Build. Test. Question.
An open experimentation layer for urban AI. Models, agents, and benchmarks enter the registries only with their task, data, evaluation, and failure modes documented.
Urban AI as a testable system.
Each registry lists public entries of one kind. An entry is a release, not a demo: it states what was built, what it was tested on, where it fails, and how to reproduce it.
Urban representations
Multimodal and spatial models for imagery, maps, mobility, text, and city-scale signals.
Open registry 02 / AGENTSResearch agents
Agents for urban analysis, evidence synthesis, scenario exploration, and planning workflows.
Open registry 03 / BENCHMARKSGrounded evaluation
Open tasks that test generalization, fairness, uncertainty, and practical usefulness.
Open registryNew and updated.
What every entry documents.
Six fields are common to all three registries. Each registry adds fields specific to its kind.
- Urban question
urban_question - The city problem the work addresses, and who is meant to use the result.
- Data provenance
data_provenance - Sources, geography, time span, licence, and processing steps for every dataset used.
- Evaluation
evaluation - Tasks, metrics, baselines, and protocol, with results reported as released.
- Failure modes
failure_modes - Known limitations, observed errors, and conditions under which the result should not be trusted.
- Geographic validity
geographic_validity - Cities tested, and whether claims are local or supported by cross-city evidence.
- Artifacts & citation
versionlicenselinkscitation - Code, configurations, weights or task files, a version, a licence, and how to cite the entry.
Prototype responsibly.
From experiment to entry.
Releases are tracked in the open.
Entries, task files, and evaluation code live in the public repository. Proposals and corrections are handled as issues.