Best AI tools for< Monitor Ai Workloads >

Helicone is an open-source platform designed for developers, offering observability solutions for logging, monitoring, and debugging. It provides sub-millisecond latency impact, 100% log coverage, industry-leading query times, and is ready for production-level workloads. Trusted by thousands of companies and developers, Helicone leverages Cloudflare Workers for low latency and high reliability, offering features such as prompt management, uptime of 99.99%, scalability, and reliability. It allows risk-free experimentation, prompt security, and various tools for monitoring, analyzing, and managing requests.

Nomi.cloud is a modern AI-powered CloudOps and HPC assistant designed for next-gen businesses. It offers developers, marketplace, enterprise solutions, and pricing console. With features like single pane of glass view, instant deployment, continuous monitoring, AI-powered insights, and budgets & alerts built-in, Nomi.cloud aims to revolutionize cloud management. It provides a user-friendly interface to manage infrastructure efficiently, optimize costs, and deploy resources across multiple regions with ease. Nomi.cloud is built for scale, trusted by enterprises, and offers a range of GPUs and cloud providers to suit various needs.

Modal is a high-performance cloud platform designed for developers, AI data, and ML teams. It offers a serverless environment for running generative AI models, large-scale batch jobs, job queues, and more. With Modal, users can bring their own code and leverage the platform's optimized container file system for fast cold boots and seamless autoscaling. The platform is engineered for large-scale workloads, allowing users to scale to hundreds of GPUs, pay only for what they use, and deploy functions to the cloud in seconds without the need for YAML or Dockerfiles. Modal also provides features for job scheduling, web endpoints, observability, and security compliance.

Palo Alto Networks is a cybersecurity company offering advanced security solutions powered by Precision AI to protect modern enterprises from cyber threats. The company provides network security, cloud security, and AI-driven security operations to defend against AI-generated threats in real time. Palo Alto Networks aims to simplify security and achieve better security outcomes through platformization, intelligence-driven expertise, and proactive monitoring of sophisticated threats.

Deflekt.ai is an AI-powered application designed to automate replies on all support channels. It helps businesses deflect customer and coworker support tickets by answering questions automatically. The tool can be integrated with various channels like web chat, email, Slack, and Teams, making it a versatile solution for support teams. Deflekt.ai allows users to customize content, localize responses, and provide human support when needed. With features like document hosting, channel activation, and conversation monitoring, Deflekt.ai streamlines support processes and reduces workload.

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.

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.

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.

LLM App Stack, also known as Emerging Architectures for LLM Applications, is a comprehensive list of available tools, projects, and vendors at each layer of the LLM app stack. It covers various categories such as Data Pipelines, Embedding Models, Vector Databases, Playgrounds, Orchestrators, APIs/Plugins, LLM Caches, Logging/Monitoring/Eval, Validators, LLM APIs (proprietary and open source), App Hosting Platforms, Cloud Providers, and Opinionated Clouds. The repository aims to provide a detailed overview of tools and projects for building, deploying, and maintaining enterprise data solutions, AI models, and applications.

Runbooks is a repository that is no longer active. The project has been deprecated in favor of KubeAI, a platform designed to simplify the operationalization of AI on Kubernetes. For more information, please refer to the new repository at https://github.com/substratusai/kubeai.

Awesome MLOps is a curated list of tools related to Machine Learning Operations, covering areas such as AutoML, CI/CD for Machine Learning, Data Cataloging, Data Enrichment, Data Exploration, Data Management, Data Processing, Data Validation, Data Visualization, Drift Detection, Feature Engineering, Feature Store, Hyperparameter Tuning, Knowledge Sharing, Machine Learning Platforms, Model Fairness and Privacy, Model Interpretability, Model Lifecycle, Model Serving, Model Testing & Validation, Optimization Tools, Simplification Tools, Visual Analysis and Debugging, and Workflow Tools. The repository provides a comprehensive collection of tools and resources for individuals and teams working in the field of MLOps.

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.

CentralMind Gateway is an AI-first data gateway that securely connects any data source and automatically generates secure, LLM-optimized APIs. It filters out sensitive data, adds traceability, and optimizes for AI workloads. Suitable for companies deploying AI agents for customer support and analytics.

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

Felafax is a framework designed to tune LLaMa3.1 on Google Cloud TPUs for cost efficiency and seamless scaling. It provides a Jupyter notebook for continued-training and fine-tuning open source LLMs using XLA runtime. The goal of Felafax is to simplify running AI workloads on non-NVIDIA hardware such as TPUs, AWS Trainium, AMD GPU, and Intel GPU. It supports various models like LLaMa-3.1 JAX Implementation, LLaMa-3/3.1 PyTorch XLA, and Gemma2 Models optimized for Cloud TPUs with full-precision training support.

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.

RAGStack is an out-of-the-box solution simplifying Retrieval Augmented Generation (RAG) in GenAI apps. RAGStack includes the best open-source for implementing RAG, giving developers a comprehensive Gen AI Stack leveraging LangChain, CassIO, and more. RAGStack leverages the LangChain ecosystem and is fully compatible with LangSmith for monitoring your AI deployments.

Awesome European Tech is an up-to-date list of recommended European projects and companies curated by the community to support and strengthen the European tech ecosystem. It focuses on privacy and sustainability, showcasing companies that adhere to GDPR compliance and sustainability standards. The project aims to highlight and support European startups and projects excelling in privacy, sustainability, and innovation to contribute to a more diverse, resilient, and interconnected global tech landscape.

The 'bookmark-summary' repository reads bookmarks from 'bookmark-collection', extracts text content using Jina Reader, and then summarizes the text using LLM. The detailed implementation can be found in 'process_changes.py'. It needs to be used together with the Github Action in 'bookmark-collection'.

Call Center AI is an AI-powered call center solution leveraging Azure and OpenAI GPT. It allows for AI agent-initiated phone calls or direct calls to the bot from a configured phone number. The bot is customizable for various industries like insurance, IT support, and customer service, with features such as accessing claim information, conversation history, language change, SMS sending, and more. The project is a proof of concept showcasing the integration of Azure Communication Services, Azure Cognitive Services, and Azure OpenAI for an automated call center solution.

CRB (Composable Runtime Blocks) is a unique framework that implements hybrid workloads by seamlessly combining synchronous and asynchronous activities, state machines, routines, the actor model, and supervisors. It is ideal for building massive applications and serves as a low-level framework for creating custom frameworks, such as AI-agents. The core idea is to ensure high compatibility among all blocks, enabling significant code reuse. The framework allows for the implementation of algorithms with complex branching, making it suitable for building large-scale applications or implementing complex workflows, such as AI pipelines. It provides flexibility in defining structures, implementing traits, and managing execution flow, allowing users to create robust and nonlinear algorithms easily.

Ray is a unified framework for scaling AI and Python applications. It consists of a core distributed runtime and a set of AI libraries for simplifying ML compute, including Data, Train, Tune, RLlib, and Serve. Ray runs on any machine, cluster, cloud provider, and Kubernetes, and features a growing ecosystem of community integrations. With Ray, you can seamlessly scale the same code from a laptop to a cluster, making it easy to meet the compute-intensive demands of modern ML workloads.

The AWS Generative AI Constructs Library is an open-source extension of the AWS Cloud Development Kit (AWS CDK) that provides multi-service, well-architected patterns for quickly defining solutions in code to create predictable and repeatable infrastructure, called constructs. The goal of AWS Generative AI CDK Constructs is to help developers build generative AI solutions using pattern-based definitions for their architecture. The patterns defined in AWS Generative AI CDK Constructs are high level, multi-service abstractions of AWS CDK constructs that have default configurations based on well-architected best practices. The library is organized into logical modules using object-oriented techniques to create each architectural pattern model.

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