what is it?
Arber AI is a platform that leverages on computer vision and analytics to transform your data into simple visualisations for strategic and forecasted insights of the farm
User Problems
1
Difficulty in Operationalising AI and Analytics Findings
Teams often find analytics and operational processes operating in isolation, even though these processes are critical in promoting constant research and development within the product
2
User Problem: Lack of Analytics Coding Expertise
Experts often rely on traditional techniques for their analysis, as they lack the skillset to make use of analytics to make their work more efficient and comprehensive
3
User Problem: Lack of Means to tackle Multi-Faceted issues rapidly
Tackling such issues often relies on having several solutions. Therefore, rapidly producing solutions is key. However, due to the lack of resources and tools, teams are often forced to focus on one solution at a time
key features
forecast analysis
Arber AI can analyse past trends and predict future outcomes for use cases such as crop yield and customer demand
data visualisation
Use charts analysis to understand relationships between conditions and crop yield
Use crop images to identify irregularities such as pest or diseases
Applications
video/image analytics (vegevision app)
The app is designed to predict environmental values in advance and alert users based on baseline profiling and rules settings
environment optimisation
The app is designed to monitor plant health via image analytic techniques
recipe optmisation
The app is designed to allow users to customise their recipes to achieve desired outcomes
hr scheduler
The app is designed to help users plan for their day-to-day operations to improve productivity and utilisation of manpower
market intelligence
The app is designed to scrap information from the internet routinely to understand market prices
finance month end automation
The app is designed to automate some of the accounting tasks in order to reduce processing time
forecasting demand
The app is designed to predict expected sales based on factors such as seasonality and data scrapped from the internet
