Cloud AI pays for compute forever. TIMA pays once.
Every cloud-first ML platform re-buys GPU time with every customer scan. TIMA trains on rented clusters as a bounded, one-time cost per model generation — then inference runs free on hardware the customer already owns. Watch the same 12-month workload:
For government, defense, and rural emergency-management buyers, the same architecture is also the compliance story: on-premise, air-gap-capable deployment with no data leaving the building — a requirement cloud-bound competitors structurally cannot meet.
Every hour online makes the dataset harder to catch.
High-quality labeled severe-weather data is the industry's constraint: scarce, expensive, and slow to construct. TIMA's foundation — 16,000 indexed events matched to 1.64 TB of raw NEXRAD — took years to assemble. The flywheel extends it automatically with live-captured, human-verified cases that exist nowhere else.
The model is open source under AGPL-3.0; the operationally-captured verification dataset is the proprietary asset. Community trust and commercial defensibility from the same architecture — and a competitor can only replicate the dataset by running for years.
We found our own inflated number. Then we published the real one.
When early training produced a suspiciously perfect AUC, we diagnosed temporal data leakage, rebuilt the entire protocol around strict leak-safe storm-day splits, and published the honest figure with full methodology. In safety-critical AI, inflated benchmarks fail procurement audits — rigor is what government buyers and grant committees actually purchase.
An automated triage fabric for severe weather.
Emergency Management
Objective, ranked threat assessment across dozens of simultaneous warnings — a defense against outbreak-mode cognitive overload for regional dispatchers and EOCs. Grant-fundable, county by county.
Defense & Logistics
Hyper-localized kinetic hazard identification for high-value defense infrastructure and supply-chain routes — deployable on-premise and air-gapped, where cloud AI is disqualified by policy.
Parametric Insurance
Archived kinematic signature scores provide instant, objective storm-intensity verification for parametric severe-weather claims — settlement in minutes, no adjuster in the field.
Where investment goes to work.
Each phase attacks the remaining false-alarm frontier — and converts detection into the metric that actually saves lives: lead time.
Phase 01 · Dual-Pol Debris Fusion
Integrate NEXRAD Level II correlation-coefficient channels. Co-located CC drops with tightening velocity couplets confirm airborne debris — the definitive tornado signature.
Phase 02 · Environmental Fusion
A secondary branch conditions radar scores on HRRR soundings — CAPE, storm-relative helicity, LCL height — down-weighting rotation in environments hostile to tornadogenesis.
Phase 03 · Temporal Nowcasting
Move from single-snapshot scoring to convolutional-recurrent sequence modeling — capturing the tightening trends that precede tornadogenesis.
Fund the minutes that matter.
We are engaging angel investors, grant committees, and strategic partners to accelerate Phases 01–03 and bring automated storm triage to every county that needs it.