Baseten is an AI infrastructure company co-founded by Tuhin Srivastava that provides a platform for deploying, serving, and scaling machine learning models in production. The platform targets engineering teams that want to run open-source, custom, or fine-tuned models without building and operating low-level inference infrastructure themselves.
Baseten centers on production model serving, offering optimized inference, autoscaling, and tooling such as its open-source Truss packaging framework to standardize how models are deployed. It supports a range of model types including large language models, image and audio models, and custom workloads, with an emphasis on performance and reliability for latency-sensitive applications.
The company also provides options like dedicated deployments and model APIs, allowing teams to balance control, cost, and convenience. Baseten has raised significant venture funding and positions itself for AI-native companies that need to ship inference-heavy products quickly while keeping infrastructure manageable.
Baseten competes with other inference and ML deployment platforms as well as do-it-yourself approaches on cloud GPUs. Its differentiation rests on performance optimization, developer experience, and scaling automation. Prospective users should evaluate GPU availability, cost at their expected scale, cold-start behavior, and how well supported their specific models and frameworks are.
Baseten is most compelling for AI product teams that need reliable, performant, and autoscaling model serving without dedicating significant engineering effort to inference infrastructure.