Feature
Batch processing
Queue up to 10 documents at once. Each runs in isolation, with status tracked in your dashboard.
One-at-a-time humanization is fine for a single essay. Real writing work is rarely one document. A researcher may be moving through eight literature-review sections. A marketer may have a sprint of blog drafts. An agency may have a stack of client work that all needs to land in the same week.
Batch mode is built for that reality. Drop up to ten documents into the dashboard in a single action, walk away, and come back to a list of finished files. Each document is processed as an independent job so a problem in one doesn't take down the rest of the batch.
How it works
What's happening under the hood
Each upload becomes a job in a Redis-backed ARQ queue. ARQ is a lightweight Python job runner that gives us per-job retries, structured logging, and a clean separation between the web process and the worker process. When a document fails, only that document is retried; the rest of the batch keeps moving.
The worker processes jobs concurrently, with each job running its own humanization pipeline — parse, extract, build the prompt, call Claude, reassemble the output. Jobs run in isolation: a bad PDF that throws an extraction error doesn't kill the nine clean DOCXs in the same batch. Errors are captured per-job and surfaced in the dashboard with the actual reason for failure.
The dashboard polls the job-status endpoint every 2 secondsso the UI shows live progress without you having to refresh. Each card moves through pending → processing → completed (or failed, with a reason). When a job completes you can download it immediately while the others are still running.
Pro accounts can have up to 10 documents in flight at once. Enterprise raises that ceiling along with the per-document word cap (10,000 words versus 5,000 on Pro). The monthly quota covers all documents whether they were submitted individually or as part of a batch — the batch is a workflow primitive, not a separate allowance.
Benefits
Why this matters
Throughput
Ten documents in flight at once instead of one. The wait time for a sprint of work collapses to the duration of the longest single job.
Fault isolation
One bad input doesn't take down the batch. Failed jobs report a reason; successful jobs are downloadable while the failures are still being retried.
Dashboard visibility per-job
Every job has its own status card with live progress, an error reason if it failed, and a download button as soon as it's done.
Related features
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