GIOS enables non-technical business operators to deploy complex automations using only natural language, compiling workflows directly from their own existing business documents. With no coding, no configuration, and no workflow canvas required, GIOS eliminates unconstrained autonomous agent loops to provide enterprises with a highly durable, cost-predictable, and deterministic operating system.
| Framework |
Causal Structure Execution Framework (CSEF) comprising 4 decoupled, proprietary libraries (Planning, Compiling, Editing, Runtime) |
| Paradigm |
Asynchronous, graph-orchestrated microservices (strictly non-agentic) |
| Data Contracts |
Strictly typed LLM outputs with rigid schema validation |
| Core Stack |
PostgreSQL, FastAPI, Next.js, and distributed microservices engineered for horizontal scaling |
| AOT Graph Compilation |
Workflows are compiled ahead-of-time, allowing the system to identify execution gaps, resolve dependencies, and rigidly map input/output data schemas between nodes prior to runtime |
| Execution |
Idempotent runtime; demand-driven graph execution where nodes activate precisely when causal dependencies are met |
| Agent Boundaries |
When native agents (e.g., Magellan) are deployed, they are scoped to a single node, execute idempotently, and act strictly as individual tools within the broader graph |
| Infrastructure |
Google Cloud Platform (GCP) |
| Database |
PostgreSQL backend for ACID-compliant, durable state tracking |
| Task Duration |
Natively supports asynchronous, long-running processes (1+ years) |
| Continuity |
Stateful orchestration allows seamless pause, branch, and resume |
| Durability |
Workflow state is persisted independently of execution workers; failures, restarts, and extended waits do not require replaying the workflow from its origin |
| Concurrency |
Natively handles complex fan-in / fan-out execution paths; a single graph structure supports multiple concurrent listeners without duplicating baseline job state |
