Abstract
Enterprise service platforms can present operational challenges due to reactive support models and compliance risks associated with managing sensitive data, such as personally identifiable information (PII). A dual-function architecture may integrate a proactive intervention engine and an augmented data compliance framework. The intervention engine can analyze real-time data signals from various enterprise systems using an inference layer, such as a large language model, to predict potential user friction points and deliver preventative interventions. Concurrently, the compliance framework can provide a proactive component for detecting potential PII for human-in-the-loop review and an on-demand utility for creating non-destructive, anonymized versions of data records. This integrated system may be used to shift enterprise support from a reactive to a more proactive model while providing a flexible, artificial intelligence-assisted framework for managing data privacy and compliance.
Publication Date
2026-01-07
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Kayande, Tanmay; Agrawal, Pooja; Dambhare, Akash; P, Mohith; and Raithatha, Deep, "System for Proactive Intervention and Dual-Mode Data Compliance", Technical Disclosure Commons, (January 07, 2026)
https://www.tdcommons.org/dpubs_series/9142