[LLM Capsule] On-Prem AI Workflow Layer for Sensitive Operational Data

The log that would close the ticket cannot leave the building, so your model never sees it. LLM Capsule lets enterprises run AI on operational data that cannot leave their environment. Logs, tickets, PDFs, network topology and runbooks often hold values that legally or physically cannot move to an external model. Capsule turns those values into protected working versions inside your environment, lets approved models work on the protected version, and reconstructs usable results back in your workflow. Masking breaks the workflow: a redacted log stops being a log, and the AI can no longer do root-cause analysis. Capsule keeps the structure the AI needs. The model path can be external; the original values do not have to be. Your team defines what is sensitive, so protection covers more than names and card numbers like circuit IDs, AS numbers, topology nodes, OT asset IDs, incident IDs and internal codenames. Capsule runs on-prem, in your VPC, or in air-gapped environments. The original values and the mapping used for reconstruction stay inside the customer-controlled environment. It is already deployed in some of the hardest operational environments in telecom, OT and the public sector. Capsule opens the blocked data path on-prem. Syntitan (cloud AI-ready data platform by CUBIG) then validates and operates the workflow in production.

Differential-privacy-based mechanisms are used to reduce re-identification risk when replacement values are combined with external data. Reconstruction is not a mathematical inversion of those values; it is performed only inside the customer-controlled environment through a protected mapping layer. The original values and the mapping never leave the customer environment.