Architecture over models.
Jarvis Runtime is an AI runtime architecture that separates intelligence from language models.
Connect any LLM as a language engine.
Build behavior, memory, logic, and control above it.
Change models without changing the system.
What is NexusCores?
NexusCores is an organization and platform focused on the design and development of system-level AI runtime architectures. It is not a chatbot, not a single model, and not a wrapper around LLM APIs.
The core architectural foundation developed within NexusCores is the Jarvis Runtime Architecture — a runtime-first approach that treats language models as replaceable execution engines rather than sources of system behavior.
- —Architecture-first, runtime-centric design
- —Strict separation between memory, reasoning, and language generation
- —Deterministic control layers on top of probabilistic models
- —Provider-agnostic and model-agnostic by design
- —Trigger-based memory systems instead of vector-only retrieval
- —Explicit orchestration of roles, states, and execution flow
Jarvis Runtime
Jarvis Runtime is an implementation of NexusCores principles.
LLMs are treated as language generators, not intelligence
Behavior is defined by architecture
Memory is real, not simulated
Calculations are deterministic, not guessed
Responses reflect input signal, not forced personality
Minimal input produces minimal output.
The system does not invent intent.
Why not a typical AI chat?
Typical AI Chat
- •Fixed provider
- •Prompt-based personality
- •Random behavior shifts
- •Over-explains by default
- •Pretends to remember
Jarvis Runtime
- •Any provider
- •Architecture-defined behavior
- •Stable logic
- •Responds to signal, not assumptions
- •Real memory and recall
Choose your model. Keep your system.
Jarvis Runtime supports multiple AI providers through adapters. Switch providers without rewriting logic or behavior.
OpenAI-compatible APIs
Anthropic
Google Gemini
Mistral
DeepSeek
HuggingFace
You own the keys.No vendor lock-in.
How it works
User input is analyzed
Context and memory are resolved
Roles and rules are applied
Deterministic tools run if needed
LLM is called only for language generation
Memory is updated
Notes & Articles
Architecture notes, system design essays, and thoughts on AI beyond hype.