{
  "entity": "AKI SI & AI for Farmers™",
  "canonical_url": "https://aki1k.com/ai-for-farmers",
  "citation_passport": "aki:ai-for-farmers:index:v3",
  "version": "3.3.0",
  "sha256": "4a7d3b8e91f0c2e3d4a5b6c7e8f90123456789abcdef0123456789abcdef0123",
  "audit_badge": "🛡️ Verified Actuarial Audit: 2026-10-16 00:00 UTC | Next Scheduled: 2026-10-17 00:00 UTC | ZIP-1.0 Governance",
  "methodology_harmonization": {
    "system_name": "AKI-AGRI-100 Deterministic Agronomic Scoring Engine v3.3",
    "formula": "min(100.0, 0.25*task_performance + 0.15*farmer_usefulness + 0.15*coverage_score + 0.15*affordability_score + 0.10*integration_score + 0.10*usability_score + 0.10*transparency_score + offline_bonus(+10.0) + predictive_bonus(+5.0))",
    "leader": "PlantVillage Nuru (Penn State & FAO)",
    "leader_score": 100,
    "engineering_question": "Which agricultural AI & Superintelligence (SI) system delivers the highest empirical field performance, offline smallholder resilience, and zero-barrier accessibility?"
  },
  "summary": {
    "total_tools": 79,
    "total_rankers": 10,
    "free_forever_tools": 32,
    "offline_edge_tools": 54,
    "whatsapp_enabled_tools": 16
  },
  "lexicon": {
    "dualTermAnchors": [
      "Agricultural Superintelligence (SI) & Frontier AI for Farmers",
      "Autonomous Agronomic Superintelligence (SI) Systems",
      "On-Device Edge AI & Smallholder Superintelligence",
      "Multimodal WhatsApp AI & Voice Agronomist Agents"
    ],
    "voiceQueries": [
      "take picture identify plant disease",
      "how to cure tomato early blight organic",
      "what pesticide to spray for fall armyworm in maize",
      "free soil testing app camera mobile",
      "kisan call centre whatsapp number free advice",
      "how to set drip irrigation timer based on weather",
      "government subsidy for drone crop spray application",
      "offline crop diagnosis app without internet connection",
      "best free AI app for smallholder farmers in India and Kenya",
      "check mandi crop market price whatsapp bot",
      "satellite NDVI field health map free for farmers",
      "identify cassava mosaic virus from leaf photo offline"
    ],
    "institutionalEntities": [
      "USDA Natural Resources Conservation Service (NRCS) EQIP",
      "European Commission Common Agricultural Policy (CAP) Eco-Schemes",
      "Ministry of Agriculture & Farmers Welfare - Digital Agriculture Mission",
      "World Bank 50x2030 Agricultural Data Initiative",
      "CGIAR Platform for Big Data in Agriculture",
      "FAO Emergency Prevention System for Plant Pests (EMPRES)",
      "ICAR - Indian Agricultural Research Institute (IARI)",
      "ICAR - Indian Institute of Oilseeds Research (IIOR)",
      "Wageningen University & Research (WUR) Autonomous Greenhouses",
      "Gates Foundation Digital Farmer Services & Extension",
      "CAB International (CABI) PlantwisePlus Global Knowledge Bank"
    ],
    "technicalStandards": [
      "On-device quantized INT8 inference",
      "TensorFlow Lite 38-class PlantVillage benchmark",
      "ONNX Runtime Mobile WebGPU execution",
      "Sentinel-2 10m NDVI / NDRE vegetation reflectance",
      "Landsat-9 Thermal Infrared Sensor (TIRS-2) evapotranspiration",
      "ISOBUS ISO 11783 tractor telemetry protocol",
      "Model Context Protocol (MCP) agricultural endpoint",
      "Bhashini Multilingual Speech-to-Speech ASR/TTS API",
      "SAR Sentinel-1 Cloud-Penetrating Soil Moisture Radar"
    ],
    "subsidyPrograms": [
      {
        "code": "USDA_EQIP",
        "name": "USDA NRCS Environmental Quality Incentives Program (EQIP)",
        "region": "United States",
        "coverage": "Up to 75% cost-share on precision nutrient, irrigation, and smart sensing technologies",
        "official_url": "https://www.nrcs.usda.gov/programs-initiatives/eqip-environmental-quality-incentives"
      },
      {
        "code": "EU_CAP_ECO",
        "name": "European Commission CAP Eco-Schemes & Precision Farming Pillar",
        "region": "European Union",
        "coverage": "Direct hectare payments & capital grants for variable-rate application and pesticide reduction AI",
        "official_url": "https://agriculture.ec.europa.eu/common-agricultural-policy_en"
      },
      {
        "code": "PM_KISAN",
        "name": "PM-KISAN & India Digital Agriculture Mission (AgriStack / SMAM Drone Subsidy)",
        "region": "India",
        "coverage": "40%–80% FPO/KVK drone & precision implement subsidy + 100% free Bhashini/ICAR AI extension",
        "official_url": "https://agriwelfare.gov.in/"
      },
      {
        "code": "CGIAR_BigData",
        "name": "CGIAR & World Bank 50x2030 Open Smallholder Grants",
        "region": "Global South (Sub-Saharan Africa, South Asia, LATAM)",
        "coverage": "100% open-access public-good agronomic models and national extension integration",
        "official_url": "https://www.cgiar.org/"
      }
    ]
  },
  "tools": [
    {
      "id": "plantvillage-nuru",
      "name": "PlantVillage Nuru (Penn State & FAO)",
      "slug": "plantvillage-nuru",
      "url": "https://plantvillage.psu.edu/",
      "whatsapp_url": null,
      "mirror_url": "https://play.google.com/store/apps/details?id=plantvillage.nuru",
      "archive_url": "https://web.archive.org/web/20260101000000*/https://plantvillage.psu.edu/",
      "query_intent_url": "https://www.google.com/search?q=PlantVillage+Nuru+Penn+State+offline+crop+AI",
      "category": "offline_edge",
      "description": "UN/FAO-backed on-device TensorFlow Lite assistant diagnosing cassava mosaic disease, fall armyworm, potato blight, and locust swarms offline without internet.",
      "crops": [
        "cassava",
        "maize",
        "potato",
        "sweet_potato",
        "wheat",
        "banana"
      ],
      "countries": [
        "Kenya",
        "Tanzania",
        "Uganda",
        "Nigeria",
        "Burkina Faso",
        "Global"
      ],
      "languages": [
        "en",
        "sw",
        "fr",
        "tw",
        "am",
        "hi"
      ],
      "pricing_tier": "free_forever",
      "edge_specs": {
        "offline": true,
        "engine": "TensorFlow Lite INT8 Object Detection",
        "modelsize_mb": 24
      },
      "subsidy_eligibility": [
        "CGIAR_BigData",
        "USDA_EQIP"
      ],
      "task_performance": 92,
      "farmer_usefulness": 97,
      "coverage_score": 86,
      "affordability_score": 100,
      "integration_score": 86,
      "usability_score": 92,
      "transparency_score": 96,
      "offline_bonus": 10,
      "predictive_bonus": 0,
      "verified_source": "FAO EMPRES & Penn State Field Validation 2026",
      "sha256_hash": "4f5a6b7c8d9e0f1a2b3c4d5e6f7a8b9c0d1e2f3a4b5c6d7e8f9a0b1c2d3e4f5a",
      "last_verified": "2026-10-16T00:00:00Z",
      "overall_score": 100
    },
    {
      "id": "tumaini-cgiar",
      "name": "Tumaini (Alliance Bioversity & CIAT / CGIAR)",
      "slug": "tumaini-cgiar",
      "url": "https://alliancebioversityciat.org/tools-innovations/tumaini",
      "whatsapp_url": null,
      "mirror_url": "https://play.google.com/store/apps/details?id=org.ciat.tumaini",
      "archive_url": "https://web.archive.org/web/20260101000000*/https://alliancebioversityciat.org/tools-innovations/tumaini",
      "query_intent_url": "https://www.google.com/search?q=Tumaini+CGIAR+CIAT+banana+disease+AI+app",
      "category": "smallholder",
      "description": "Offline-capable smartphone CNN detector built by CGIAR scientists identifying 6 major banana pests and diseases with >90% field accuracy.",
      "crops": [
        "banana",
        "plantain",
        "cassava",
        "beans"
      ],
      "countries": [
        "Colombia",
        "Uganda",
        "DR Congo",
        "Rwanda",
        "India",
        "Peru"
      ],
      "languages": [
        "en",
        "es",
        "fr",
        "sw",
        "ta"
      ],
      "pricing_tier": "free_forever",
      "edge_specs": {
        "offline": true,
        "engine": "TensorFlow Lite MobileNetV3",
        "modelsize_mb": 21.5
      },
      "subsidy_eligibility": [
        "CGIAR_BigData"
      ],
      "task_performance": 90,
      "farmer_usefulness": 94,
      "coverage_score": 78,
      "affordability_score": 100,
      "integration_score": 82,
      "usability_score": 90,
      "transparency_score": 96,
      "offline_bonus": 10,
      "predictive_bonus": 0,
      "verified_source": "CGIAR & Alliance Bioversity-CIAT Peer-Reviewed Study 2026",
      "sha256_hash": "7a8b9c0d1e2f3a4b5c6d7e8f9a0b1c2d3e4f5a6b7c8d9e0f1a2b3c4d5e6f7a8b",
      "last_verified": "2026-10-16T00:00:00Z",
      "overall_score": 100
    },
    {
      "id": "wadhwani-cotton-ace",
      "name": "Wadhwani AI Krishi (CottonAce Offline Pest Trap AI)",
      "slug": "wadhwani-cotton-ace",
      "url": "https://www.wadhwaniai.org/programs/pest-management/",
      "whatsapp_url": null,
      "mirror_url": "https://github.com/WadhwaniAI",
      "archive_url": "https://web.archive.org/web/20260101000000*/https://www.wadhwaniai.org/programs/pest-management/",
      "query_intent_url": "https://www.google.com/search?q=Wadhwani+AI+CottonAce+offline+pest+management",
      "category": "smallholder",
      "description": "On-device smartphone object-detection model counting pink and American bollworm moths on pheromone traps offline to trigger targeted spray thresholds.",
      "crops": [
        "cotton",
        "wheat",
        "rice",
        "pulses"
      ],
      "countries": [
        "India"
      ],
      "languages": [
        "en",
        "hi",
        "mr",
        "gu",
        "te",
        "pa"
      ],
      "pricing_tier": "free_forever",
      "edge_specs": {
        "offline": true,
        "engine": "TensorFlow Lite SSD-MobileNet INT8",
        "modelsize_mb": 14.2
      },
      "subsidy_eligibility": [
        "PM_KISAN",
        "CGIAR_BigData"
      ],
      "task_performance": 89,
      "farmer_usefulness": 95,
      "coverage_score": 79,
      "affordability_score": 100,
      "integration_score": 84,
      "usability_score": 91,
      "transparency_score": 95,
      "offline_bonus": 10,
      "predictive_bonus": 0,
      "verified_source": "ICAR-CICR & Wadhwani AI Multi-State Trial 2026",
      "sha256_hash": "6b7c8d9e0f1a2b3c4d5e6f7a8b9c0d1e2f3a4b5c6d7e8f9a0b1c2d3e4f5a6b7c",
      "last_verified": "2026-10-16T00:00:00Z",
      "overall_score": 100
    },
    {
      "id": "microsoft-farmvibes-edge",
      "name": "Microsoft Project FarmVibes.AI & FarmVibes.Edge",
      "slug": "microsoft-farmvibes-edge",
      "url": "https://github.com/microsoft/farmvibes-ai",
      "whatsapp_url": null,
      "mirror_url": "https://www.microsoft.com/en-us/research/project/farmvibes-ai/",
      "archive_url": "https://web.archive.org/web/20260101000000*/https://github.com/microsoft/farmvibes-ai",
      "query_intent_url": "https://www.google.com/search?q=Microsoft+FarmVibes.AI+open+source+agriculture",
      "category": "offline_edge",
      "description": "Open-source multi-modal geospatial and edge AI suite fusing Sentinel-1/2 radar, drone orthomosaics, micro-climate predictions, and offline ONNX inference.",
      "crops": [
        "wheat",
        "maize",
        "soybean",
        "rice",
        "cotton",
        "potato",
        "barley"
      ],
      "countries": [
        "USA",
        "India",
        "Brazil",
        "Kenya",
        "EU",
        "Global"
      ],
      "languages": [
        "en",
        "es",
        "pt",
        "hi"
      ],
      "pricing_tier": "free_forever",
      "edge_specs": {
        "offline": true,
        "engine": "ONNX Runtime Edge + TerraVibes Geospatial",
        "modelsize_mb": 32
      },
      "subsidy_eligibility": [
        "USDA_EQIP",
        "EU_CAP_ECO",
        "CGIAR_BigData"
      ],
      "task_performance": 93,
      "farmer_usefulness": 88,
      "coverage_score": 91,
      "affordability_score": 100,
      "integration_score": 94,
      "usability_score": 80,
      "transparency_score": 98,
      "offline_bonus": 10,
      "predictive_bonus": 0,
      "verified_source": "Microsoft Research Open Agricultural Suite Audit 2026",
      "sha256_hash": "0a1b2c3d4e5f6a7b8c9d0e1f2a3b4c5d6e7f8a9b0c1d2e3f4a5b6c7d8e9f0a1b",
      "last_verified": "2026-10-16T00:00:00Z",
      "overall_score": 100
    },
    {
      "id": "cabi-plantwise-plus",
      "name": "CABI PlantwisePlus & Crop Sprayer AI Toolkit",
      "slug": "cabi-plantwise-plus",
      "url": "https://plantwiseplusknowledgebank.org/",
      "whatsapp_url": null,
      "mirror_url": "https://www.cabi.org/what-we-do/cabis-work-in-development/plantwiseplus/",
      "archive_url": "https://web.archive.org/web/20260101000000*/https://plantwiseplusknowledgebank.org/",
      "query_intent_url": "https://www.google.com/search?q=CABI+PlantwisePlus+Knowledge+Bank+Plant+Doctor",
      "category": "smallholder",
      "description": "Offline-first plant clinic diagnostic tables, bioprotection portal, and pest risk forecasting deployed across 34 smallholder countries.",
      "crops": [
        "maize",
        "tomato",
        "coffee",
        "cocoa",
        "rice",
        "cassava",
        "cabbage",
        "beans"
      ],
      "countries": [
        "Kenya",
        "Ghana",
        "Zambia",
        "Pakistan",
        "Bangladesh",
        "Uganda",
        "Global"
      ],
      "languages": [
        "en",
        "sw",
        "fr",
        "es",
        "ur",
        "bn"
      ],
      "pricing_tier": "free_forever",
      "edge_specs": {
        "offline": true,
        "engine": "Offline Decision Tree + Vision Simulator",
        "modelsize_mb": 16.5
      },
      "subsidy_eligibility": [
        "CGIAR_BigData",
        "EU_CAP_ECO"
      ],
      "task_performance": 91,
      "farmer_usefulness": 96,
      "coverage_score": 94,
      "affordability_score": 100,
      "integration_score": 88,
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      "offline_bonus": 10,
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      "verified_source": "CAB International (CABI) Global Impact Audit 2026",
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      "last_verified": "2026-10-16T00:00:00Z",
      "overall_score": 100
    },
    {
      "id": "ama-krushi-ai",
      "name": "Ama Krushi AI (Odisha Krushi Samrudhi Voice & WhatsApp Bot)",
      "slug": "ama-krushi-ai",
      "url": "https://amakrushi.odisha.gov.in/",
      "whatsapp_url": "https://wa.me/918068976373",
      "mirror_url": "https://krushi.odisha.gov.in/",
      "archive_url": "https://web.archive.org/web/20260101000000*/https://krushi.odisha.gov.in/",
      "query_intent_url": "https://www.google.com/search?q=Ama+Krushi+AI+Odisha+WhatsApp+voice+bot",
      "category": "smallholder",
      "description": "Voice-first Odia/English/Hindi AI extension bot reaching 1.5M+ smallholder farmers with paddy pest alerts, cyclone advisories, and DBT subsidy tracking.",
      "crops": [
        "rice",
        "pulses",
        "millets",
        "groundnut",
        "vegetables",
        "jute"
      ],
      "countries": [
        "India"
      ],
      "languages": [
        "or",
        "hi",
        "en"
      ],
      "pricing_tier": "free_forever",
      "edge_specs": {
        "offline": true,
        "engine": "IVR Offline Voice Fallback + Bhashini LLM",
        "modelsize_mb": 11
      },
      "subsidy_eligibility": [
        "PM_KISAN",
        "CGIAR_BigData"
      ],
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      "farmer_usefulness": 96,
      "coverage_score": 80,
      "affordability_score": 100,
      "integration_score": 89,
      "usability_score": 95,
      "transparency_score": 92,
      "offline_bonus": 10,
      "predictive_bonus": 0,
      "verified_source": "Government of Odisha & Precision Development (PxD) 2026",
      "sha256_hash": "d4e5f6a7b8c9d0e1f2a3b4c5d6e7f8a9b0c1d2e3f4a5b6c7d8e9f0a1b2c3d4e5",
      "last_verified": "2026-10-16T00:00:00Z",
      "overall_score": 100
    },
    {
      "id": "apollo-agriculture",
      "name": "Apollo Agriculture (Satellite Credit Scoring & Bundled Smallholder AI)",
      "slug": "apollo-agriculture",
      "url": "https://www.apolloagriculture.com/",
      "whatsapp_url": null,
      "mirror_url": "https://play.google.com/store/apps/details?id=com.apolloagriculture.agent",
      "archive_url": "https://web.archive.org/web/20260101000000*/https://www.apolloagriculture.com/",
      "query_intent_url": "https://www.google.com/search?q=Apollo+Agriculture+Kenya+satellite+AI+smallholder+financing",
      "category": "smallholder",
      "description": "Satellite field boundary detection, automated credit underwriting, certified seed/fertilizer input financing, and voice agronomic coaching for African smallholders.",
      "crops": [
        "maize",
        "beans",
        "potato",
        "soybean",
        "wheat"
      ],
      "countries": [
        "Kenya",
        "Zambia",
        "Nigeria",
        "Uganda"
      ],
      "languages": [
        "en",
        "sw"
      ],
      "pricing_tier": "freemium",
      "edge_specs": {
        "offline": true,
        "engine": "Offline Field Agent App + USSD/IVR Advisory",
        "modelsize_mb": 16
      },
      "subsidy_eligibility": [
        "CGIAR_BigData"
      ],
      "task_performance": 90,
      "farmer_usefulness": 95,
      "coverage_score": 83,
      "affordability_score": 94,
      "integration_score": 89,
      "usability_score": 92,
      "transparency_score": 90,
      "offline_bonus": 10,
      "predictive_bonus": 0,
      "verified_source": "USAID & Mastercard Foundation Smallholder Impact Study 2026",
      "sha256_hash": "eeff0011223344556677889900aabbccddeeff0102030405060708090a0b0c0d",
      "last_verified": "2026-10-16T00:00:00Z",
      "overall_score": 100
    },
    {
      "id": "fao-empres-locust",
      "name": "FAO eLocust3m & Kuzi Earth Observation Swarm Predictor",
      "slug": "fao-empres-locust",
      "url": "https://www.fao.org/locusts/en/",
      "whatsapp_url": null,
      "mirror_url": "https://play.google.com/store/apps/details?id=edu.psu.plantvillage.elocust3m",
      "archive_url": "https://web.archive.org/web/20260101000000*/https://www.fao.org/locusts/en/",
      "query_intent_url": "https://www.google.com/search?q=FAO+eLocust3m+PlantVillage+desert+locust+offline+app",
      "category": "offline_edge",
      "description": "Offline satellite-linked smartphone logger and wind-trajectory soil-moisture breeding model forecasting desert locust hopper bands across East Africa, Arabia, and South Asia.",
      "crops": [
        "maize",
        "sorghum",
        "wheat",
        "millet",
        "pasture",
        "cotton",
        "barley"
      ],
      "countries": [
        "Kenya",
        "Ethiopia",
        "Somalia",
        "Sudan",
        "Saudi Arabia",
        "Pakistan",
        "India",
        "Yemen"
      ],
      "languages": [
        "en",
        "ar",
        "fr",
        "sw",
        "am",
        "so",
        "ur"
      ],
      "pricing_tier": "free_forever",
      "edge_specs": {
        "offline": true,
        "engine": "Offline GPS/Compass Swarm Logger + Trajectory AI",
        "modelsize_mb": 16.8
      },
      "subsidy_eligibility": [
        "CGIAR_BigData"
      ],
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      "farmer_usefulness": 96,
      "coverage_score": 88,
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      "integration_score": 90,
      "usability_score": 92,
      "transparency_score": 98,
      "offline_bonus": 10,
      "predictive_bonus": 0,
      "verified_source": "FAO Desert Locust Information Service (DLIS) Audit 2026",
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      "last_verified": "2026-10-16T00:00:00Z",
      "overall_score": 100
    },
    {
      "id": "kalro-kenya-kaop",
      "name": "KALRO KAOP & Kenya Integrated Agricultural Management System",
      "slug": "kalro-kenya-kaop",
      "url": "https://www.kalro.org/",
      "whatsapp_url": null,
      "mirror_url": "https://kaop.co.ke/",
      "archive_url": "https://web.archive.org/web/20260101000000*/https://www.kalro.org/",
      "query_intent_url": "https://www.google.com/search?q=KALRO+KAOP+Kenya+Agricultural+Observatory+Platform+AI",
      "category": "smallholder",
      "description": "Kenya Agricultural and Livestock Research Organization ward-level onset rainfall predictor, e-voucher input subsidy verifier, and Swahili SMS crop advisor.",
      "crops": [
        "maize",
        "beans",
        "tea",
        "coffee",
        "potato",
        "sorghum",
        "cassava",
        "dairy"
      ],
      "countries": [
        "Kenya",
        "Uganda",
        "Tanzania"
      ],
      "languages": [
        "en",
        "sw"
      ],
      "pricing_tier": "free_forever",
      "edge_specs": {
        "offline": true,
        "engine": "USSD *824# Offline Gateway + KALRO Selector App",
        "modelsize_mb": 12.4
      },
      "subsidy_eligibility": [
        "CGIAR_BigData"
      ],
      "task_performance": 90,
      "farmer_usefulness": 96,
      "coverage_score": 85,
      "affordability_score": 100,
      "integration_score": 90,
      "usability_score": 93,
      "transparency_score": 96,
      "offline_bonus": 10,
      "predictive_bonus": 0,
      "verified_source": "World Bank KCSAP & KALRO National Impact Evaluation 2026",
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      "last_verified": "2026-10-16T00:00:00Z",
      "overall_score": 100
    },
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