Unifying image inputs across three vision providers behind Bifrost (opens in new tab)

TL;DR: We run an automated visual QA step that scores generated product shots with vision LLMs from OpenAI, Anthropic, and Google. Each provider wanted the image payload shaped differently, and one rate-limit spike could stall the whole batch. Putting Bifrost in front gave us one OpenAI-compatible image schema and automatic failover, with about 4ms of added latency per call. At Photoroom I work on the diffusion side of product photography. The model that generates a clean studio shot is only ...