Precision Intelligence for the Soil.
Qidian VP combines multimodal data processing with real-world grounding to provide farmers with actionable insights that were previously invisible.
AI Architecture — Built on Google
Qidian VP is a purpose-built vertical AI application layered on top of Google's frontier AI infrastructure. We don't maintain model weights — we integrate tightly with the best foundation models on the planet.
Gemini Vision — Crop Analysis
Gemini 2.0 Flash's native vision capability processes farm photos in real-time, identifying 240+ diseases, pests, and nutrient deficiencies across rice, maize, cassava, and sugarcane — from a simple smartphone camera, even in low-light field conditions.
Voice — Cloud Speech-to-Text v2
Farmers describe symptoms verbally in their native dialect. Google Cloud Speech-to-Text v2 with custom agricultural vocabulary transcribes queries in Vietnamese, Thai, Bahasa, and 11 additional regional dialects — even in noisy field environments.
Search Grounding — Reduced Hallucination Risk
Every Gemini response is anchored to verified sources via Google Search Grounding — ingesting current pest advisories, weather forecasts, commodity prices, and government agronomic bulletins before generating advice.
Unified Gemini Response Engine
Vision analysis, voice query, and grounded web context all converge in a single Gemini API call. The model returns a structured JSON diagnosis with confidence score, recommended treatment, estimated cost, and a plain-language explanation in the farmer's dialect.
Grounded in Reality, Not Hallucinations.
Unlike generic LLM chat interfaces, Qidian VP uses Gemini's Search Grounding feature to anchor every response to current, verifiable sources. Farmers receive advice traceable to specific agronomic databases, government pest bulletins, and real-time commodity prices — not AI-generated approximations.
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checkFAO & IRRI Open-Access Database Integration Recommendations cross-referenced with the International Rice Research Institute's disease library and FAO crop protection standards.
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checkLive Commodity Price Feed Market data sourced from regional agricultural commodity boards and integrated via Google Search Grounding for real-time economic context.
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checkTraceable Source Citations Every recommendation includes links to its source data, enabling agronomist review and farmer trust-building.
Data Sovereignty & Google Cloud Security
Qidian VP runs entirely on Google Cloud infrastructure — benefiting from Google's global compliance certifications (ISO 27001, SOC 2 Type II), regional data residency controls, and enterprise-grade encryption. Farmer data never leaves the Southeast Asia cloud region without explicit consent.
Performance Benchmarks
Measured during the Mekong Delta pilot deployment (Q4 2025) across 4,200+ real-world diagnoses.
1.2s
Median Inference Latency
Gemini 2.0 Flash multimodal call (image + text + grounding) measured at P50. P95 latency: 3.4s. P99: 5.1s.
87.3%
Top-1 Diagnostic Accuracy
Validated by independent agronomists using IRRI Rice Knowledge Bank protocols. Top-3 accuracy: 93.1%. Measured across 240+ disease classes.
$0.0041
Cost per Diagnosis
Combined cost of Gemini API ($1.80), STT ($0.70), Search Grounding ($0.50), Maps ($0.21), Cloud Run/Firebase ($0.90) = $4.11/1000 queries.
monitoring Detailed Performance Metrics — Pilot Data
| Metric | Value | Notes |
|---|---|---|
| Gemini API Uptime | 99.7% | Measured over 90-day pilot period (asia-southeast1 region) |
| Voice Recognition Accuracy | 94.2% | Southern Vietnamese dialect; 89.7% for Central Vietnamese |
| Offline Model Accuracy | 78.4% | Google AI Edge distilled model (top-1); 88.2% (top-3) |
| Image Processing | Low-latency | Image pre-processing + upload for 12MP smartphone photo (varies by network conditions) |
| Concurrent Users Tested | 500 | Load test via Cloud Run auto-scaling (0→50 instances) |
| Cold Start Time | 1.8s | Cloud Run container cold start with min-instances=2 |
| Monthly GCP Cost (312 users) | $127 | Pilot period; projected $2,800/mo at 50K MAU target |
Crop Disease Coverage — 240+ Conditions
Qidian VP's diagnostic engine covers the major diseases, pests, and nutritional deficiencies affecting Southeast Asia's four staple crops. Our training dataset includes 120,000+ annotated field images sourced from publicly available datasets (PlantVillage, IRRI Rice Knowledge Bank, CIAT open repositories) and supplemented by 8,000+ images collected during our Mekong Delta pilot.
Rice
98 conditions covered
- Rice Blast (Magnaporthe oryzae)
- Bacterial Leaf Blight
- Sheath Blight (Rhizoctonia)
- Brown Planthopper (BPH)
- Tungro Virus Complex
- Stem Borer
- Nitrogen/Phosphorus Deficiency
- + 91 more conditions
Maize
62 conditions covered
- Fall Armyworm (Spodoptera)
- Northern Leaf Blight
- Stalk Rot Complex
- Downy Mildew
- Maize Streak Virus
- Ear Rot (Fusarium)
- Zinc Deficiency
- + 55 more conditions
Cassava
47 conditions covered
- Cassava Mosaic Disease
- Bacterial Blight (Xanthomonas)
- Cassava Mealybug
- Brown Leaf Spot
- Anthracnose
- White Fly Infestation
- Root Rot
- + 40 more conditions
Sugarcane
33 conditions covered
- Red Rot (Colletotrichum)
- Smut Disease
- Top Borer
- Rust (Puccinia)
- Wilt Disease
- Leaf Scald
- Iron Chlorosis
- + 26 more conditions
Expansion Roadmap:
Coffee, rubber, and tropical fruit crops (mango, dragon fruit, durian) scheduled for Q3 2026. Training data collection in partnership with Nông Lâm University (HCMC) and Kasetsart University (Bangkok).
System Architecture
End-to-end data flow from farmer's smartphone to AI-powered diagnosis and back — all on Google Cloud.
Client Layer
Flutter Mobile App
PWA (Lite version)
Google AI Edge SDK
Firebase Auth
API Gateway
Cloud Run (Serverless)
Cloud Endpoints
Cloud Armor (DDoS)
Identity Platform
AI Engine
Gemini 2.0 Flash
Vertex AI Pipeline
Search Grounding API
Speech-to-Text v2
Data Storage
Firestore · Cloud Storage · BigQuery
External APIs
Google Maps · Weather API · Commodity Exchanges
Observability
Cloud Monitoring · Cloud Trace · Error Reporting
Limitations & Known Constraints
What Qidian VP cannot do yet — and what we're working to improve.
- warning Qidian VP does not replace professional agronomist consultation for complex multi-disease interactions.
- warning Accuracy varies by crop: rice (89.4%) > maize (86.1%) > cassava (83.7%) > sugarcane (79.2%).
- warning Voice recognition accuracy drops to ~82% in very noisy environments (e.g., near farm machinery).
- warning Offline mode provides basic identification only — full treatment plans require connectivity.
- warning Currently limited to 4 crop categories; tropical fruits and tree crops not yet supported.
See the Technology in Action
We're onboarding a limited cohort of agricultural extension services and agri-fintech partners to test the system in real field conditions during H1 2026.