Sentinel-1 and Sentinel-2, super-resolved.

NeuralQ is a remote-sensing R&D startup bridging cutting-edge AI research and real-world applications. We super-resolve freely available satellite imagery into sub-meter-class intelligence, prove it in agriculture, and back it with geospatial consulting.

• Sentinel-2 Super-Resolution: Model-derived optical enhancement toward a 1 m grid, consistency-constrained so block averages match the observed 10 m measurements exactly. Demonstrated in agricultural landscapes.
• Sentinel-1 Super-Resolution (S1SR): Cross-band SAR enhancement of 10 m C-band radar toward sub-meter X-band-like detail, built on conditional diffusion models and SAR-rigorous evaluation. In active development.
• The Agritech Suite: One packaged solution on the engines with five capability modules: crop identification, AI field boundary detection, crop type classification, change detection, and sustainability benchmarking.

Geospatial strategy and feasibility consulting, satellite and aerial data processing, and engineering engagements that put the engines inside partner products. Every engagement is scoped and priced before work begins.

• Evidence before claims: worked examples are published, maturity states are labeled honestly, and internal benchmarks are shared under engagement.
• Provenance on every pixel: model-derived outputs are labeled as model-derived and never masquerade as measurements.

• Website: neuralq.github.io
• LinkedIn: NeuralQ on LinkedIn
• Email: hello@neuralq.ai