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Inputs

Batch Input Processing

Accept many files or prompts at once, queue them with per-item status, and let people pause, cancel, or export results in bulk. Built for workflows beyond one-at-a-time chat.

Interactive demo

Batch Input Processing

Overview

How might we design batch input processing so people can trust and act on AI output?

When to use

  • Ideal for data processing tools, bulk operations, and workflows where processing multiple inputs simultaneously improves efficiency and productivity.

When to skip

  • Interactive tasks needing immediate single-turn feedback.
  • Batch size caps ignored on shared tenant quotas.
  • Items that must be strictly ordered with cross-dependencies.

Rules

  • Batch with no per-item error detail.

  • All-or-nothing export when half failed.

  • No estimate of total time or cost upfront.

  • Restart entire batch after one validation error.

Evidence

ProductImplementation
Image processing toolsMulti-upload queues with per-file progress bars.
Data analysis platformsCSV row batches through AI enrichment pipelines.
Document processorsFolder ingest with OCR and summary per doc.
Batch APIsJob IDs, webhooks, and downloadable result bundles.

FAQ

What UI does batch processing need?

Upload list, queue order, status per item, aggregate progress, and download or retry failed rows.

Batch input vs batch processing queue?

Input processing is user-facing multi-submit. Processing queue is backend job orchestration with same UX patterns.

Parallel or serial?

Show policy: parallel for independent items; serial when rate limits require it.

Partial failure handling?

Export successes and a failure report with row IDs and error reasons.