Ai reflex engine for automated policy change intervention

An automated policy intervention system comprising:

• an ingestion interface configured to receive a first version of a policy document and a second version of the policy document;
• a delta-detection engine operatively coupled to the ingestion interface,
• wherein the delta-detection engine is configured to compare the first version of the policy document and the second version of the policy document to identify at least one linguistic difference and, in response, to generate a delta object based on the at least one linguistic difference;
• a mapping engine configured to determine one or more affected target associated with the delta object and to produce at least one context vector configured to describe an operational impact of the at least one linguistic difference;
• a reflex logic core comprising a prompt stack stored in a non-transitory memory and a large language model inference service,
• wherein the reflex logic core is configured to specify at least one remedial control action, a condition under which the at least one remedial control action is to be executed, and an identity of an actor or system authorized to execute the at least one remedial control action;
• an orchestration module communicatively coupled to the reflex logic core,
• wherein the orchestration module is configured to execute the at least one remedial control action on the one or more affected target by issuing at least one programmatic call to an external system interface;
• and
• an audit ledger configured to record the delta object, the at least one context vector, an identifier of the executed at least one remedial control action, and a reasoning trace produced by the reflex logic core.

A non-transitory computer-readable storage medium encoded with instructions that, when executed by one or more processors of a computing system, cause the computing system to perform operations comprising:

• receiving a first version of a policy document and a second version of the policy document;
• comparing, via a delta-detection module, the first version of the policy document and the second version of the policy document to identify at least one linguistic difference and, in response, generating a structured delta object that characterizes the at least one linguistic difference;
• mapping, via a contextual-mapping module, the structured delta object to determine one or more affected target and to produce at least one context vector to describe an operational impact of the at least one linguistic difference;
• executing, by a reflex logic core, a large language model inference service to receive the structured delta object and the at least one context vector,
• wherein the reflex logic core is configured to specify at least one remedial control action, a condition under which the at least one remedial control action is to be executed, and an identity of an actor or a system authorized to execute the at least one remedial control action;
• invoking, via an orchestration module, the at least one remedial control action on the one or more affected target by issuing at least one programmatic call to an external system interface;
• and
• recording, in an audit ledger, the structured delta object, the at least one context vector, the at least one remedial control action, and a reasoning trace produced by the reflex logic core.