Phase 01: Audit
Understanding your current state across every dimension of the operation.
Deliverables
Soil & Infrastructure Survey
2,400-point soil sampling protocol across all managed hectares. Topography, drainage, compaction mapping.
Data Inventory Report
Full audit of existing sensors, ERP systems, weather stations, and manual record-keeping workflows.
Gap Analysis Matrix
Side-by-side comparison of current vs. benchmark precision operations. Quantified opportunity per input category.
ROI Projection Model
Conservative, base, and optimistic financial models tied to specific intervention points identified during audit.
Client Team Involved
Technology Deployed
Timeline
Phase 02: Architect
Designing the sensor network, data architecture, and ML pipeline before a single cable is run.
Deliverables
Sensor Network Blueprint
Node placement maps for soil moisture, EC, temperature, and weather stations. LoRaWAN vs. cellular decision matrix per zone.
Data Architecture Spec
Cloud infrastructure design (AWS/Azure), data lake schema, API integration specs for existing ERP and market systems.
ML Model Selection Report
Crop-specific model recommendations: yield prediction, irrigation scheduling, disease risk scoring. Training data requirements.
Procurement & Vendor List
Hardware SKUs, vendor contracts, lead times, and total cost of ownership over 5 years.
Client Team Involved
Technology Deployed
Timeline
Phase 03: Integrate
Physical installation, data pipeline commissioning, and baseline model training.
Deliverables
Deployed Sensor Network
All nodes installed, powered, and transmitting. Network coverage map with signal strength per zone. 99.2% uptime SLA.
Live Dashboard v1.0
Real-time field monitoring dashboard. Per-hectare soil moisture, temperature, EC, and weather overlays. Alert configuration.
Data Pipeline Certification
End-to-end data flow testing. Latency benchmarks. Failover protocols. GDPR/data sovereignty compliance documentation.
Baseline ML Models (Active)
First-generation yield and irrigation models live with 8–12 weeks of training data. Accuracy benchmarks documented.
Client Team Involved
Technology Deployed
Timeline
Phase 04: Optimize
Continuous model refinement, agronomic integration, and measurable yield improvement.
Deliverables
Monthly Optimization Reports
Per-field performance vs. pre-integration baseline. Irrigation savings quantified. Input cost per tonne tracked against target.
Adaptive Irrigation Schedules
ML-generated irrigation prescriptions updated weekly. Water savings vs. calendar-based scheduling documented per zone.
Yield Prediction Accuracy Reports
Model accuracy improving each season. 90-day yield forecasts with confidence intervals for board presentations.
Quarterly Executive Dashboard
Board-ready PDF and live view. Yield-per-input, water efficiency, cost-per-hectare, and risk index. Benchmark vs. regional average.
Client Team Involved
Technology Deployed
Timeline
Phase 05: Transfer
Building internal capability so your team owns the system — not depends on us.
Deliverables
Internal Training Program
40-hour certification curriculum for data analysts and agronomists. Dashboard operation, alert management, model interpretation.
System Documentation Package
Complete technical documentation. Hardware maintenance guides. Model retraining playbooks. Troubleshooting decision trees.
Vendor & Support Handover
Direct relationships established with hardware vendors. Support contracts transferred. Emergency escalation protocols documented.
12-Month Post-Transfer Support
Retained access to Cultivate engineers for 12 months post-handover. Monthly check-in calls. Priority ticket response within 4 hours.
Client Team Involved
Technology Deployed
Timeline
↑ 31%
Water efficiency
Mato Grosso soy operation
Brazil · 78,400 ha · 2024
↑ 18%
Yield per input
Saskatchewan wheat cooperative
Canada · 124,000 ha · 2023
−23%
Fertilizer cost/tonne
Pampas corn & soy rotation
Argentina · 52,000 ha · 2024
94%
Yield prediction accuracy
Season-ahead forecasting
Multiple operations · Season 3 · 2024
Operations by ICP
São Paulo–based grain exporter, 92,000 ha soy & corn
Challenge
Board demanded 15% yield improvement without capex increase. Irrigation scheduling was calendar-based. No soil data below 30cm.
Outcome
Deployed 2,840 soil probes across 6 zones. ML irrigation model reduced water use 28% while yield increased 14% in first full season.
340-member wheat cooperative, Western Australia, 186,000 ha aggregate
Challenge
Climate volatility creating 40% yield variance between members on identical inputs. Cooperative needed shared infrastructure economics.
Outcome
Shared LoRaWAN network across all member properties. Individual prescription maps. Variance reduced to 18%. Shared cost: $4.20/ha/year.
Federal agricultural ministry, subsidy reform program, 1.2M ha target
Challenge
Subsidy payments based on self-reported yield data. No verification infrastructure. Political pressure to tie payments to measurable outcomes.
Outcome
Pilot program across 85,000 ha. Satellite + sensor verification layer. Subsidy framework redesigned around verified yield-per-input metrics.
The 12-Month Digital Farm Roadmap
The complete methodology, hardware specifications, cost benchmarks, and ROI templates used across 40+ operations. No sales call required.
Hardware. Pipeline. Intelligence.
No proprietary black boxes. Every component is specification-grade, vendor-independent, and documented for internal handover.
Hardware Stack
Sentek EnviroSCAN
Soil Moisture
0.1% VWC accuracy · 10 depths
Dragino LoRa Gateways
Connectivity
LoRaWAN 1.0.3 · 15km range
Davis Vantage Pro 2
Weather Station
ET calculation · 1-min intervals
DJI Matrice 350 RTK
Aerial Survey
1cm GSD · NDVI/NDRE payloads
EM38-MK2
Soil EC Mapping
Electromagnetic induction · 1.5m depth
Trimble R12i
GNSS / RTK
±4mm horizontal accuracy
Data Pipeline Architecture
AWS IoT Core / MQTT
Real-time sensor data ingestion at 50k msg/sec
TimescaleDB + S3
Time-series optimized, 5-year hot storage
Apache Kafka + Spark
Stream processing, anomaly detection pipeline
XGBoost / LightGBM / LSTM
Yield prediction, irrigation scheduling, disease risk
Custom React + Mapbox GL
Per-hectare overlays, live telemetry, board exports
Platform Integrations
Request a Transformation Audit
A 30-minute diagnostic call with a senior Cultivate engineer and agronomist. No pitch deck — just an honest assessment of where your operation sits and what the next 12 months could look like.
What Happens in the 30-Minute Call
Operation Overview
You brief us on scale, crops, current systems, and the pressure you're under.
Gap Identification
We map your operation against our benchmark database. Where are the largest yield-per-input gaps?
Rough Opportunity Sizing
Conservative estimate of what Phase 1 (Audit) would surface. No commitment required.
Next Steps
If there's mutual fit, we outline the Audit scope and timeline. You leave with a written summary.
Prefer to book directly? Schedule a 30-minute diagnostic call with a senior Cultivate engineer.