TrueFoundry supports deploying, serving, monitoring, or operating AI and machine-learning systems.
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Valohai supports deploying, serving, monitoring, or operating AI and machine-learning systems.
Wallaroo.AI supports deploying, serving, monitoring, or operating AI and machine-learning systems.
Open-source project that supports deploying, serving, monitoring, or operating AI and machine-learning systems.
Weco Observe supports deploying, serving, monitoring, or operating AI and machine-learning systems.
The open source standard for data logging. Enables ML monitoring and observability.
Eurybia monitors data and model drift over time and securizes model deployment with data validation.
A model gateway and unified interface for multiple model providers.
Package, configure, and iterate on a model with Truss at whatever level of control your model needs.
Run sandboxes, task queues, and custom model inference with ultrafast boot times, instant autoscaling, and a developer experience that just works.
Open-source platform for high-performance ML model serving.
Go binding for MXNet c predict api to do inference with a pre-trained model.
Build multimodal AI services via cloud native technologies · Model Serving · Generative AI · Neural Search · Cloud Native.
Open source MLOps project that eases model handoffs between data scientist and DevOps.
Machine learning model serving framework with dynamic batching and pipelined stages, provides an easy-to-use Python interface.
Python-free Rust inference server with OpenAI API compatibility and hot model swapping.
An MLOps/LLMOps platform for model building, evaluation, and fine-tuning.
Helps teams build, deploy, observe or operate machine-learning systems.
MLOps in a notebook - uncover insights, surface problems, monitor, and fine tune your models.
Inference hosting for AI teams who ship fast and scale faster.
Bayesian Inference Tools in Python.
An open-source LLM gateway with routing, load balancing, guardrails, and observability for 1000+ models. opensource.
Deploy a ML inference service on a budget in less than 10 lines of code.
An easy-to-use feature store. Optimized for time-series data.