Technical Information
Sankhya Intelligence – Technical Overview
1. System Definition
Sankhya Intelligence is a per-tree agricultural intelligence system designed to convert soil and environmental measurements into structured decision support over time.
The system does not treat a farm as a single averaged unit.
Each tree is modeled individually.
Sankhya operates as a longitudinal feedback system, tracking how trees respond to irrigation, nutrition, seasonal shifts, and interventions across multiple cycles.
It is designed for precision orchard management and perennial crop systems.
2. Core Principle: Longitudinal Feedback Modeling
Sankhya operates on a continuous feedback loop:
Measure → Act → Observe → Learn → Refine
Instead of interpreting readings in isolation, the system evaluates:
- Changes in soil moisture over time
- Changes in EC (electrical conductivity)
- Shifts in pH
- Temperature dynamics
- Intervention timing and dosage
The system analyzes rate-of-change (Δ values) and response patterns to determine whether observed shifts are due to:
- Nutrient uptake
- Salt accumulation
- Evaporation
- Biological consumption
- Seasonal stress
- Structural imbalance
This temporal context is central to the system’s intelligence.
3. Data Sources
Sankhya can operate using:
Manual Data Entry
- Handheld moisture meter readings
- EC measurements
- pH measurements
- Temperature readings
- Recorded irrigation and fertilization events
Continuous Sensor Integration (Optional)
- Soil moisture sensors
- EC sensors
- pH probes
- Root-zone temperature probes
- Ambient environmental sensors
Data collection frequency influences resolution but does not change the system’s modeling logic.
4. Analytical Architecture
The system processes structured time-series data for each individual tree.
Each tree maintains its own:
- Historical measurement archive
- Intervention history
- Seasonal context
- Root-zone behavior patterns
From this dataset, Sankhya generates:
- Signal summaries
- Root-zone target ranges
- Short-term (7-day) action guidance
- Mid-term (14-day) monitoring guidance
- Structural (21-day+) planning insights
Outputs are structured and derived from trend analysis rather than static thresholds.
5. Decision-Support Model
Sankhya is a decision-support system.
It does not autonomously control irrigation or fertilization equipment.
Instead, it provides:
- Context-aware interpretation
- Risk identification
- Root-zone balance assessment
- Early stress detection
- Intervention timing refinement
Final decisions remain with the grower.
6. Crop Scope
The system is crop-agnostic by design.
It is currently deployed in orchard environments and perennial tree systems.
The architecture supports broader perennial agricultural applications.
7. Data Ownership and Privacy
All primary data belongs to the grower.
Sankhya does not sell identifiable farm data.
Where system-level improvements occur, they are based on anonymized pattern recognition and do not expose individual farm identity.
8. System Intent
Sankhya Intelligence is designed to:
- Improve yield consistency
- Reduce input waste
- Reduce salt buildup risk
- Increase root-zone stability
- Transition growers from reactive to predictive management
The system improves in accuracy as seasonal depth increases.
Long-term context is foundational to its operation.
Last updated: 22nd Feb 2026