Your process data stays priviate.
KEVIN is designed to protect customer and process information throughout the recommendation workflow. Data entered into KEVIN is stored on the AmeriCOM server and is not automatically sent to public AI services or cloud-based language models.
What KEVIN does – and does not do – with your data.
The system keeps process information inside the AmeriCOM environment, limits access to authorized functions, and separates incomplete records from verified historical evidence.
Customer and process data remains on the AmeriCOM server so runs can be reviewed later and kept as a complete process history.
KEVIN does not send proprietary manufacturing information to ChatGPT, Claude, Gemini, or other public commercial AI services during normal operation.
Only completed and validated polishing runs can be used to improve future recommendations.
Historical process records are password protected and access is restricted to authorized users and functions.
A protected record from initial case to final outcome.
KEVIN saves the case so it can be reviewed later and, when final polishing results are available, compared against what actually happened. That creates a complete record without allowing incomplete data to influence future recommendations.
Enter the process and measurement information needed for KEVIN to review the run.
The information is stored securely on the AmeriCOM server so the case can be reviewed again later.
When the polishing run is finished, the actual outcome can be compared with the recommendation.
A completed and validated record may then support future recommendations. Incomplete records remain stored but do not influence them.
Designed to keep proprietary process information contained.
The application exposes only the limited information necessary to support authorized functions within KEVIN.
Run information is retained inside the KEVIN environment for later review and comparison.
That includes services such as ChatGPT, Claude, Gemini, and other commercial AI platforms.
Password protection and limited software access help keep historical records controlled.
Real-world results can improve KEVIN – incomplete guesses cannot.
Historical polishing records are used only to improve the quality and consistency of future recommendations inside KEVIN. A run must be completed and validated before its outcome can be considered as evidence.
Verified outcome data can help KEVIN measure the effectiveness of earlier recommendations and build a stronger evidence base for later runs.
These records remain available for reporting and history, but they are excluded from subsequent recommendation logic until they are completed and validated.
Preserve the process history. Learn from verified outcomes. Keep the data controlled.
KEVIN’s data model is designed to make recommendations more consistent over time without handing customer process information to public AI platforms. The value comes from completed, validated polishing results that remain within AmeriCOM’s controlled environment.
Customer process information remains under the control of AmeriCOM and its authorized users, while validated historical outcomes can be used within KEVIN to improve recommendation quality.