Best AI tools for< Manage Model Lifecycles >

DVC Studio is a collaboration tool for machine learning teams. It provides seamless data and model management, experiment tracking, visualization, and automation. DVC Studio is built for ML researchers, practitioners, and managers. It enables model organization and discovery across all ML projects and manages model lifecycle with Git, unifying ML projects with the best DevOps practices. DVC Studio also provides ML experiment tracking, visualization, collaboration, and automation using Git. It applies software engineering and DevOps best-practices to automate ML bookkeeping and model training, enabling easy collaboration and faster iterations.

Evisort is an AI-powered contract management software that simplifies contract management at every stage. It offers a complete, AI-native platform for end-to-end contract lifecycle management, including the first large language model built specifically for contracts. Evisort's AI capabilities enable users to ask questions about their contracts in simple, natural language and get clear, reasoned answers. It can also track terms of interest across all contracts and related documents, and generate data points that matter for sales, procurement, risk, and finance teams. Additionally, Evisort's AI-powered workflows automate tasks such as redlining, clause generation, and contract approvals, saving time and reducing risk.

MLflow is an open source platform for managing the end-to-end machine learning (ML) lifecycle, including tracking experiments, packaging models, deploying models, and managing model registries. It provides a unified platform for both traditional ML and generative AI applications.

Baseten is a machine learning infrastructure that provides a unified platform for data scientists and engineers to build, train, and deploy machine learning models. It offers a range of features to simplify the ML lifecycle, including data preparation, model training, and deployment. Baseten also provides a marketplace of pre-built models and components that can be used to accelerate the development of ML applications.

Evisort is an AI-powered contract management software that simplifies contract management at every stage. It offers a complete, AI-native platform for end-to-end contract lifecycle management, including the first large language model built specifically for contracts. With Evisort, you can connect and integrate your contracts from various systems, analyze them to surface risks and opportunities, and automate workflows to streamline the contract management process. Evisort is trusted by savvy legal professionals at global brands and has been recognized as a leader in contract lifecycle management by Gartner.

Vellum AI is an AI platform that supports using Microsoft Azure hosted OpenAI models. It offers tools for prompt engineering, semantic search, prompt chaining, evaluations, and monitoring. Vellum enables users to build AI systems with features like workflow automation, document analysis, fine-tuning, Q&A over documents, intent classification, summarization, vector search, chatbots, blog generation, sentiment analysis, and more. The platform is backed by top VCs and founders of well-known companies, providing a complete solution for building LLM-powered applications.

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HatchWorks is an AI development partner that specializes in building AI-native solutions and using AI to enhance software development processes. The company offers services such as Gen AI Product Development, Data & AI/ML Software Development, Product Strategy, and UX & UI Design. HatchWorks leverages cutting-edge technologies like Generative AI, Machine Learning, and AI-Powered Software Development to deliver custom software solutions efficiently. The company's proprietary Generative-Driven Development™ methodology enables faster software development, increased productivity, and cost-effectiveness. HatchWorks is trusted by leading brands for delivering exceptional AI-driven outcomes and impactful solutions.

One Data is an AI-powered data product builder that offers a comprehensive solution for building, managing, and sharing data products. It bridges the gap between IT and business by providing AI-powered workflows, lifecycle management, data quality assurance, and data governance features. The platform enables users to easily create, access, and share data products with automated processes and quality alerts. One Data is trusted by enterprises and aims to streamline data product management and accessibility through Data Mesh or Data Fabric approaches, enhancing efficiency in logistics and supply chains. The application is designed to accelerate business impact with reliable data products and support cost reduction initiatives with advanced analytics and collaboration for innovative business models.

Azure AI Platform by Microsoft offers a comprehensive suite of artificial intelligence services and tools for developers and businesses. It provides a unified platform for building, training, and deploying AI models, as well as integrating AI capabilities into applications. With a focus on generative AI, multimodal models, and large language models, Azure AI empowers users to create innovative AI-driven solutions across various industries. The platform also emphasizes content safety, scalability, and agility in managing AI projects, making it a valuable resource for organizations looking to leverage AI technologies.

Freeplay is a tool that helps product teams experiment, test, monitor, and optimize AI features for customers. It provides a single pane of glass for the entire team, lightweight developer SDKs for Python, Node, and Java, and deployment options to meet compliance needs. Freeplay also offers best practices for the entire AI development lifecycle.

Jumio is a leading digital identity verification platform that offers AI-driven services to verify the identities of new and existing users, assess risk, and help meet compliance mandates. With over 1 billion transactions processed, Jumio provides cutting-edge AI and ML models to detect fraud and maintain trust throughout the customer lifecycle. The platform offers solutions for identity verification, predictive fraud insights, dynamic user experiences, and risk scoring, trusted by global brands across various industries.

LiteLLM is a platform that simplifies model access, spend tracking, and fallbacks across 100+ LLMs. It provides a gateway to manage model access and offers features like logging, budget tracking, pass-through endpoints, and self-serve key management. LiteLLM is open-source and compatible with the OpenAI format, allowing users to access various LLMs seamlessly.

BCT Digital is an AI-powered risk management suite provider that offers a range of products to help enterprises optimize their core Governance, Risk, and Compliance (GRC) processes. The rt360 suite leverages next-generation technologies, sophisticated AI/ML models, data-driven algorithms, and predictive analytics to assist organizations in managing various risks effectively. BCT Digital's solutions cater to the financial sector, providing tools for credit risk monitoring, early warning systems, model risk management, environmental, social, and governance (ESG) risk assessment, and more.

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.

Weights & Biases is an AI tool that offers documentation, guides, tutorials, and support for using AI models in applications. The platform provides two main products: W&B Weave for integrating AI models into code and W&B Models for building custom AI models. Users can access features such as tracing, output evaluation, cost estimates, hyperparameter sweeps, model registry, and more. Weights & Biases aims to simplify the process of working with AI models and improving model reproducibility.

Role Model AI is a revolutionary multi-dimensional assistant that combines practicality and innovation. It offers four dynamic interfaces for seamless interaction: phone calls for on-the-go assistance, an interactive agent dashboard for detailed task management, lifelike 3D avatars for immersive communication, and an engaging Fortnite world integration for a gaming-inspired experience. Role Model AI adapts to your lifestyle, blending seamlessly into your personal and professional worlds, providing unparalleled convenience and a unique, versatile solution for managing tasks and interactions.

UbiOps is an AI infrastructure platform that helps teams quickly run their AI & ML workloads as reliable and secure microservices. It offers powerful AI model serving and orchestration with unmatched simplicity, speed, and scale. UbiOps allows users to deploy models and functions in minutes, manage AI workloads from a single control plane, integrate easily with tools like PyTorch and TensorFlow, and ensure security and compliance by design. The platform supports hybrid and multi-cloud workload orchestration, rapid adaptive scaling, and modular applications with unique workflow management system.

Wallaroo.AI is an AI inference platform that offers production-grade AI inference microservices optimized on OpenVINO for cloud and Edge AI application deployments on CPUs and GPUs. It provides hassle-free AI inferencing for any model, any hardware, anywhere, with ultrafast turnkey inference microservices. The platform enables users to deploy, manage, observe, and scale AI models effortlessly, reducing deployment costs and time-to-value significantly.

OneDollarAI.lol is an AI application that offers the best AI language model for just one dollar a month. It features LLaMa 3, which is known for being the fastest and most powerful language model. Users can enjoy unlimited usage with no limits, at an affordable price of only $1 per month. The application provides instant responses and requires no setup. It is designed to be user-friendly and accessible to all, making it a convenient tool for various language-related tasks.

Sample notebooks for IBM Watsonx.ai for IBM Cloud and IBM Watsonx.ai software product. The notebooks demonstrate capabilities such as running experiments on model building using AutoAI or Deep Learning, deploying third-party models as web services or batch jobs, monitoring deployments with OpenScale, managing model lifecycles, inferencing Watsonx.ai foundation models, and integrating LangChain with Watsonx.ai. Notebooks with Python code and the Python SDK can be found in the `python_sdk` folder. The REST API examples are organized in the `rest_api` folder.

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.

LLMOps with Prompt flow is a template and guidance for building LLM-infused apps using Prompt flow. It provides centralized code hosting, lifecycle management, variant and hyperparameter experimentation, A/B deployment, many-to-many dataset/flow relationships, multiple deployment targets, comprehensive reporting, BYOF capabilities, configuration-based development, local prompt experimentation and evaluation, endpoint testing, and optional Human-in-loop validation. The tool is customizable to suit various application needs.

Experts.js is a tool that simplifies the creation and deployment of OpenAI's Assistants, allowing users to link them together as Tools to create a Panel of Experts system with expanded memory and attention to detail. It leverages the new Assistants API from OpenAI, which offers advanced features such as referencing attached files & images as knowledge sources, supporting instructions up to 256,000 characters, integrating with 128 tools, and utilizing the Vector Store API for efficient file search. Experts.js introduces Assistants as Tools, enabling the creation of Multi AI Agent Systems where each Tool is an LLM-backed Assistant that can take on specialized roles or fulfill complex tasks.

Fueling-Ambitions-Via-Book-Discoveries is an Advanced Machine Learning & AI Course designed for students, professionals, and AI researchers. The course integrates rigorous theoretical foundations with practical coding exercises, ensuring learners develop a deep understanding of AI algorithms and their applications in finance, healthcare, robotics, NLP, cybersecurity, and more. Inspired by MIT, Stanford, and Harvard’s AI programs, it combines academic research rigor with industry-standard practices used by AI engineers at companies like Google, OpenAI, Facebook AI, DeepMind, and Tesla. Learners can learn 50+ AI techniques from top Machine Learning & Deep Learning books, code from scratch with real-world datasets, projects, and case studies, and focus on ML Engineering & AI Deployment using Django & Streamlit. The course also offers industry-relevant projects to build a strong AI portfolio.

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.

QMedia is an open-source multimedia AI content search engine designed specifically for content creators. It provides rich information extraction methods for text, image, and short video content. The tool integrates unstructured text, image, and short video information to build a multimodal RAG content Q&A system. Users can efficiently search for image/text and short video materials, analyze content, provide content sources, and generate customized search results based on user interests and needs. QMedia supports local deployment for offline content search and Q&A for private data. The tool offers features like content cards display, multimodal content RAG search, and pure local multimodal models deployment. Users can deploy different types of models locally, manage language models, feature embedding models, image models, and video models. QMedia aims to spark new ideas for content creation and share AI content creation concepts in an open-source manner.

Starwhale is an MLOps/LLMOps platform that brings efficiency and standardization to machine learning operations. It streamlines the model development lifecycle, enabling teams to optimize workflows around key areas like model building, evaluation, release, and fine-tuning. Starwhale abstracts Model, Runtime, and Dataset as first-class citizens, providing tailored capabilities for common workflow scenarios including Models Evaluation, Live Demo, and LLM Fine-tuning. It is an open-source platform designed for clarity and ease of use, empowering developers to build customized MLOps features tailored to their needs.

MLflow is a platform to streamline machine learning development, including tracking experiments, packaging code into reproducible runs, and sharing and deploying models. MLflow offers a set of lightweight APIs that can be used with any existing machine learning application or library (TensorFlow, PyTorch, XGBoost, etc), wherever you currently run ML code (e.g. in notebooks, standalone applications or the cloud). MLflow's current components are: * `MLflow Tracking `_: An API to log parameters, code, and results in machine learning experiments and compare them using an interactive UI. * `MLflow Projects `_: A code packaging format for reproducible runs using Conda and Docker, so you can share your ML code with others. * `MLflow Models `_: A model packaging format and tools that let you easily deploy the same model (from any ML library) to batch and real-time scoring on platforms such as Docker, Apache Spark, Azure ML and AWS SageMaker. * `MLflow Model Registry `_: A centralized model store, set of APIs, and UI, to collaboratively manage the full lifecycle of MLflow Models.

This course has 18 lessons. Each lesson covers its own topic so start wherever you like! Lessons are labeled either "Learn" lessons explaining a Generative AI concept or "Build" lessons that explain a concept and code examples in both **Python** and **TypeScript** when possible. Each lesson also includes a "Keep Learning" section with additional learning tools. **What You Need** * Access to the Azure OpenAI Service **OR** OpenAI API - _Only required to complete coding lessons_ * Basic knowledge of Python or Typescript is helpful - *For absolute beginners check out these Python and TypeScript courses. * A Github account to fork this entire repo to your own GitHub account We have created a **Course Setup** lesson to help you with setting up your development environment. Don't forget to star (🌟) this repo to find it easier later. ## 🧠 Ready to Deploy? If you are looking for more advanced code samples, check out our collection of Generative AI Code Samples in both **Python** and **TypeScript**. ## 🗣️ Meet Other Learners, Get Support Join our official AI Discord server to meet and network with other learners taking this course and get support. ## 🚀 Building a Startup? Sign up for Microsoft for Startups Founders Hub to receive **free OpenAI credits** and up to **$150k towards Azure credits to access OpenAI models through Azure OpenAI Services**. ## 🙏 Want to help? Do you have suggestions or found spelling or code errors? Raise an issue or Create a pull request ## 📂 Each lesson includes: * A short video introduction to the topic * A written lesson located in the README * Python and TypeScript code samples supporting Azure OpenAI and OpenAI API * Links to extra resources to continue your learning ## 🗃️ Lessons | | Lesson Link | Description | Additional Learning | | :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ | | 00 | Course Setup | **Learn:** How to Setup Your Development Environment | Learn More | | 01 | Introduction to Generative AI and LLMs | **Learn:** Understanding what Generative AI is and how Large Language Models (LLMs) work. | Learn More | | 02 | Exploring and comparing different LLMs | **Learn:** How to select the right model for your use case | Learn More | | 03 | Using Generative AI Responsibly | **Learn:** How to build Generative AI Applications responsibly | Learn More | | 04 | Understanding Prompt Engineering Fundamentals | **Learn:** Hands-on Prompt Engineering Best Practices | Learn More | | 05 | Creating Advanced Prompts | **Learn:** How to apply prompt engineering techniques that improve the outcome of your prompts. | Learn More | | 06 | Building Text Generation Applications | **Build:** A text generation app using Azure OpenAI | Learn More | | 07 | Building Chat Applications | **Build:** Techniques for efficiently building and integrating chat applications. | Learn More | | 08 | Building Search Apps Vector Databases | **Build:** A search application that uses Embeddings to search for data. | Learn More | | 09 | Building Image Generation Applications | **Build:** A image generation application | Learn More | | 10 | Building Low Code AI Applications | **Build:** A Generative AI application using Low Code tools | Learn More | | 11 | Integrating External Applications with Function Calling | **Build:** What is function calling and its use cases for applications | Learn More | | 12 | Designing UX for AI Applications | **Learn:** How to apply UX design principles when developing Generative AI Applications | Learn More | | 13 | Securing Your Generative AI Applications | **Learn:** The threats and risks to AI systems and methods to secure these systems. | Learn More | | 14 | The Generative AI Application Lifecycle | **Learn:** The tools and metrics to manage the LLM Lifecycle and LLMOps | Learn More | | 15 | Retrieval Augmented Generation (RAG) and Vector Databases | **Build:** An application using a RAG Framework to retrieve embeddings from a Vector Databases | Learn More | | 16 | Open Source Models and Hugging Face | **Build:** An application using open source models available on Hugging Face | Learn More | | 17 | AI Agents | **Build:** An application using an AI Agent Framework | Learn More | | 18 | Fine-Tuning LLMs | **Learn:** The what, why and how of fine-tuning LLMs | Learn More |

CSGHub is an open source, trustworthy large model asset management platform that can assist users in governing the assets involved in the lifecycle of LLM and LLM applications (datasets, model files, codes, etc). With CSGHub, users can perform operations on LLM assets, including uploading, downloading, storing, verifying, and distributing, through Web interface, Git command line, or natural language Chatbot. Meanwhile, the platform provides microservice submodules and standardized OpenAPIs, which could be easily integrated with users' own systems. CSGHub is committed to bringing users an asset management platform that is natively designed for large models and can be deployed On-Premise for fully offline operation. CSGHub offers functionalities similar to a privatized Huggingface(on-premise Huggingface), managing LLM assets in a manner akin to how OpenStack Glance manages virtual machine images, Harbor manages container images, and Sonatype Nexus manages artifacts.

ATLAS (Adaptive Task & Logic Automation System) is a high-performance Model Context Protocol server designed for LLMs to manage complex task hierarchies. Built with TypeScript, it features ACID-compliant storage, efficient task tracking, and intelligent template management. ATLAS provides LLM Agents task management through a clean, flexible tool interface. The server implements the Model Context Protocol (MCP) for standardized communication between LLMs and external systems, offering hierarchical task organization, task state management, smart templates, enterprise features, and performance optimization.

MCPHub.nvim is a powerful Neovim plugin that integrates MCP (Model Context Protocol) servers into your workflow. It offers a centralized config file for managing servers and tools, with an intuitive UI for testing resources. Ideal for LLM integration, it provides programmatic API access and interactive testing through the `:MCPHub` command.

LakeSoul is a cloud-native Lakehouse framework that supports scalable metadata management, ACID transactions, efficient and flexible upsert operation, schema evolution, and unified streaming & batch processing. It supports multiple computing engines like Spark, Flink, Presto, and PyTorch, and computing modes such as batch, stream, MPP, and AI. LakeSoul scales metadata management and achieves ACID control by using PostgreSQL. It provides features like automatic compaction, table lifecycle maintenance, redundant data cleaning, and permission isolation for metadata.

WebLLM is a modular and customizable javascript package that directly brings language model chats directly onto web browsers with hardware acceleration. Everything runs inside the browser with no server support and is accelerated with WebGPU. WebLLM is fully compatible with OpenAI API. That is, you can use the same OpenAI API on any open source models locally, with functionalities including json-mode, function-calling, streaming, etc. We can bring a lot of fun opportunities to build AI assistants for everyone and enable privacy while enjoying GPU acceleration.

The Generative AI Application Builder on AWS (GAAB) is a solution that provides a web-based management dashboard for deploying customizable Generative AI (Gen AI) use cases. Users can experiment with and compare different combinations of Large Language Model (LLM) use cases, configure and optimize their use cases, and integrate them into their applications for production. The solution is targeted at novice to experienced users who want to experiment and productionize different Gen AI use cases. It uses LangChain open-source software to configure connections to Large Language Models (LLMs) for various use cases, with the ability to deploy chat use cases that allow querying over users' enterprise data in a chatbot-style User Interface (UI) and support custom end-user implementations through an API.

PartCAD is a tool for documenting manufacturable physical products, providing tools to maintain product information and streamline workflows at all product lifecycle phases. It is a next-generation CAD tool that focuses on specifying manufacturable physical products using computer-aided design in a more generic sense, including the use of AI models. PartCAD offers modular and reusable packages for product information, generating outputs like product documentation, bill of materials, sourcing information, and manufacturing process specifications. It integrates with third-party tools for iterative improvements, design validation, and manufacturing processes verification. PartCAD also offers supplementary products like a CRM and inventory tool for managing part manufacturing and assembly shops. By enabling easy switching between third-party tools, PartCAD creates a competitive environment for service providers and ensures data sovereignty for users.

At ZenML, we believe in the importance of annotation and labeling workflows in the machine learning lifecycle. This repository showcases a curated list of open-source data annotation and labeling tools that are actively maintained and fit for purpose. The tools cover various domains such as multi-modal, text, images, audio, video, time series, and other data types. Users can contribute to the list and discover tools for tasks like named entity recognition, data annotation for machine learning, image and video annotation, text classification, sequence labeling, object detection, and more. The repository aims to help users enhance their data-centric workflows by leveraging these tools.

TapeAgents is a framework that leverages a structured, replayable log of the agent session to facilitate all stages of the LLM Agent development lifecycle. The agent reasons by processing the tape and the LLM output to produce new thoughts, actions, control flow steps, and append them to the tape. Key features include building agents as low-level state machines or high-level multi-agent team configurations, debugging agents with TapeAgent studio or TapeBrowser apps, serving agents with response streaming, and optimizing agent configurations using successful tapes. The Tape-centric design of TapeAgents provides ultimate flexibility in project development, allowing access to tapes for making prompts, generating next steps, and controlling agent behavior.

Try the new AI chat model: GPT 4o ("Omni") Assistant. It's faster and better than regular GPT. Plus it will incorporate speech-to-text, intelligence, and speech-to-text capabilities with extra low latency.

AI language model specializing in orchestrating human-AI interactions

Benchmark HVAC GPT model with unmatched expertise and forward-thinking solutions, powered by OpenAI

Step into the world of high fashion. As runway designers, they create unique collections, organize dazzling fashion shows, and stay ahead of the latest trends. It blends elements of design, marketing, and business management in the glamorous fashion industry

Event Modeling Architect for detailed system process steps

专注于IP和公私域商业模式，提供流量和变现的一站式解决方案。

Designs workflow diagrams from user inputs

Web Deployment, Designing, 3D - Modeling, CMS system and much more Providing

This is the most intelligent GPT evern in existence

Updated: https://chat.openai.com/g/g-32kHtFC2B-guru

Formador para la certificación de ML Engineer en GCP, con respuestas y explicaciones detalladas.

Discover A More Robust Business: Craft tailored value proposition statements, develop a comprehensive business model canvas, conduct detailed PESTLE analysis, and gain strategic insights on enhancing business model elements like scalability, cost structure, and market competition strategies. (v1.18)

Let's get started by telling me about your business: What do you offer? Who do you serve? ------------------------------------------------------- Need help Prompt Engineering? Reach out on LinkedIn: StephenHnilica

Business Model Canvas Creator - Build and evaluate your business model

Generates Environmental impact assessment templates based on specific global locations and parameters.

Un aiuto a costruire il Business Model Canvas della tua iniziativa

Business model expert, create detailed reports based on business ideas.

A software architect for C4 Model generation.

Consultor experto en Business Model Canvas para emprendedores