Models become replaceable engines
Local, cloud, multimodal, embedding, and specialist models should plug into a runtime without forcing the product to be rebuilt around each model.
The runtime layer after the LLM
Machine Intelligence Runtime
LLM runtimes run models. Machine Intelligence Runtime runs the intelligence layer around them: tools, memory, agents, policies, approvals, local endpoints, and evidence.
- Local-first control
- Tool mediation
- Typed memory
- Evidence trails
MI
Models
Tools
Memory
Policy
Evidence
Category shift
From token streaming to governed execution
The future of AI runtime infrastructure is not only faster inference. It is a runtime control plane for intelligent work.
Tools become controlled contracts
Tool calls need schemas, permissions, approval gates, error recovery, and clear evidence of what happened.
Memory becomes a governed asset
Memory must be scoped, inspectable, editable, and tied to user consent rather than hidden inside unbounded context.
Runtime architecture
The model is not the runtime
A production-grade Machine Intelligence Runtime separates model execution from policy, memory, tool permissions, state transitions, telemetry, and evidence. This keeps intelligent systems adaptable and reviewable.
Explore the runtime stackApplication
Orchestration
Policy
Memory
Tools
Models
Evidence
Why it matters
The next runtime must prove its work
As AI systems move from answers to actions, users need a durable trail of requests, context, tools, decisions, approvals, and artifacts.
Local-first intelligence
Control should remain visible where work happens
Machine intelligence increasingly touches private files, code, messages, schedules, and business workflows. A local-first runtime keeps sensitive decisions close to the user while still allowing hybrid model routing when appropriate.
Read local-first principlesRuntime control plane
- Inspect context before use
- Approve high-impact actions
- Route models by privacy and capability
- Export evidence after execution
MiRuntime.com
The future of AI runtimes is Machine Intelligence Runtime.
Define the category now: controlled execution for models, tools, agents, memory, policies, and evidence.