Anthropic Batch API for Asynchronous Multi-Tenant AI Processing: Cutting Claude Costs by 50% Without Sacrificing Feature Responsiveness

Anthropic Batch API for Asynchronous Multi-Tenant AI Processing: Cutting Claude Costs by 50% Without Sacrificing Feature Responsiveness

At CitizenApp, we process thousands of document summaries, compliance classifications, and policy analyses daily. Our first instinct was synchronous: user uploads document → Claude responds in real-time → dashboard updates. It felt responsive. It also felt like burning cash.

Then we realized: 80% of those requests don't actually need synchronous responses. A user uploads a document for summarization? They're fine waiting 5–30 minutes. A tenant wants to bulk-classify 500 policies? That's explicitly an async job. The Batch API is built for this, and it's absurdly underutilized.

Here's how I wired it into CitizenApp—and why you should too.

The 50% cost reduction is the headline, but the real win is architectural. Batching forces you to separate concerns: