neuron-js

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AI-rule safety ​

LLMs are great at drafting JSON business rules — and that's exactly the risk. A plausible-looking rule can still encode the wrong field, the wrong threshold, or the wrong action. Neuron-JS exists so AI-drafted rules become safe to run: schema-validated, constrained to a developer-owned vocabulary, reviewable like code, and explainable after the fact.

AI drafts. Neuron-JS verifies.

1. AI can draft rules ​

A plausible JSON rule can still encode the wrong assumption, field, or action — it is not production-ready on its own.

A developer inspects an amber LLM-generated JSON rule card. A small rose warning marker highlights a risky business assumption, with text saying the draft is not production-ready.

2. Validate before runtime ​

Schema-first checks (validateScript) reject malformed scripts before they ever execute, and return the exact JSON path to fix.

A JSON rule passes through a schema validation gate. One invalid path is blocked in rose with an exact JSON path, while a corrected rule exits with an emerald pass marker.

3. Constrain what can run ​

A developer-owned registry defines the approved actions, conditions, parameters, and rules. Anything outside that vocabulary simply cannot execute — no arbitrary code.

A validated rule enters a developer-owned registry boundary. Approved action and condition tiles connect in cyan, while an unapproved action is blocked outside the boundary.

4. Review like code ​

Generated rules are serializable data, so they go through the same governance as code: tests, owner approval, and rollback — never automatic AI approval.

A generated rule card sits beside a review checklist showing tests, owner approval, and rollback snapshot. The visual emphasizes governance before production use.

5. Then execute deterministically ​

Synapse runs the approved rule path deterministically, and the explanation trace shows why the decision matched or failed — ready for audit, logs, or a support ticket.

An approved JSON rule flows into a Synapse execution node. A result card and violet explanation trace rows show why the rule matched and what action ran, with the caption "AI drafts. Neuron-JS verifies."

In short ​

Validate → constrain → test → approve → execute → explain. Deterministic workflow logic with auditability is the guardrail that makes AI-assisted business rules safe to ship.