PaperVision Migration

System Overview

PaperVision is an enterprise content management system from Digitech Systems designed for document capture, indexing, storage, and retrieval. The platform uses a structured archive model where metadata is stored in SQL Server databases and document images are organized across static storage locations on the file system.

PaperVision supports multiple project types, each with its own set of index fields and storage configuration. While PaperVision served many organizations well as an early-generation document imaging solution, the platform has aged significantly. Organizations running PaperVision often face hardware dependencies on older server configurations and limited integration capabilities with modern business systems.

Specific Technical Challenges

PaperVision's flat file storage model and reliance on SQL metadata for all document context create a fragile relationship between files and their meaning.

Opaque Numeric File Naming

Documents are stored as flat files in a directory structure using internal numeric IDs with no human-readable file names or folder paths. Without the database, there is no way to determine what any file contains or who it belongs to.

Database-Dependent File Identity

The SQL metadata contains the only mapping between file IDs and their index values. If the database is corrupted, incomplete, or out of sync with the file system, files become permanently orphaned with no way to identify their content.

Proprietary Legacy Compression

Older versions used a proprietary compression format for stored images that requires Digitech's own tools to decompress. Standard image libraries cannot read these files, and the compression format is not publicly documented.

Multi-Queue Document Versions

Multiple document queues including capture, QC, and production may contain different versions of the same document at different processing stages. Determining which version is authoritative requires understanding the queue workflow logic.

Detached OCR Text Indexes

OCR text indexes are stored separately from the document files and may not correspond to the final version of the document. Migrating the OCR text without verifying it against the current document version can produce misleading search results.

Unmounted Volume Storage

Volume-based storage means documents can span multiple physical volumes including drives and network shares that may no longer be mounted or accessible. Locating and reconnecting all volumes is a prerequisite before extraction can begin.

How Merkh Helps

Precision has reverse-engineered the PaperVision database schema across multiple versions of the platform and built extraction tools that resolve numeric file IDs back to their full metadata context. We handle proprietary compression formats, reconnect unmounted storage volumes, and reconcile OCR indexes against current document versions. Our team validates every extracted document against the source database to ensure complete, accurate output, producing audit-ready export packages for your target platform.

PaperVision Migration Experts