Knowledge-centric.
Model-agnostic.
Research-native.
KAMI.OS is a Research Operating System for end-to-end academic research orchestration — connecting knowledge, workflow, integrity, identity, and research intelligence into one operational layer.
KAMI.OS EDU
The operational environment for academic research, workflows, knowledge, and AI-assisted research orchestration.
Research Intelligence
Live aggregate intelligence from the KAMI.OS research ecosystem, powered by the operational research layer.
KAMI.OS Entitlement
Service authorization and entitlement management for the KAMI.OS ecosystem.
Operational proof from a live research ecosystem.
Aggregate research activity provides a measurable view of platform adoption and operational depth. Public metrics are intentionally privacy-safe and contain no researcher-level personal information.
An operational layer for trustworthy research automation.
KAMI.OS combines integrity controls, research state infrastructure, orchestration, and auditable execution into a model-agnostic architecture.
Integrity Guard Engine
Integrity validation, risk classification, policy checks, and decision routing before automated processing.
Research State Orchestration
Event-sourced research state, session observability, replay, drift detection, and operational metrics.
Audit Trace
Structured traceability across decisions, sessions, events, execution fingerprints, and workflow routing.
Model-agnostic Architecture
Designed around knowledge and orchestration layers rather than dependency on a single AI model provider.
MCP Integration
Tool and system connectivity for structured AI-assisted research operations.
Workflow Orchestration
n8n provides workflow execution, webhooks, integrations, and automation infrastructure beneath the public platform.
Integrity decisions should be traceable.
IGE evaluates research inputs through structured validation, metadata analysis, risk scoring, and decision routing.
Decisions can produce structured trace IDs, severity scores, event identifiers, execution fingerprints, and workflow routing metadata for institutional traceability.
Observable research state, not a black box.
RSO provides operational observability across research sessions, events, replay, drift, and unresolved workflow states.
Research behind the system.
Sutrisno, Agus and Lastriyanto, Anang. (2026).
“KamiOS: A Knowledge-centric and Model-agnostic Research Operating System for End-to-End Academic Research Orchestration.”
July 30, 2026 · SSRN
Move from research workflow to research operating system.
Explore the operational environment where KAMI.OS connects research knowledge, orchestration, integrity, and intelligence.
Open KAMI.OS EDU →