Best AI tools for< Monitor Ai >

AI Spend is an AI application designed to help users monitor their AI costs and prevent surprises. It allows users to keep track of their OpenAI usage and costs, providing fast insights, a beautiful dashboard, cost insights, notifications, usage analytics, and details on models and tokens. The application ensures simple pricing with no additional costs and securely stores API keys. Users can easily remove their data if needed, emphasizing privacy and security.

Vocera is an AI voice agent testing tool that allows users to test and monitor voice AI agents efficiently. It enables users to launch voice agents in minutes, ensuring a seamless conversational experience. With features like testing against AI-generated datasets, simulating scenarios, and monitoring AI performance, Vocera helps in evaluating and improving voice agent interactions. The tool provides real-time insights, detailed logs, and trend analysis for optimal performance, along with instant notifications for errors and failures. Vocera is designed to work for everyone, offering an intuitive dashboard and data-driven decision-making for continuous improvement.

Fiddler AI is an AI Observability platform that provides tools for monitoring, explaining, and improving the performance of AI models. It offers a range of capabilities, including explainable AI, NLP and CV model monitoring, LLMOps, and security features. Fiddler AI helps businesses to build and deploy high-performing AI solutions at scale.

Monitaur is an AI governance software that provides a comprehensive platform for organizations to manage the entire lifecycle of their AI systems. It brings together data, governance, risk, and compliance teams onto one platform to mitigate AI risk, leverage full potential, and turn intention into action. Monitaur's SaaS products offer user-friendly workflows that document the lifecycle of AI journey on one platform, providing a single source of truth for AI that stays honest.

The OECD Artificial Intelligence Policy Observatory, also known as OECD.AI, is a platform that focuses on AI policy issues, risks, and accountability. It provides resources, tools, and metrics to build and deploy trustworthy AI systems. The platform aims to promote innovative and trustworthy AI through collaboration with countries, stakeholders, experts, and partners. Users can access information on AI incidents, AI principles, policy areas, publications, and videos related to AI. OECD.AI emphasizes the importance of data privacy, generative AI management, AI computing capacities, and AI's potential futures.

Enterprise AI provides comprehensive information, news, and tips on artificial intelligence (AI) for businesses. It covers various aspects of AI, including AI business strategies, AI infrastructure, AI technologies, AI platforms, careers in AI, and enterprise applications of AI. The website offers insights into the latest AI trends, best practices, and industry news. It also provides resources such as e-books, webinars, and podcasts to help businesses understand and implement AI solutions.

Compassionate AI is a cutting-edge AI-powered platform that empowers individuals and organizations to create and deploy AI solutions that are ethical, responsible, and aligned with human values. With Compassionate AI, users can access a comprehensive suite of tools and resources to design, develop, and implement AI systems that prioritize fairness, transparency, and accountability.

K2 AI is an AI consulting company that offers a range of services from ideation to impact, focusing on AI strategy, implementation, operation, and research. They support and invest in emerging start-ups and push knowledge boundaries in AI. The company helps executives assess organizational strengths, prioritize AI use cases, develop sustainable AI strategies, and continuously monitor and improve AI solutions. K2 AI also provides executive briefings, model development, and deployment services to catalyze AI initiatives. The company aims to deliver business value through rapid, user-centric, and data-driven AI development.

Lumenova AI is an AI platform that focuses on making AI ethical, transparent, and compliant. It provides solutions for AI governance, assessment, risk management, and compliance. The platform offers comprehensive evaluation and assessment of AI models, proactive risk management solutions, and simplified compliance management. Lumenova AI aims to help enterprises navigate the future confidently by ensuring responsible AI practices and compliance with regulations.

Steamship is an AI application that specializes in providing ready-to-hire AI Employees. Their first offering is an Influencer Marketing Manager, dedicated to enhancing and expanding marketing campaigns. The platform aims to streamline the hiring process for AI professionals, making it easier for businesses to access top talent in the field.

AIxBlock is an AI tool that empowers users to unleash their AI initiatives on the Blockchain. The platform offers a comprehensive suite of features for building, deploying, and monitoring AI models, including AI data engine, multimodal-powered data crawler, auto annotation, consensus-driven labeling, MLOps platform, decentralized marketplaces, and more. By harnessing the power of blockchain technology, AIxBlock provides cost-efficient solutions for AI builders, compute suppliers, and freelancers to collaborate and benefit from decentralized supercomputing, P2P transactions, and consensus mechanisms.

Invicta AI is a provider of artificial intelligence solutions for the enterprise. The company's flagship product is a platform that enables businesses to build and deploy AI models without the need for specialized expertise. Invicta AI's platform provides a range of tools and services to help businesses with every step of the AI development process, from data preparation and model training to deployment and monitoring.

Arthur is an industry-leading MLOps platform that simplifies deployment, monitoring, and management of traditional and generative AI models. It ensures scalability, security, compliance, and efficient enterprise use. Arthur's turnkey solutions enable companies to integrate the latest generative AI technologies into their operations, making informed, data-driven decisions. The platform offers open-source evaluation products, model-agnostic monitoring, deployment with leading data science tools, and model risk management capabilities. It emphasizes collaboration, security, and compliance with industry standards.

Maxim is an end-to-end AI evaluation and observability platform that empowers modern AI teams to ship products with quality, reliability, and speed. It offers a comprehensive suite of tools for experimentation, evaluation, observability, and data management. Maxim aims to bring the best practices of traditional software development into non-deterministic AI workflows, enabling rapid iteration and deployment of AI models. The platform caters to the needs of AI developers, data scientists, and machine learning engineers by providing a unified framework for evaluation, visual flows for workflow testing, and observability features for monitoring and optimizing AI systems in real-time.

Hamming is an AI tool designed to help automate voice agent testing and optimization. It offers features such as prompt optimization, automated voice testing, monitoring, and more. The platform allows users to test AI voice agents against simulated users, create optimized prompts, actively monitor AI app usage, and simulate customer calls to identify system gaps. Hamming is trusted by AI-forward enterprises and is built for inbound and outbound agents, including AI appointment scheduling, AI drive-through, AI customer support, AI phone follow-ups, AI personal assistant, and AI coaching and tutoring.

deepset is an AI platform that offers enterprise-level products and solutions for AI teams. It provides deepset Cloud, a platform built with Haystack, enabling fast and accurate prototyping, building, and launching of advanced AI applications. The platform streamlines the AI application development lifecycle, offering processes, tools, and expertise to move from prototype to production efficiently. With deepset Cloud, users can optimize solution accuracy, performance, and cost, and deploy AI applications at any scale with one click. The platform also allows users to explore new models and configurations without limits, extending their team with access to world-class AI engineers for guidance and support.

Kindo is an AI-powered platform designed for DevSecOps teams to automate tasks, write doctrine, and orchestrate infrastructure responses. It offers AI-powered Runbook automations to streamline workflows, automate tedious tasks, and enhance security controls. Kindo enables users to offload time-consuming tasks to AI Agents, prioritize critical tasks, and monitor AI-related activities for compliance and informed decision-making. The platform provides a comprehensive vantage point for modern infrastructure defense and instrumentation, allowing users to create repeatable processes, automate vulnerability assessment and remediation, and secure multi-cloud IAM configurations.

Lunary is an AI developer platform designed to bring AI applications to production. It offers a comprehensive set of tools to manage, improve, and protect LLM apps. With features like Logs, Metrics, Prompts, Evaluations, and Threads, Lunary empowers users to monitor and optimize their AI agents effectively. The platform supports tasks such as tracing errors, labeling data for fine-tuning, optimizing costs, running benchmarks, and testing open-source models. Lunary also facilitates collaboration with non-technical teammates through features like A/B testing, versioning, and clean source-code management.

Future AGI is a revolutionary AI data management platform that aims to achieve 99% accuracy in AI applications across software and hardware. It provides a comprehensive evaluation and optimization platform for enterprises to enhance the performance of their AI models. Future AGI offers features such as creating trustworthy, accurate, and responsible AI, 10x faster processing, generating and managing diverse synthetic datasets, testing and analyzing agentic workflow configurations, assessing agent performance, enhancing LLM application performance, monitoring and protecting applications in production, and evaluating AI across different modalities.

Fordi is an AI management tool that helps businesses avoid risks in real-time. It provides a comprehensive view of all AI systems, allowing businesses to identify and mitigate risks before they cause damage. Fordi also provides continuous monitoring and alerting, so businesses can be sure that their AI systems are always operating safely.

Air Quality Info is a PHP-based page that displays current PM10 and PM2.5 measurements from Sensor.Community-compatible devices. It features a clean interface, stores records in MySQL, renders graphs with ChartJS, supports multiple devices, offers locale support, and functions as a Progressive Web App. The project setup involves creating directory structures, setting permissions, and starting Docker containers. The admin dashboard is accessible at http://aqi.eco.localhost:8080/, while the Air Quality Info pages use a specific naming schema. The project is supported by Nettigo Air Monitor, Sensor.Community, and a forum thread in Polish.

Responsible AI Toolbox is a suite of tools providing model and data exploration and assessment interfaces and libraries for understanding AI systems. It empowers developers and stakeholders to develop and monitor AI responsibly, enabling better data-driven actions. The toolbox includes visualization widgets for model assessment, error analysis, interpretability, fairness assessment, and mitigations library. It also offers a JupyterLab extension for managing machine learning experiments and a library for measuring gender bias in NLP datasets.

Pezzo is a fully cloud-native and open-source LLMOps platform that allows users to observe and monitor AI operations, troubleshoot issues, save costs and latency, collaborate, manage prompts, and deliver AI changes instantly. It supports various clients for prompt management, observability, and caching. Users can run the full Pezzo stack locally using Docker Compose, with prerequisites including Node.js 18+, Docker, and a GraphQL Language Feature Support VSCode Extension. Contributions are welcome, and the source code is available under the Apache 2.0 License.

The Radicalbit AI Monitoring Platform provides a comprehensive solution for monitoring Machine Learning and Large Language models in production. It helps proactively identify and address potential performance issues by analyzing data quality, model quality, and model drift. The repository contains files and projects for running the platform, including UI, API, SDK, and Spark components. Installation using Docker compose is provided, allowing deployment with a K3s cluster and interaction with a k9s container. The platform documentation includes a step-by-step guide for installation and creating dashboards. Community engagement is encouraged through a Discord server. The roadmap includes adding functionalities for batch and real-time workloads, covering various model types and tasks.

AI Central is a powerful tool designed to take control of your AI services with minimal overhead. It is built on Asp.Net Core and dotnet 8, offering fast web-server performance. The tool enables advanced Azure APIm scenarios, PII stripping logging to Cosmos DB, token metrics through Open Telemetry, and intelligent routing features. AI Central supports various endpoint selection strategies, proxying asynchronous requests, custom OAuth2 authorization, circuit breakers, rate limiting, and extensibility through plugins. It provides an extensibility model for easy plugin development and offers enriched telemetry and logging capabilities for monitoring and insights.

Parea AI provides a SDK to evaluate & monitor AI applications. It allows users to test, evaluate, and monitor their AI models by defining and running experiments. The SDK also enables logging and observability for AI applications, as well as deploying prompts to facilitate collaboration between engineers and subject-matter experts. Users can automatically log calls to OpenAI and Anthropic, create hierarchical traces of their applications, and deploy prompts for integration into their applications.

This repository contains a custom component for Home Assistant that integrates various Xiaomi Mi Air Purifier and Xiaomi Mi Air Humidifier models. It provides detailed support for different devices, including power control, preset modes, child lock, LED control, favorite level adjustment, and various attributes monitoring. The custom component offers a more extensive range of supported devices compared to the official Home Assistant component, with additional features and device compatibility. Users can easily set up and configure their Xiaomi air purifiers and humidifiers within Home Assistant for enhanced control and monitoring.

Firebase Genkit (beta) is a framework with powerful tooling to help app developers build, test, deploy, and monitor AI-powered features with confidence. Genkit is cloud optimized and code-centric, integrating with many services that have free tiers to get started. It provides unified API for generation, context-aware AI features, evaluation of AI workflow, extensibility with plugins, easy deployment to Firebase or Google Cloud, observability and monitoring with OpenTelemetry, and a developer UI for prototyping and testing AI features locally. Genkit works seamlessly with Firebase or Google Cloud projects through official plugins and templates.

The AI Enablement Stack is a curated collection of venture-backed companies, tools, and technologies that enable developers to build, deploy, and manage AI applications. It provides a structured view of the AI development ecosystem across five key layers: Agent Consumer Layer, Observability and Governance Layer, Engineering Layer, Intelligence Layer, and Infrastructure Layer. Each layer focuses on specific aspects of AI development, from end-user interaction to model training and deployment. The stack aims to help developers find the right tools for building AI applications faster and more efficiently, assist engineering leaders in making informed decisions about AI infrastructure and tooling, and help organizations understand the AI development landscape to plan technology adoption.

This open-source course teaches how to build an advanced RAG and LLM system using LLMOps and ML systems best practices. It helps you create an AI assistant that leverages your personal knowledge base to answer questions, summarize documents, and provide insights. The course covers topics such as LLM system architecture, pipeline orchestration, large-scale web crawling, model fine-tuning, and advanced RAG features. It is suitable for ML/AI engineers and data/software engineers & data scientists looking to level up to production AI systems. The course is free, with minimal costs for tools like OpenAI's API and Hugging Face's Dedicated Endpoints. Participants will build two separate Python applications for offline ML pipelines and online inference pipeline.

Coding-Aider is a plugin for IntelliJ IDEA that seamlessly integrates Aider's AI-powered coding assistance into the IDE. It boosts productivity by offering rapid access for precision code generation and refactoring, with complete control over the context utilized by the LLM. The plugin provides various features such as AI-powered coding assistance, intuitive access through keyboard shortcuts, persistent file management, dual execution modes, Git integration, real-time progress tracking, multi-file support, web crawling, clipboard image support, and various specialized actions. It also supports structured mode and plans for managing complex features, working directory support, summarized output, and the ability to specify additional arguments for Aider commands. Coding-Aider addresses limitations in existing IntelliJ plugins by offering optimized token usage, a feature-rich terminal interface, a wide range of commands, and robust recovery mechanisms with seamless Git integration.

A curated list of Generative AI projects, tools, artworks, and models

AI Flow is an open-source, user-friendly UI application that empowers you to seamlessly connect multiple AI models together, specifically leveraging the capabilities of multiples AI APIs such as OpenAI, StabilityAI and Replicate. In a nutshell, AI Flow provides a visual platform for crafting and managing AI-driven workflows, thereby facilitating diverse and dynamic AI interactions.

AIStore on Kubernetes is a toolkit for deploying a lightweight, scalable object storage solution designed for AI applications in a Kubernetes environment. It includes documentation, Ansible playbooks, Kubernetes operator, Helm charts, and Terraform definitions for deployment on public cloud platforms. The system overview shows deployment across nodes with proxy and target pods utilizing Persistent Volumes. The AIStore Operator automates cluster management tasks. The repository focuses on production deployments but offers different deployment options. Thorough planning and configuration decisions are essential for successful multi-node deployment. The AIStore Operator simplifies tasks like starting, deploying, adjusting size, and updating AIStore resources within Kubernetes.

AiTreasureBox is a versatile AI tool that provides a collection of pre-trained models and algorithms for various machine learning tasks. It simplifies the process of implementing AI solutions by offering ready-to-use components that can be easily integrated into projects. With AiTreasureBox, users can quickly prototype and deploy AI applications without the need for extensive knowledge in machine learning or deep learning. The tool covers a wide range of tasks such as image classification, text generation, sentiment analysis, object detection, and more. It is designed to be user-friendly and accessible to both beginners and experienced developers, making AI development more efficient and accessible to a wider audience.

AITreasureBox is a comprehensive collection of AI tools and resources designed to simplify and accelerate the development of AI projects. It provides a wide range of pre-trained models, datasets, and utilities that can be easily integrated into various AI applications. With AITreasureBox, developers can quickly prototype, test, and deploy AI solutions without having to build everything from scratch. Whether you are working on computer vision, natural language processing, or reinforcement learning projects, AITreasureBox has something to offer for everyone. The repository is regularly updated with new tools and resources to keep up with the latest advancements in the field of artificial intelligence.

AgentOps is a toolkit for evaluating and developing robust and reliable AI agents. It provides benchmarks, observability, and replay analytics to help developers build better agents. AgentOps is open beta and can be signed up for here. Key features of AgentOps include: - Session replays in 3 lines of code: Initialize the AgentOps client and automatically get analytics on every LLM call. - Time travel debugging: (coming soon!) - Agent Arena: (coming soon!) - Callback handlers: AgentOps works seamlessly with applications built using Langchain and LlamaIndex.

NodeTool is a platform designed for AI enthusiasts, developers, and creators, providing a visual interface to access a variety of AI tools and models. It simplifies access to advanced AI technologies, offering resources for content creation, data analysis, automation, and more. With features like a visual editor, seamless integration with leading AI platforms, model manager, and API integration, NodeTool caters to both newcomers and experienced users in the AI field.

Instill Core is an open-source orchestrator comprising a collection of source-available projects designed to streamline every aspect of building versatile AI features with unstructured data. It includes Instill VDP (Versatile Data Pipeline) for unstructured data, AI, and pipeline orchestration, Instill Model for scalable MLOps and LLMOps for open-source or custom AI models, and Instill Artifact for unified unstructured data management. Instill Core can be used for tasks such as building, testing, and sharing pipelines, importing, serving, fine-tuning, and monitoring ML models, and transforming documents, images, audio, and video into a unified AI-ready format.

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Informative guide on asbestos hazards and removal

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ComplianceChecker simplifies and explains the terms and policies of platforms like Facebook, TikTok, and YouTube for compliance purposes.

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