ipnops

Capabilities · 02

The understanding layer.

Multimodal fusion, environmental embeddings, anomaly detection, and predictive forecasting. The intelligence engine that makes coastal data legible.

Layer · 01

Embed

Every modality is encoded into a shared spatiotemporal embedding space. Satellite tiles, sensor traces, and scientific text all become reasoning-ready vectors.

Layer · 02

Fuse

Cross-modal alignment. A reef section is the same entity whether observed by optical satellite, SAR, drone, or in-situ biodiversity survey.

Layer · 03

Remember

Long-term ecosystem memory — every observation, prediction, and intervention tied to place and time. The platform learns your coast.

Layer · 04

Detect

Anomaly surfacing across modalities. A turbidity spike, a thermal anomaly, an unexplained bathymetric shift — flagged in real time.

Layer · 05

Reason

Gemma-class reasoning over the environmental graph. Ask in natural language; receive spatial, temporal, and probabilistic answers.

Layer · 06

Forecast

TimesFM, GraphCast, and FourCastNet ensembles project shoreline change, storm trajectories, ecosystem trends — with confidence intervals.

Reasoning interface

Speak to the ecosystem.

Plain language in. Spatial, temporal, probabilistic answers out. No GIS expertise required.

"Predict shoreline erosion over 5 years."
"Which reef sectors are degrading fastest?"
"How will this reclamation affect sediment transport?"
"Predict flood risk after monsoon intensification."
"Where should we restore mangroves first for max wave attenuation?"
"Compare 1995 and 2025 shoreline at Hulhumalé."