Agriculture
See what sovereign AI looks like for Indian farming.
3 scenarios. Real data. Real outcomes.
01
Five Silos. Zero Intelligence.
AgriStack, eNAM, ICAR, IMD, soil maps. Five data sources. Never connected. Farmers get generic advice. Traders profit from information asymmetry.
7.63 Cr
Farmer IDs registered
23.5 Cr
agricultural plots mapped
$0B
annual post-harvest loss
02
Per-plot advisory. 42 languages.
-
01
Farmer ID + plot dataAgriStack identity linked to specific plot coordinates, soil type, and crop history.
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02
Data fusionSatellite imagery, IMD weather forecast, and soil health card fused into a single knowledge graph.
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03
Precision advisoryPlot-specific recommendation generated. Sowing window, fertiliser dose, irrigation schedule. In the farmer's language.
42K
AGROVOC concepts indexed
Offline
capable for rural deployment
42
languages supported
Not generic state-level advice. Per-plot. Per-season. Per-farmer.
03
Plant with market intelligence. Not blind hope.
Farmers plant without price visibility. They discover the market price at the mandi gate. Traders profit.
Price data exists on eNAM. But it's never connected to planting decisions.
1,000+
mandi prices as knowledge graph
Harvest timing
advisory based on price forecast
15-30%
income gain potential
Example: Tomato price drops 40% in March at Kolar mandi every year. Advisory: stagger harvest or switch to cold-storage-ready variety.
Information asymmetry is the biggest tax on Indian farmers. We eliminate it.
04
PMFBY claim in hours. Not months.
TRADITIONAL
6 months
WITH ADIOS
6 hours
55M farmer applications. Fraud caught by satellite, not field visits.
05
Not a roadmap. Running today.
0
tests
0
AGROVOC concepts
0
patents
Offline
capable
Rust. On-premises. Sovereign by design.
06
Before and After
Before
Generic state-level advisory
14-day data lag
Manual insurance claims
Knowledge lost on officer transfer
→
→
→
→
After
Per-plot precision advisory
Real-time satellite + weather
Satellite-verified claims
Institutional knowledge persisted