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The Complete AI Agronomist.

Beyond detection — AgriVision AI gives your crops a full treatment plan, environmental prescription, and a 90-day care roadmap, powered by state-of-the-art computer vision and AI reasoning.

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⚠ Alternaria solani — Early Blight
Tomato · Sector B-4 · Sample #T-2031 · 2025-10-09 00:52 KST
HIGH SEVERITY
98.4%
📊 Overview
💊 Treatment
🌡 Environment
📅 90-Day Care Plan
📈 Risk Forecast
62

Crop Health Score

Moderate stress. Fungal infection affecting 34% of leaf area. Immediate intervention required to prevent spread.

34%
Leaf Area Infected
Stage 3
Disease Stage (1-5)
5–7 days
Est. Spread Window
AI Reasoning Summary

Image analysis confirms Alternaria solani. Characteristic concentric ring lesions (5–12mm diameter) with yellow chlorotic halos detected on lower canopy leaves. Lesion density is highest in rows B-3 to B-6, suggesting humidity pooling near the drip line. Secondary bacterial co-infection risk is elevated (est. 28%). Without treatment, estimated yield loss in this sector: 40–60% within 3 weeks.

5-Step Treatment Protocol
1
Isolate affected rows immediately
Cordon off rows B-3 through B-6. Restrict worker movement. Disinfect all equipment entering and exiting the zone with 70% ethanol spray.
⚡ Do now (within 2 hours)
2
Remove and bag infected leaves
Prune all leaves showing lesions >3mm. Double-bag in sealed plastic and remove from field. Do NOT compost. This reduces primary inoculum by ~60%.
⚡ Do now (same day)
3
Apply fungicide: Mancozeb 75WP
Mix at 2.5 g/L. Apply as a thorough foliar spray covering both leaf surfaces. Repeat every 7 days × 3 applications. Do not apply within 7 days of harvest. Rotate to Chlorothalonil on 2nd cycle to prevent resistance.
⏰ Within 24 hours
4
Soil drench with Trichoderma harzianum
Apply beneficial biocontrol fungi at 5 g/L around the root zone. This outcompetes Alternaria in the soil, preventing re-infection via root uptake. Combine with phosphorus-rich fertilizer to boost plant immunity.
⏰ Within 48 hours
5
Reschedule AI scan for follow-up assessment
Schedule a rescan of sector B in 5 days to confirm treatment efficacy and adjust the protocol if needed. Early detection of resistance or spread is critical.
📋 Schedule (Day 5)
Environmental Prescription — Current vs Target

Early Blight thrives in warm, humid conditions. Adjusting these parameters is as important as the chemical treatment.

💧
Canopy Humidity
Current: 87% ⚠
Target: ≤ 70% — Increase ventilation / reduce irrigation
🌡
Daytime Temperature
Current: 29°C ⚠
Target: 22–25°C — Open vents 06:00–09:00 KST
🌬
Air Circulation
Current: 0.3 m/s ⚠
Target: 0.8–1.2 m/s — Enable oscillating fans
💦
Irrigation Frequency
Current: 3× / day ⚠
Target: 1× / day (morning only) — Reduce leaf wetness
☀️
Daily Light Integral
Current: 12 DLI ✓
Target: 14–18 DLI — Trim overhead shading net
🌱
Soil EC (Nutrient)
Current: 1.1 mS/cm ⚠
Target: 2.0–2.5 — Add K·P supplement to strengthen immunity
90-Day Crop Care Roadmap
Day 1–30

🚨 Active Treatment & Containment Phase

3× fungicide applications (7-day intervals). Daily humidity and temperature monitoring. Remove pruned material immediately. Weekly AI rescans to track treatment efficacy. Soil biocontrol inoculation in Week 2.

Day 31–60

🔄 Recovery & Nutritional Boost Phase

Transition to biweekly preventive copper-based fungicide. Foliar feed with calcium + boron to rebuild cell wall integrity. Re-introduce beneficial insects (predatory mites) for sustainable pest control. Bi-weekly AI health rescans.

Day 61–90

✅ Prevention & Immunity Hardening Phase

Implement crop rotation planning for next season. Apply silicon-based foliar treatment to strengthen leaf cuticle. Monthly AI baseline scans to establish new health benchmarks. Fine-tune irrigation and EC based on growth stage and weather forecast integration.

14-Day Pathogen Risk Forecast (Sector B)

Predictive model based on regional weather telemetry and historical outbreak data.

Key Risk Factors Detected
🌧 Rain forecast Day 6–7 → extended leaf wetnessHIGH RISK
🌡 Temp. drop to 18°C on Day 8 → fungal sporulation triggerMED RISK
💨 Strong winds Day 10 → potential spore dispersal to Sector CMED RISK

58 Conditions. Full Care Protocol
for Every Single One.

Updated Q3 2025 · Expanding quarterly
Core Technology

Not Just Diagnosis.
A Complete Crop Care AI.

From a single image to a full agronomic treatment plan — in under 40ms. Our AI thinks like a PhD plant pathologist, an agronomist, and an IoT systems engineer combined.

🔬

Holistic Crop Health Assessment

Beyond identifying the pathogen, we quantify infection severity, estimate yield impact, and compute a dynamic Crop Health Score from 0–100.

💊

Precision Treatment Protocols

AI-generated, step-by-step treatment plans with specific chemical concentrations, application timing, and resistance rotation — not generic advice.

🌡

Environmental Prescription Engine

We read your IoT sensor data and prescribe exact target values for humidity, temperature, ventilation, and irrigation to suppress pathogen proliferation.

📅

90-Day Care Roadmap

Every diagnosis auto-generates a structured 90-day care calendar covering active treatment, recovery nutrition, and long-term immunity hardening.

📈

14-Day Outbreak Risk Forecast

Time-series weather telemetry feeds our predictive models to forecast daily outbreak risk, alerting you 5–14 days before visible symptoms appear on untreated areas.

🔌

One-Click ERP & IoT Sync

Treatment protocols push directly to your drip-irrigation controller, SCADA system, or farm ERP via REST/MQTT webhooks — no manual re-entry.

We Believe Farmers Deserve
PhD-Level AI Support

Founded in early 2025 by a multidisciplinary team of agricultural scientists, ML engineers, and former farm operators, AgriVision AI was built from the ground up to provide the kind of deep, expert-level crop intelligence that was previously only available to large agribusiness corporations.

Fully bootstrapped. No VC. We grow by building something our users genuinely cannot live without. Our private beta is currently live across pilot farm networks in South Korea and Southeast Asia, analyzing thousands of crop samples daily.

58+
Detectable Conditions
38ms
Avg. Inference Latency
98.7%
Diagnostic Accuracy
100%
Bootstrapped
Team

Meet the Founders

🌾
Shin Kim
신 김
Co-Founder & CEO — Agricultural Systems Engineer. Former research lead at NAAS (National Institute of Agricultural Sciences, Korea). 12 years field experience in precision crop management.
⚙️
Jiyoon Park
박지윤
Co-Founder & CTO — ML Infrastructure & Edge Systems. Former senior engineer at Kakao Brain. Specializes in computer vision model optimization and real-time inference pipelines on embedded hardware.
🔬
Sunwoo Lee, PhD
이선우 박사
Head of Research — Plant Pathology & Bioinformatics. PhD, Seoul National University (SNU). Published 14 peer-reviewed papers on fungal plant pathogens and biocontrol. Expert advisor to Korean Ministry of Agriculture.

Partner With Us to Feed
the Next Billion People

We are selectively onboarding enterprise pilot partners and evaluating strategic AI integration partnerships to dramatically scale our inference pipeline. If you operate a large-scale farm network or an agritech platform, reach out directly.