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AI Visibility Monitor is an open-source CLI that runs buyer queries against ChatGPT, Claude, and Perplexity and reports which queries are winnable, source surfaces, and visibility trends. It runs on the user's own API keys, with no signup and no SaaS upsell.
Open-source project that supports deploying, serving, monitoring, or operating AI and machine-learning systems.
Banana provides GPU inference hosting for AI teams. The platform scales GPUs up and down automatically and includes monitoring, business analytics, a CLI, SDKs, and an open automation API. Backends can be written with Potassium, an open-source HTTP framework. Paid Team and Enterprise tiers are offered.
Open-source project that 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.
Dominodatalab supports deploying, serving, monitoring, or operating AI and machine-learning systems.
Helicone AI supports deploying, serving, monitoring, or operating AI and machine-learning systems.
MLflow is an open source AI engineering platform for agents, LLMs, and ML models. It provides tools for debugging, evaluating, monitoring, and optimizing AI applications, including tracing, evaluation metrics, prompt management, an AI gateway, and an agent server. The project is released under the Apache 2.0 license.
MLOps Now 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.
Nimblebox 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.
OpenLIT is an open-source agent harness engineering platform built on OpenTelemetry. It provides tracing, evaluations, guardrails, prompt and context management, and cost and GPU monitoring for the harness around AI agents and coding agents. It is free to self-host under Apache 2.0 and is described as working with many models, frameworks and harnesses.
Open-source project that supports deploying, serving, monitoring, or operating AI and machine-learning systems.
The open source solution for monitoring your AI models in production.
Tecton 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.
A guide to MLOps is an open-source tutorial from the Swiss AI Center team that walks engineers and small teams from notebook experiments to production. It covers local training and model evaluation, moving the model to the cloud, serving and deploying, monitoring and maintaining, and labeling data and retraining, using tools such as DVC, Git, GitHub Actions, CML, Docker, BentoML, Fluent Bit, Evidently AI, and Label Studio.
Adaptive Reliability Layer is a Python project that sits between an inference pipeline and a monitoring layer. It detects distribution shift, decides whether adaptation is warranted, and learns from delayed revealed labels. It does not replace the model.
Agenta is an open-source workspace for AI agents. Agents are built through chat, improved with feedback, and shared with a team, either self-hosted or in the cloud. Integrations and messaging in Slack or Telegram are described on the site.
agenttrace is a local-first terminal TUI and report generator for AI coding-agent session history. It reads logs from several coding agents and produces reports on cost, tokens, time, and slow-run diagnosis. Prompts, code, and logs stay on the local machine.
This is a Scaler blog category page collecting articles on artificial intelligence and machine learning. Posts listed include MLOps projects, becoming an AI research scientist, model drift detection and monitoring, and retrieval-augmented generation evaluation metrics. The page also links to categories such as software development and data science, and offers career counselling.
A Hugging Face Space that classifies whether given text was written by a human or a language model. Users enter text in an input box and receive a classification result. The Space is shown as sleeping due to inactivity.
