Nebula Cloud Labs · Collaboration Calls
Bring agentic AI into real spatial research workflows.
Research Challenge
How can agentic AI move from assisting with individual tasks to understanding, planning and executing complete spatial research workflows across data, models, software and evidence?
Current AI tools help researchers with isolated steps — writing code, answering questions, summarizing papers. But spatial research workflows involve chained multi-tool execution: acquiring imagery, processing rasters, running models, comparing results, generating maps, validating against ground truth, and producing reproducible outputs.
This call seeks research that explores how autonomous agents can orchestrate these complete workflows rather than merely assisting with fragments.
Disciplines
Researchers working across spatial disciplines who want to explore agentic AI in their domain.
Spatial data science, analysis, geoprocessing workflows.
Earth observation, satellite imagery, change detection.
Agentic systems, multi-step reasoning, tool orchestration.
City analytics, infrastructure, land use.
Spatial twins, IoT integration, 3D modelling.
HPC, simulation, numerical methods in geoscience.
Lifecycle
Promising research from collaboration calls can become operational capabilities within Nebula Cloud Studio, Workbenches, and Capability Packs.
Context
This call connects to active Nebula Cloud Labs research programs that demonstrate the kind of spatial-AI workflow execution we want to explore more broadly:
We welcome proposals across these and related tracks:
These are example directions, not constraints. We are interested in any research where autonomous agents can improve spatial research workflows.
Apply
Submit a proposal and collaborate with Nebula Cloud Labs on agentic spatial intelligence.