RUNTIME LABS
About
Runtime Labs anchors language models in time, location, and context. Our work is grounded in two convictions: grounding language models in real-world event structure increases their reliability and utility, and time is a foundational primitive for memory, planning, and coordinating between natural language intent and physical action.
Óra is our first release. It serves as a scheduling engine and interaction surface where natural language conversations, memory, and events coexist on a shared timeline. Users can create events, manage context, and engage with language models in ways that produce persistent, actionable plans grounded in real-world constraints.
Runtime Labs is building toward a new class of systems where language models function as persistent, time-aligned collaborators — capable of reasoning across past, present, and future state — and where scheduling, memory, and planning are unified within a single coherent interface.
Research
We develop infrastructure that enables language models to reason over time, maintain persistent context, and operate on structured representations of real-world events. This includes systems for temporal indexing, memory persistence, and context retrieval that allow models to interpret past activity, manage future plans, and respond coherently within an evolving timeline.
This research makes it possible for language models to function reliably in scheduling and planning environments, where correct behavior depends on understanding temporal relationships, user intent, and shared contextual state.
Product
Óra is built on Runtime Labs' temporal infrastructure, enabling language models to operate on persistent, time-structured state rather than isolated prompts. Outcomes are durable and live on a continuous timeline anchored in real-world time and location.
Users can plan and manage their schedules through natural language conversation. Language models interpret intent, propose structured events for approval, and update the timeline accordingly. Each interaction contributes to a persistent system state that maintains continuity across past activity and future plans.
By grounding language model interaction in temporal structure and shared context, Óra transforms conversation from a transient interface into a reliable system for planning, scheduling, and managing real-world commitments.
Values
- We pursue truth rigorously and treat others with respect and care.
- We allocate time, capital, and compute deliberately.
- We exercise discipline and restraint in product design, release, and external outreach, while maintaining urgency in daily execution.
- We adapt quickly when diminishing returns in product or research become evident.
- We maintain a respectful environment where criticism and feedback are treated as essential inputs to invention.