STR
Structured Temporal Representation
Explicit temporal targets for events, dependencies, and state transitions — giving the system something stable and inspectable to reason over, rather than relying on implicit sequence position.
Research direction
Continuity Models
Reliable reasoning across time, state, and workflow.
Continuity models is Rkive's thesis for systems that stay coherent across time, state, and workflow rather than resetting around isolated prompts. In Studio, this manifests as persistent context across editing sessions, publishing chains, and multi-step creative decisions — the system reasons forward instead of starting from scratch at every interaction.
Why continuity matters
Multimodal work unfolds over time — editing sessions, publishing chains, conversations that span days. Continuity keeps context, state, and intent coherent across long-running workflow decisions so the system reasons forward instead of starting from scratch.
UMI
Unified Model Interface
A single input-output contract for all model interactions, enabling native cross-model evaluation, model selection, and fallback routing at the interface level. Continuity depends on how context is exposed.
MFI
Multimodal Fusion Interface
Heterogeneous media inputs — video, audio, images — normalized into modality-specific token sequences. Supports early and late fusion for architecture-agnostic encoding while keeping multimodal context aligned.
Temporal continuity as the mechanism: models and systems keep coherent traces of events, state transitions, and intent across time.
Logical continuity as the result: reasoning remains stable as work evolves instead of resetting at every prompt boundary.
Internally, TEMPO is the program line where this temporal thesis is developed and validated.
