Structure-Preserving Processing
Replacing sensitive elements while maintaining document layout, entity relationships, and semantic context for accurate AI processing — a core capability of LLM Capsule.
Explanation
Flat masking treats every sensitive value as an independent token, replacing each with a generic placeholder. This collapses entity relationships, breaks table schemas, and removes the structural information AI models use for comprehension.
Structure-preserving processing maintains these relationships. When the same entity appears in multiple locations, all occurrences map to the same replacement. Table column headers and row identifiers remain semantically consistent. Cross-references between document sections maintain their logical connections.
Example
A contract references "Acme Corp" 47 times across 30 pages — as a party in the preamble, a signatory in the execution block, and a reference in 12 obligation clauses. Structure-preserving processing replaces all 47 instances with ENTITY_A, maintaining the ability for AI to track Acme Corp's obligations throughout the document.
See LLM Capsule Structure-Preserving Processing in Action
Experience how enterprise documents retain full structural integrity throughout the encapsulation and AI processing pipeline.
Enterprise AI Enablement by CUBIG
![](data:image/svg+xml,<svg display="block" role="presentation" viewBox="0 0 148 16" xmlns="http://www.w3.org/2000/svg"><path d="M 11.102 15.765 L 0 15.765 L 0 0.225 L 3.59 0.225 L 3.59 12.61 L 11.102 12.61 L 11.102 15.766 Z M 24.19 15.765 L 13.086 15.765 L 13.086 0.225 L 16.676 0.225 L 16.676 12.61 L 24.188 12.61 L 24.188 15.766 Z M 26.177 0.226 L 29.85 0.226 L 34.324 10.366 L 38.798 0.226 L 42.472 0.226 L 42.472 15.765 L 38.882 15.765 L 38.882 7.361 L 35.526 14.844 L 33.13 14.844 L 29.774 7.36 L 29.774 15.764 L 26.184 15.764 L 26.184 0.225 L 26.177 0.225 Z M 57.981 0 C 60.649 0 62.947 1.352 64.375 3.556 L 63.362 4.334 C 62.01 2.341 60.09 1.27 57.99 1.27 C 54.4 1.27 51.785 4.139 51.785 8.012 C 51.785 11.886 54.453 14.74 58.058 14.74 C 60.219 14.74 62.138 13.698 63.499 11.674 L 64.467 12.452 C 63.068 14.626 60.694 16 58.056 16 C 53.741 16 50.469 12.565 50.469 8.011 C 50.469 3.458 53.696 0 57.996 0 Z M 65.483 15.765 L 71.62 0.225 L 73.335 0.225 L 79.472 15.765 L 78.142 15.765 L 76.562 11.793 L 68.392 11.793 L 66.812 15.765 L 65.482 15.765 Z M 76.079 10.57 L 72.466 1.456 L 68.869 10.57 Z M 81.833 15.765 L 81.833 0.225 L 87.872 0.225 C 90.706 0.225 92.55 2.008 92.55 4.711 C 92.55 7.414 90.706 9.151 87.872 9.151 L 83.14 9.151 L 83.14 15.765 L 81.832 15.765 Z M 83.141 7.92 L 87.811 7.92 C 90.048 7.92 91.212 6.651 91.212 4.718 C 91.212 2.785 90.049 1.464 87.812 1.464 L 83.14 1.464 L 83.14 7.92 Z M 95.465 12.028 C 96.553 13.81 98.299 14.739 100.196 14.739 C 102.093 14.739 103.891 13.697 103.891 11.96 C 103.891 10.224 102.607 9.499 99.757 8.495 C 96.583 7.37 94.973 6.275 94.973 4.077 C 94.973 1.389 97.467 0 99.773 0 C 102.304 0 103.99 1.314 104.821 2.71 L 103.808 3.488 C 102.924 2.008 101.496 1.268 99.772 1.268 C 98.049 1.268 96.296 2.243 96.296 4.048 C 96.296 5.489 97.528 6.328 100.158 7.218 C 103.952 8.51 105.214 9.71 105.214 11.938 C 105.214 14.573 102.818 16 100.196 16 C 97.785 16 95.54 14.784 94.49 12.806 L 95.457 12.028 Z M 108.278 0.226 L 109.578 0.226 L 109.578 10.102 C 109.578 12.835 111.475 14.715 114.528 14.715 C 117.581 14.715 119.478 12.85 119.478 10.102 L 119.478 0.226 L 120.778 0.226 L 120.778 10.102 C 120.778 13.636 118.398 15.999 114.528 15.999 C 110.659 15.999 108.278 13.629 108.278 10.102 Z M 124.785 15.765 L 124.785 0.225 L 126.092 0.225 L 126.092 14.512 L 135.056 14.512 L 135.056 15.772 L 124.785 15.772 Z M 137.67 0.226 L 147.329 0.226 L 147.329 1.464 L 138.978 1.464 L 138.978 7.097 L 146.188 7.097 L 146.188 8.343 L 138.978 8.343 L 138.978 14.534 L 147.571 14.534 L 147.571 15.773 L 137.67 15.773 Z" fill="rgb(35, 31, 32)" height="16px" id="o43yy6bJZ" width="147.57099816894532px"/></svg>)