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About Cromai

Cromai is an AI-based software platform from Cromai that offers a complete portfolio of solutions for the agricultural sector. It provides solutions such as Cromai Scan Weed, Cromai Sentinel, and Cromai Scan Growline for effective identification, management, and monitoring of weeds, plant impurities, and more. This platform is designed to support agricultural professionals in improving crop yields and managing resources more efficiently. With advanced capabilities, Cromai's solutions assist in real-time data analysis and provide actionable insights to users. Key capabilities: weed identification plant impurity management real-time monitoring data analysis crop yield improvement Best for: agricultural professionals that need effective solutions for weed management and crop monitoring.

Cromai Details

Vendor
Cromai
Year Launched
2017
Location
Rua Cezira Giovanoni Moretti, 655 – Reserva Jequitibá, Piracicaba – SP, 13414‑157, Brazil
Deployment
cloud, ios, android
Training Options
Countries Served
Brazil
Languages
Portuguese
Users
Mid‑size to large agricultural operations, crop producers, sugar‑cane mills
Industries Served
Agribusiness, specifically sugar‑cane cultivation, large‑scale farming.
Tags
Farm Management, Agriculture, Cromai

Cromai's In-App Market Place

Does Cromai have an in-app market place?

Yes

How many Mini-Apps in the marketplace?

1

Mini Apps

N/A

Pricing Options

Free trial
Free version
Request a quote
Promo Offer

Accepted Payment Currencies

USD ($), EUR (€), GBP (£), AUD (A$), CAD (C$), JPY (¥), CNY (¥), RUB (₽), BRL (R$), MXN ($)

Pros & Cons

  • High precision weed detection enabling more efficient herbicide usage and cost reduction.
  • Rapid spray map generation reduces operational planning time significantly.
  • Scalable solution suitable for large agribusinesses and sugarcane mills.
  • Integrates AI, aerial imagery, and mobile guidance in a single platform for comprehensive management.
  • Real-time operational dashboards allow quick, informed decision-making.
  • Currently focused mainly on Brazil, limiting global support and adoption.
  • Requires drone infrastructure and aerial imagery, which may increase operational costs.
  • Dependence on internet connectivity for data processing and dashboard access may hinder remote use.
  • May require technical expertise to interpret AI-generated weed maps effectively.
  • Implementation may involve a learning curve for field operators unfamiliar with drone technology.

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