Gatkul IAOS · Programs
Layered architecture
A buyer-facing map of how IAOS holds an intelligence amplification program together — from model study through integration deployment — without pretending to replace your ML infrastructure or replace institutional ethics review.
01 · Model study workspace
Structured environments for benchmarking and understanding AI models — hypothesis lineage, experiment evidence, and comparative analysis trails.
02 · Neural architecture exploration
Labs for studying architectures from feedforward networks to transformers — tied to real deployment constraints and interpretability.
03 · Human-AI integration design
Tooling for prototyping and evaluating how AI integrates into human cognitive and operational workflows.
04 · Emerging technology track
Governed exploration of neural interfaces, ambient intelligence, and next-generation human-machine interaction research.
05 · Cohort collaboration layer
Multi-institution research groups and builder cohorts — shared workspaces, versioned experiments, and structured knowledge exchange.
06 · Responsible AI governance
Human oversight paths, safety checkpoints, ethics review integration, and deployment guardrails built into the architecture.