Start with the time the business needs the result
Some AI work can wait: drafting descriptions for internal review, categorising an archive or running an evaluation set. Our recommendation is to separate these tasks from requests where someone needs an immediate answer. Agree when the results must be usable, who will review them and what happens if processing takes longer than expected. A task belongs in the batch workflow only when that waiting time fits the business process.
Check the service before designing the workflow
Anthropic’s Message Batches API processes requests asynchronously and independently. Amazon Bedrock also supports asynchronous batch inference, with input and output files stored in Amazon S3. These are different services with their own supported models, formats and limits. Check the chosen service’s current documentation, regional availability, data handling and account permissions before sending any business information. Begin with synthetic examples that represent the intended request shape. Anthropic: Batch processing. AWS: Batch inference in Amazon Bedrock.
Keep a record for every input
Our suggested design assigns each input a stable identifier and records the model, prompt version and source version used. Anthropic documents a custom identifier for matching batch results to requests and warns that result order is not guaranteed. Reconcile results by identifier rather than position in a file. Keep a record of which items were submitted and which outputs passed validation before making them available to the next step. Anthropic: Batch processing.
Treat completion and usefulness as separate checks
Anthropic distinguishes successful, errored, cancelled and expired requests within a batch. A finished batch therefore needs a review of its individual outcomes. Our recommendation is to validate the expected output structure and sample the content against the same quality criteria used for interactive processing. Separate requests needing a corrected input from requests eligible for another attempt. Keep approved results available while unresolved items follow a defined recovery or human review path. Anthropic: Batch processing.
Measure the whole workflow before expanding
Compare total elapsed time, usable outputs and complete operating cost on a representative trial. Include storage, validation, review and any repeated processing in that comparison. Check current pricing for the selected model and service when estimating a budget; do not assume one provider’s batch terms apply elsewhere. Expand only after the trial shows that the workflow meets its deadline and quality requirements, with someone responsible for collecting results and resolving exceptions.