has ensured the future of agriculture looks bright and shiny with its ever evolving systems and diverse applications. Artificial intelligence in farm machinery will be the icing on the cake that is AMIGO IQ – the real plough-t twist that is yet to come!


  • AVERAGE RETURN ON INVESTMENT :  11 x the cost of the Ai platform

  • AVERAGE EFFICIENCIES AND TIME SAVING:  X65 TO X150 the current process 

  • AVERAGE COST FOR Ai / Machine Learning / Big Data Preparation / RPA / Deep Learning : $100,000 to $138,750

  • Average length of project: 4 to 6 months


Key Features

  • Agri Alternate Data for accurate decision making

  • Reduced Cost of Operations

  • Lending :
    Effective Credit Risk Assessment
    Plot level Monitoring System

  • Insurance :
    Crop Risk Assessment at Region Level
    Risk Adjusted Variable Pricing



AMIOG IQ SMART FARM, is a Predictive and Prescriptive Solution for Risk Monitoring, Mitigation and Forecasting Intelligence. The AI and Machine-learning based platform detects cropping patterns and predicts the future of the crop, thus highlighting the associated risk and opportunity for agri-stakeholders. The businesses can achieve farm-level crop detection and yield prediction through the  capabilities that can also establish historical performance of every pixel at farm/postcode/state/country level by utilizing easy-to-use Connector APIs.

The agri stakeholders can improve the loan collection process, optimize the loan disbursement process, preemptively assess NPA, perform crop growth analysis to monitor risk in real time and expand lending portfolios to new regions with higher confidence.

Key Features

  • Farm to Fork traceability

  • Quality Control

  • Order to Fulfillment

  • Flexible Inventory Management

  • SKU tagging & traceability to the source

  • Order processing & tagging

  • Better Marketability

  • Enhanced Visibility


Key Features

  • End-to-end supply chain traceability

  • Patented, non-replicable QR code stickers

  • Customizable, tamper-proof, and weather-resistant labels

  • QR codes that can be scanned only using app to prevent counterfeiting

How do they empower agribusinesses?

  • Ensure brand credibility and increased consumer confidence

  • Develop, meet, and maintain quality standard for exports

  • Market certified brand of produce while preventing counterfeiting

  • Enable buyers to verify the authenticity of produce by scanning a unique QR-code

  • Fetch the right price for the producers with certifications of quality


We’re transforming businesses through intelligence and insight.


Simplified data gathering through a smartphone app that records activities & milestones. Ensuring efficient operations, lower costs and better visibility for your field agents at all times


Real-time actionable insights enable farm management companies to take planned & responsive business decisions. The predictability of quantity & quality of yield combined with reduced cost of operations results in higher productivity for the businesses


Meet today’s agri-needs while strengthening resources for the future by creating a healthy environment, economic profitability, and social & economic equity for all. Empowering the agri in the agri-ecosystem by enabling businesses to benefit from actionable insights while empowering farmers through advisory & alerts.


Precision Livestock Farming

As in the case of precision agriculture, smart farming techniques enable farmers better to monitor the needs of individual animals and to adjust their nutrition accordingly, thereby preventing disease and enhancing herd health.

The IoT-Based Smart Farming Cycle

The core of IoT is the data you can draw from things (“T”) and transmit over the Internet (“I”). To optimize the farming process, IoT devices installed on a farm should collect and process data in a repetitive cycle that enables farmers to react quickly to emerging issues and changes in ambient conditions. Smart farming follows a cycle like this one:

1. Observation 

Sensors record observational data from the crops, livestock, soil, or atmosphere. 

2. Diagnostics

 The sensor values are fed to a cloud-hosted IoT platform with predefined decision rules and models—also called “business logic”—that ascertain the condition of the examined object and identify any deficiencies or needs.

3. Decisions 

After issues are revealed, the user, and/or machine learning-driven components of the IoT platform determine whether location-specific treatment is necessary and if so, which.

4. Action 

After end-user evaluation and action, the cycle repeats from the beginning.


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