How Botika runs full-stack generative AI on Modal

Botika, a generative-AI company that produces and personalizes fashion imagery for global brands, uses Modal to operate its data processing, model training, research, and production inference systems. The company maintains proprietary foundation models with tens of billions of parameters, processes a 100-terabyte image dataset, and serves roughly 15 production models across several GPU types. After previously managing Kubernetes and GCP Batch infrastructure, Botika adopted Modal in 2023 to reduce the operational work associated with autoscaling, GPU management, cold starts, orchestration, and environment configuration. Its pipeline runs numerous specialized AI models across thousands of concurrent containers, while researchers reportedly increased experiment throughput from one or two runs per day to dozens by launching short jobs and scaling promising results. Botika also uses Modal for multi-node training, reinforcement learning infrastructure, and inference that can automatically handle sudden traffic increases, with CEO Eran Dagan saying the platform has allowed the company to operate with fewer infrastructure-focused staff and avoid relying extensively on traditional cloud services.

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