KVASIR replaces farmer self-attestation with satellite-observed, audit-defensible proof of conservation tillage, cover crops, and crop rotation across every acre in your supply shed.
USDA acknowledged that only 3% of eligible producers participate in carbon markets due to high transaction costs. The rest are self-reported and unaudited, creating risk exposure for every facility relying on those claims for CI reductions.
The voluntary carbon market collapsed when independent research found the vast majority of credits failed to deliver real emissions reductions. Self-attested CSA claims face the same scrutiny. The IRS will not accept what cannot be independently verified.
KVASIR does not model what farmers say they did. It observes what physically happened: tillage disturbance, residue presence, cover crop emergence, rotation patterns. Sentinel-1 radar and Sentinel-2 optical imagery at 10-meter resolution.
Every classification traces from raw satellite observation to spectral feature extraction to Census-calibrated learning to uncertainty quantification to pixel-level map. No black boxes. No synthetic data. No forced classifications. Every ambiguous pixel is labeled UNKNOWN rather than claimed.
We provide what can be confidently verified, not the maximum that could be claimed. That is exactly what Treasury, the IRS, and your auditors expect from a verification system. If a pixel cannot be defended, it is not claimed.
Six-dimensional spectral analysis detects crop residue via the Normalized Difference Tillage Index with soil-corrected signatures. Two-stage classification uses optical for primary detection and SAR coherent change detection for three-tier separation: no-till, reduced-till, and conventional.
Eight-month trajectory analysis tracks vegetative signal from October through May, capturing emergence, winter persistence, spring peak, and termination. Learned from Census 2022 ground truth, stratified by soil type using published Gozukara corrections for Mollisol accuracy.
C3/C4 phenology separation identifies corn vs. soybean via summer NDVI trajectories. Multi-year pixel tracking confirms rotation patterns at the individual field level, the practice with the largest CI impact in the GREET model.
Every 45Z credit you claim will eventually face examination. KVASIR provides a pixel-level audit trail from satellite observation to acreage claim, with uncertainty quantified and disclosed. Methodology maps directly to §2100.051 tillage tier definitions.
Know exactly which practices are happening across your entire sourcing region, not just the farms that self-report. Identify conservation tillage hotspots, cover crop adoption patterns, and rotation rates at county and parcel level.
Three-tier tillage classification means no-till acres earn larger CI reductions than reduced-till. Most systems cannot distinguish the two. KVASIR's SAR-optical fusion enables the differentiation, so you claim the credit each acre actually earns.
Self-attestation creates friction with growers and administrative overhead for your team. Satellite verification works independently. No enrollment forms, no farm visits, no data collection portals. The observation happens whether or not the farmer participates.
| Capability | KVASIR Intelligence™ | Typical Ag-MRV Platforms |
|---|---|---|
| Primary detection method | Multi-sensor satellite observation (Sentinel-1 SAR + Sentinel-2 optical) | Farmer-reported data supplemented with satellite |
| Ground truth calibration | USDA Census 2022 — learns signatures from verified ground truth | Model-estimated or self-reported baselines |
| Tillage tier resolution | ✓ Three-tier: no-till / reduced-till / conventional (via SAR CCD) | ~ Binary: tilled / not-tilled (optical only) |
| Uncertainty handling | ✓ Explicit UNKNOWN class — ambiguous pixels excluded | ✗ Forced classification — all pixels assigned |
| Synthetic training data | ✓ Never — all observations from real satellite data | ~ Often used to fill gaps in training sets |
| Farmer enrollment required | ✓ No — operates independently of farmer participation | ✗ Yes — requires farmer sign-up and data entry |
| Audit trail depth | Pixel → feature → LDA score → classification → acreage (fully traceable) | Aggregate confidence scores per field |
| Soil correction methodology | ✓ Gozukara-corrected for Mollisol spectral interference | ✗ Generic models without soil-type stratification |
| Regulatory mapping | Direct to §2100.051 (tillage), §2100.052 (cover crops), FD-CIC inputs | Generic conservation practice categories |
170 pages of proposed regulations. ISO 14065 verification required. Safe harbor for third-party substantiation established.
Window to submit comments on proposed regulations, including evidence that satellite verification should be formally recognized.
Treasury anticipates the FD-CIC module will be published this year, activating CSA practice verification requirements for CI scoring.
Extended through OBBBA. Four production years remaining to maximize credit capture with verified practices.
We will prepare a confidential analysis of conservation practice adoption across your sourcing counties, using the same methodology deployed across 1.9 million acres.
Your information is confidential and used only to prepare your briefing. We do not share data with third parties.