Skip to main content

Documentation Index

Fetch the complete documentation index at: https://docs.neuro-tech.io/llms.txt

Use this file to discover all available pages before exploring further.

State machines give the platform a structured way to model processes that evolve over time. Not every workflow is a single action. In real systems, agreements, permissions, payments, and asset-related processes often move through a series of defined states — such as draft, pending approval, active, fulfilled, suspended, or archived. In Neuro, state machines are part of the platform’s programmable logic model and can be connected to tokens, contracts, and payments.

​
Why they matter

A state machine makes business logic explicit. Instead of hiding process rules across multiple services, database flags, and custom scripts, a state machine defines which states exist, what transitions are allowed, and what actions can happen when a transition occurs. This is especially useful when workflows need to be predictable, automatable, and auditable. Neuro connects state machines to token behavior, contract execution, and programmable payment flows.

​
How they fit into the platform

In Neuro, state machines are not isolated workflow diagrams — they are part of a broader trust model. They can be connected to smart contracts, to signed actions by identified parties, and to tokens that carry rules over time. Tokens whose logic is governed by state-machine definitions inside the corresponding smart contract can also drive payment-related behavior.

​
What they can be used for

State machines are a good fit for workflows such as:
  • Contract lifecycles
  • Approval flows
  • Escrow-like processes
  • Milestone-based payments
  • Subscriptions, leases, and recurring obligations
  • Tokenized assets that change state over time
  • Operational processes that need explicit transitions and history
This is one of the reasons state machines are valuable in Neuro: they make automation and governance work together instead of being treated as separate problems.

​
Key takeaways

A state machine turns process logic into a first-class platform object. That makes it easier to reason about:
  • What can happen next
  • Who is allowed to trigger it
  • What data or signatures are required
  • What should be recorded
  • What action should follow a transition
A state machine gives contracts, tokens, and workflows a structured lifecycle.

​
Real-world context

State machines become especially important in operational environments where workflows must be governed explicitly:
  • Medical record consent flows — A consent agreement can move through states like pending, approved, active, revoked, and expired, with each transition requiring specific actor roles and signatures.
  • Real estate token lifecycle — A tokenized property asset might move through states tied to listing, sale agreement, payment confirmation, and ownership transfer — each tied to contract rules and ledger-backed events.
  • IoT device provisioning — Device onboarding, activation, and decommissioning can be modeled as a state machine with explicit transition rules and audit trails.
  • Payment flows — Milestone-based or escrow-like payment processes benefit from a state machine model that defines when funds are released and what conditions must be met.

​
Further reading

Neuro-Foundation

Platform specification and standards

TAG Documentation

Neuron and associated technologies

TAG Community

Tutorials and implementation guides