Baseten
AI Infrastructure & MLOps
Serve and scale open-source and custom AI models on the fastest, most reliable inference platform.
Baseten is an AI inference platform designed to serve and scale open-source and custom machine learning models. The platform provides infrastructure for deploying models with a focus on performance and reliability. The platform is built for machine learning engineers, data scientists, and AI teams who need to operationalize models beyond development environments. Baseten handles the underlying infrastructure requirements, allowing users to focus on model development and deployment rather than managing servers and scaling systems. Key capabilities include support for both open-source models and proprietary custom models, with tooling to manage model serving at scale. The platform abstracts away infrastructure complexity, offering a streamlined path from model development to production deployment. Baseten operates under an open-source model, making its core technology accessible to developers. The platform integrates with existing ML workflows and supports common model frameworks and formats. The service is particularly relevant for teams building AI applications that require reliable, performant inference endpoints. Rather than managing dedicated GPU infrastructure or cloud resources directly, users can leverage Baseten's pre-configured environment optimized for model inference workloads. Baseten positions itself within the broader AI infrastructure and MLOps category, addressing the gap between model development and production serving for organizations of varying sizes.
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Run and deploy AI models with a cloud API
Hey HN! I'm Fabio and I built UltraContext, a simple context API for AI agents with automatic versioning. After two years building AI agents in production, I experienced firsthand how frustrating it is to manage context at scale. Storing messages, iterating system prompts, debugging behavior an
The AI community platform for models and datasets
Hi HN! I'm Erik. We built Butter, an LLM proxy that makes agent systems deterministic by caching and replaying responses, so automations behave consistently across runs. - It’s a chat completions compatible endpoint, making it easy to drop into existing agents with a custom base_url - The cache
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