What encoding is the output text in?

Output .txt files use UTF-8 encoding, which is compatible with standard text processing tools, Python, and most data pipeline frameworks.

How do I handle OCR errors in a downstream pipeline?

The most reliable approach is confidence filtering: run a character-level or word-level quality check on the extracted text and route low-confidence documents to a human review queue before ingestion.

Can I automate batch OCR using the Deliteful API?

Deliteful is a web-based tool with no public API at this time. Batch processing via the UI supports up to 50 files per run, which covers most medium-scale preprocessing needs.

Generate Plain Text Files from Scanned PDFs for Data Pipelines

Data pipelines that consume document content break down when source files are image-based scanned PDFs. Deliteful's PDF OCR → Text tool produces clean .txt output from scanned PDFs, giving your ingestion pipelines the machine-readable text they need without custom preprocessing scripts.

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Data engineers building document ingestion workflows — for NLP models, search indexes, or analytics systems — frequently encounter scanned PDFs in upstream data sources: insurance forms, government filings, legacy enterprise records. Writing one-off OCR scripts for each source is brittle. Using Deliteful as a preprocessing step standardizes scanned PDFs into plain text before they enter your pipeline, decoupling OCR from your core ingestion logic.

Deliteful outputs one .txt file per PDF with text in reading order. There is no JSON envelope, no metadata wrapper — just raw extracted text, though page boundaries may include separator characters depending on document structure. Batch sizes of up to 50 files and 2 GB per run make it practical for medium-scale document sets. For very large corpora, sequential batching is the approach. OCR quality is deterministic given scan quality: 300 DPI+ typed documents produce near-perfect output; degraded sources require downstream quality filtering.

How it works

1
Create a free account
Sign up with Google OAuth in 3 clicks — no card required.
2
Upload scanned PDFs
Batch upload up to 50 scanned PDFs per run, up to 300 MB each.
3
Download plain text output
Receive one .txt file per PDF — raw extracted text, no wrappers or metadata.
4
Feed into your pipeline
Pass .txt files to your ingestion layer, NLP model, or search indexer.

Frequently asked questions

What encoding is the output text in?: Output .txt files use UTF-8 encoding, which is compatible with standard text processing tools, Python, and most data pipeline frameworks.
Does the tool include any metadata or just raw text?: Output is plain text only — no JSON envelope, no metadata wrapper. Page boundaries may include separator characters depending on document structure. If you need document-level metadata, maintain that mapping in your own pipeline.
How do I handle OCR errors in a downstream pipeline?: The most reliable approach is confidence filtering: run a character-level or word-level quality check on the extracted text and route low-confidence documents to a human review queue before ingestion.
Can I automate batch OCR using the Deliteful API?: Deliteful is a web-based tool with no public API at this time. Batch processing via the UI supports up to 50 files per run, which covers most medium-scale preprocessing needs.

Create your free Deliteful account with Google and preprocess your scanned PDFs into plain text before they hit your data pipeline.