Ingest
Receive scanned PDFs, TIFFs, images and born-digital documents from client repositories or production systems.
Built for scanning companies, digitization providers, records-management organizations and document-intensive enterprises, DXT AI processes document collections across eras and formats, from microfilm and microfiche to invoices, logs, scanned images and born-digital files.
Document operations rarely fail because OCR is unavailable. They fail because documents vary, exceptions matter, source quality changes and production teams need accountable outputs.
DXT AI is designed around that reality. AI handles repeatable understanding tasks, confidence logic routes uncertain work, reviewers validate what matters, and Skylark can operate the process at scale.
A configurable operating pipeline for high-volume document work.
Receive scanned PDFs, TIFFs, images and born-digital documents from client repositories or production systems.
Identify document types, logical groups, page boundaries and processing paths.
Capture required fields, metadata and document-level intelligence using AI and configurable rules.
Route low-confidence fields and exceptions to human reviewers with source context and auditability.
Apply naming, merge/split, conversion, image/document QC and structured packaging logic as required.
Return validated data, processed files and status outputs into the client's downstream workflow.
DXT AI can complement existing scanning and document-management infrastructure rather than forcing a rip-and-replace model.
Document and page-level routing for mixed batches and complex source sets.
Automated and human-validated capture of client-defined index fields.
Merge, split, naming, page-count analysis and production exception handling.
Review-oriented workflows for readability, orientation, blanks and processing exceptions.
Confidence-driven review and approval for fields or documents that need judgment.
Skylark teams can operate the workflow as an extension of the client's production environment.
DXT AI is not designed to hide uncertainty. Confidence and exceptions become explicit parts of the operating model.
We can map the process, identify automation opportunities and design a production model around your actual documents.