FutureAGI

Model evaluation with observability, simulation, datasets, and annotation.

Evaluates model output against a dataset, and reviews where quality dropped.

Use FutureAGI with Snow

Snow is a personal AI assistant that builds real apps for you, and they can put FutureAGI to work.

These are the FutureAGI operations Snow and the apps you build with it can run. Sign in to choose which ones Snow may run without asking.

Look at your data without changing it.

List Agent Definitions
List one page of agent definitions in the connected FutureAGI organization, optionally filtering by type, name, assistant ID, or agent ID. Returns next_cursor to continue.
List Annotation Labels
List one page of FutureAGI annotation labels by type, name, project, or dataset, optionally including usage counts. Returns next_cursor to continue.
List Annotation Queues
List one page of FutureAGI annotation queues by status or name, optionally including item counts. Returns next_cursor to continue.
List Custom Eval Configs
List custom evaluation configurations, optionally restricted to a FutureAGI project or evaluation task.
List Datasets
List one page of datasets in the connected FutureAGI organization, optionally searching by name. Returns next_cursor to continue.
List Eval Tasks
List one page of FutureAGI evaluation tasks, optionally filtering by project ID or task name. Returns next_cursor to continue.
List Personas
List one page of built-in and workspace personas for FutureAGI simulations, with type, simulation-mode, and text filters. Returns next_cursor to continue.
List Run Tests
List one page of configured FutureAGI run tests without executing them, optionally filtering by name, source type, or prompt template. Returns next_cursor to continue.
List Scenarios
List one page of FutureAGI simulation scenarios, optionally filtering by agent definition, agent type, or search text. Returns next_cursor to continue.

Machine learning platform with datasets, models, clusters, predictions, and evaluations.

AI quality with projects, production monitoring, test evaluation, and regression tracking.

AI observability with traces, evaluations, datasets, experiments, and prompt versions.