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scoutlabs

Agri-Sense provides an AI-powered platform that predicts insect pest populations to help farmers proactively protect their crop yields. By analyzing environmental data and pest trends, the platform enables early intervention strategies, minimizing crop loss and optimizing agricultural productivity.

Traction 10/10
HQ unknown
Founded 2022183K+ followers
  • Agriculture Technology
  • Artificial Intelligence
  • Data & Analytics
  • Hardware
  • Internet of Things
  • Software Only
Updated 18 months ago

Funding

Raised to date

$2MRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.

Funding rounds are not available yet.

Founders

1 founder

Jimmy Fong

Helping millions of farmers worldwide in predicting insect pest populations before they destroy their crop yield

Product

Problem

Manual insect pest monitoring is labor-intensive, costly, and often provides questionable data, leading to inefficient pest control and potential yield loss for farmers. Existing digital solutions can be prohibitively expensive, especially for growers with tight margins.

Solution

Scoutlabs provides an affordable and scalable digital insect monitoring solution that transforms existing manual traps into smart traps. By retrofitting standard pheromone traps with a camera-based IoT device, Scoutlabs captures daily images of trapped insects and transmits them to a cloud server. Proprietary image-recognition algorithms differentiate insect species, and an agronomist team validates the data to ensure high accuracy. Farmers can then access visualized data on their mobile devices, enabling them to make informed decisions about pest control and optimize spraying plans, reducing both labor costs and pesticide use.

Target Audience

Scoutlabs targets growers of specialty crops such as almonds, pistachios, grapes, and apples, as well as PCAs, researchers, and manual trap network operators seeking to reduce labor costs, improve data accuracy, and optimize pest management strategies.

Features

  • Camera-based IoT device that retrofits existing delta pheromone traps
  • Automated image capture and transmission via low-bandwidth cellular connectivity
  • AI-powered image recognition for insect identification, validated by agronomists
  • Mobile app for real-time data visualization of pest pressure and trends
  • Integration with existing farm management software via API
  • Affordable subscription model with no upfront hardware costs
  • Delta trap design optimized for accuracy and efficiency with AI models
  • Automated health checks to ensure proper trap function
This profile is AI-generated and may contain inaccuracies.