The Fast INtention Agnostic LEarning Server (FINALES) is designed as a broker server mediating between the simulations, experiments, optimizers, and other tenants. It can handle incoming and outgoing requests asynchronously and acts as a central hub in the communication. In contrast to the laboratory orchestration system HELAO , FINALES acts as a brokering service on a hardware independent level by abstracting away from a sequence of hardware events to requesting desired outcomes. FINALES allows for maximum flexibility and redundancy by explicitly allowing several hardware or software services with the same capabilities as well as a virtually unlimited number of simultaneous optimizers. This multi-tenancy design allows for several intention-aware tenants exploring and exploiting the data and services available through the server. The communication with FINALES is defined through Pydantic 54 schemas. This structured representation of the data facilitates the integration of an ontology such as BattINFO . Furthermore, the type-checking, which Pydantic promotes, improves the security of FINALES. Type-checking and automatic validation of input data even allows to include non-automated data acquisition in autonomously orchestrated loops, maximizing the inclusiveness and versatility of FINALES. What most significantly distinguishes FINALES from HELAO or any other automation framework like Bluesky or ChemOS is FINALES' passivity as its operation does not depend on the state of the individual tenants. By design, HELAO, Bluesky or ChemOS operated instruments could be connected to FINALES as tenants. Data management in FINALES works in an append-only mode, which preserves all generated data. Datasets can be rated by the tenant providing it e.g. according to the success or failure of the measurement through a score related to the fidelity of the data. Deletion of requests is not allowed by design.