Costly hardware kept small farms from smart irrigation. Now, an AI agent uses satellite data to send free watering plans via WhatsApp.
An agricultural technology provider with proprietary sensor-based irrigation algorithms sought to expand its reach to the 90% of the world's farmers running small-scale operations.
Unpredictable climate change has made traditional irrigation methods ineffective, but small-scale farmers lack the resources and technical experience...
“Around 90% of the world’s farmers are running small-scale operations. Often, they have little experience with technology and lack resources to install hardware. By redesigning our technology to meet their needs, we aimed to help significantly raise crop productivity across the world.”
SupPlant's Irrigation recommendations is part of this use case:
AI-powered precision agriculture platform for sensor-based autonomous irrigation.
Enterprise technology and consulting for cloud computing, AI, and business solutions.
Related implementations across industries and use cases
Building a policy assistant in-house meant a six-month wait. With watsonx, they launched a secure Slack bot in just one month.
Manual review of sensitive files took two days. AI agents now finish the work in one hour.
Contract routing took 2 days of manual checks. AI now finishes in 60 minutes, escalating only complex exceptions for human review.
Single-source data gaps stalled global staffing. AI agents now aggregate 10+ providers to map the market in 2 weeks, not 2 months.
Reps lost hours manually assessing leads across disconnected systems. Now, AI agents evaluate intent and instantly route top prospects.
Moderation couldn't keep pace with 600M users. AI agents now filter toxicity while models recognize 2.5B objects to refine search.
Accountants manually scoured mailboxes to assemble 15 subsidiary workbooks. Now, staff-built AI agents pull invoice data for instant review.
Repetitive coding slowed R&D. Now 80% of engineers use agentic tools to automate work, saving up to 2 hours weekly per person.
Manual testing consumed 20% of developer time. Now, 1,500 engineers use AI agents to auto-generate tests and prototype solutions.
Costly hardware kept small farms from smart irrigation. Now, an AI agent uses satellite data to send free watering plans via WhatsApp.
An agricultural technology provider with proprietary sensor-based irrigation algorithms sought to expand its reach to the 90% of the world's farmers running small-scale operations.
Unpredictable climate change has made traditional irrigation methods ineffective, but small-scale farmers lack the resources and technical experience...
“Around 90% of the world’s farmers are running small-scale operations. Often, they have little experience with technology and lack resources to install hardware. By redesigning our technology to meet their needs, we aimed to help significantly raise crop productivity across the world.”
SupPlant's Irrigation recommendations is part of this use case:
AI-powered precision agriculture platform for sensor-based autonomous irrigation.
Enterprise technology and consulting for cloud computing, AI, and business solutions.
Related implementations across industries and use cases
Building a policy assistant in-house meant a six-month wait. With watsonx, they launched a secure Slack bot in just one month.
Manual review of sensitive files took two days. AI agents now finish the work in one hour.
Contract routing took 2 days of manual checks. AI now finishes in 60 minutes, escalating only complex exceptions for human review.
Single-source data gaps stalled global staffing. AI agents now aggregate 10+ providers to map the market in 2 weeks, not 2 months.
Reps lost hours manually assessing leads across disconnected systems. Now, AI agents evaluate intent and instantly route top prospects.
Moderation couldn't keep pace with 600M users. AI agents now filter toxicity while models recognize 2.5B objects to refine search.
Accountants manually scoured mailboxes to assemble 15 subsidiary workbooks. Now, staff-built AI agents pull invoice data for instant review.
Repetitive coding slowed R&D. Now 80% of engineers use agentic tools to automate work, saving up to 2 hours weekly per person.
Manual testing consumed 20% of developer time. Now, 1,500 engineers use AI agents to auto-generate tests and prototype solutions.