Gemini Enterprise Agent Platform (formerly Vertex AI) is a comprehensive platform for developers to build, scale, govern and optimize agents.
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A flexible and easy to use tool for serving PyTorch models.
Inference for text-embedding models.
TensorZero builds open-source tools for production-grade LLM applications: LLM gateway, observability, optimization, evaluations, and experimentation.
Examples showing how to use the OpenAI vision API to run inference on images, video files and webcam streams.
OpenAI-compatible LLM inference server for Apple Silicon using MLX. 2-4x faster than Ollama with tool calling and prompt caching.
Quix is the agentic AI platform for hardware engineering — turn test-rig and sensor data into real-time insight.
Nimblebox supports deploying, serving, monitoring, or operating AI and machine-learning systems.
A framework providing the right abstractions to ease research, development, and deployment of your ML pipelines.
An open-source platform for tracking ML experiments, evaluating models and prompts, deploying models, and adding LLM observability. opensource.
Full-stack AI platform focused on multimodal agents and consumer-scale deployment.
Helps teams build, deploy, observe or operate machine-learning systems.
Observability and prompt management platform for LLM-based apps. Take your LLMs to the next level.
A lightweight, portable pure C99 onnx inference engine for embedded devices with hardware acceleration support.
Go binding for MXNet c predict api to do inference with a pre-trained model.
Ultravox is a real-time voice AI infrastructure layer that powers fast, natural, and scalable voice agents.
Ultravox is a real-time voice AI infrastructure layer that powers fast, natural, and scalable voice agents.
A Virtual Feature Store. Turn your existing data infrastructure into a feature store.
10x faster, cheaper, and better vector database.
Open-source project that supports deploying, serving, monitoring, or operating AI and machine-learning systems.
Run sandboxes, task queues, and custom model inference with ultrafast boot times, instant autoscaling, and a developer experience that just works.
MLOps in a notebook - uncover insights, surface problems, monitor, and fine tune your models.
Helps teams build, deploy, observe or operate machine-learning systems.
Blazing fast short-text-topic-modelling for Python.