Best AI tools for< Manage Engineering Projects >

Spoke.ai is an AI tool designed to enhance communication and streamline workflow processes. The platform aims to help users communicate more effectively and build projects faster by leveraging artificial intelligence technology. By joining Salesforce to support Slack AI, Spoke.ai is at the forefront of revolutionizing the future of work. The tool offers various features to improve collaboration and productivity, making it a valuable asset for teams and individuals alike.

GitBook is a knowledge management platform that helps engineering teams centralize, access, and add to their technical knowledge in the tools they use every day. With GitBook, teams can capture knowledge from conversations, code, and meetings, and turn it into useful, readable documentation. GitBook also offers a variety of features to help teams collaborate on documentation, including a branch-based workflow, real-time editing, and user permissions.

Ocular is an AI-powered search platform that allows users to search, visualize, and take action on their work and engineering tools and data on one unified platform. It is designed to help engineers work more efficiently and effectively by providing them with a single, central location to access all of their relevant information.

Allex is a project management and portfolio management software that offers a digital multi-project solution. It helps project professionals accelerate time-to-market results by harmonizing projects, resources, and tasks. The platform enables users to have a sweeping overview of projects, predict capacity bottlenecks, improve project coordination through collaboration, and communicate effectively with internal and external stakeholders. Allex is designed to handle complex projects and offers expert support to ensure informed decision-making from planning to launch.

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.

Coherent Solutions is a custom software development and engineering company that offers a range of services including digital product engineering, artificial intelligence, data and analytics, mobile development, DevOps and cloud, quality assurance, Salesforce, and product design and UX. They work collaboratively and transparently with clients to deliver successful projects. The company values set the standard for all decisions, and they have a strong focus on understanding and meeting the business needs of their clients. Coherent Solutions has a strong track record of success in various industries and is known for empowering business success through global expertise and industry-specific product engineering consulting services.

Langtail is a platform that helps developers build, test, and deploy AI-powered applications. It provides a suite of tools to help developers debug prompts, run tests, and monitor the performance of their AI models. Langtail also offers a community forum where developers can share tips and tricks, and get help from other users.

Devin AI, developed by Cognition Labs, is the world's first fully autonomous AI software engineer. It streamlines software development by handling complex tasks, allowing engineers to focus on more challenging aspects. Devin AI possesses advanced programming skills, can manage complex tasks, understands and learns contextually, integrates with developer tools, and offers collaborative features. It can build and deploy applications, detect and fix bugs, contribute to open-source projects, train AI models, and handle GitHub repositories. Devin AI has demonstrated strong performance in issue resolution, surpassing previous AI models. It is currently in early access, with plans for future enhancements and integration with various development tools and platforms.

The Library Innovation Lab at Harvard University is an AI tool that focuses on bringing library principles to technological frontiers. It is a forward-looking group working at the intersection of libraries, technology, and law. The lab aims to democratize open knowledge and explore the use of generative AIs in information access and law. They offer various projects like Caselaw Access Project, H2O, The Nuremberg Project, Perma.cc, Alterspace, and Time Capsule Encryption to achieve their goals.

Dart is the ultimate AI project management tool designed to save time and streamline project management processes. It offers features like task execution, subtask generation, project planning, duplicate detection, roadmaps, calendar views, document storage, meeting notes, integrations with workplace tools, and more. Dart is used by teams across various roles like engineering, product management, leadership, design, and sales to enhance productivity and efficiency in task management. The application leverages AI capabilities to automate tasks, generate reports, and assist in project ideation and execution.

RealEngineers is an innovative AI-powered job platform that revolutionizes the engineering hiring process. Unlike traditional job sites, it focuses on detailed project-based profiles instead of resumes, leveraging AI to match skills and experiences with job requirements. Employers can evaluate candidates quickly and fairly, while candidates can showcase their authenticity and detailed projects to stand out. The platform aims to provide a level playing field for all candidates and help bridge the gap between talent and opportunity in the engineering industry.

Elessar is an AI-powered platform designed to enhance engineering productivity by providing automatic documentation, reporting, and visibility for development teams. It seamlessly integrates with existing ecosystems, connects codebases, communications, and documentation tools, and offers features like AI-generated pull request changelogs, Notion documentation, Slack bot integration, VS Code extension, and issue tracking. Elessar ensures data privacy and security by following SOC II compliant policies and infrastructures, and it does not use company data for training or storage.

Harness is an AI-driven software delivery platform that empowers software engineering teams with AI-infused technology for seamless software delivery. It offers a single platform for all software delivery needs, including DevOps modernization, continuous delivery, GitOps, feature flags, infrastructure as code management, chaos engineering, service reliability management, secure software delivery, cloud cost optimization, and more. Harness aims to simplify the developer experience by providing actionable insights on SDLC, secure software supply chain assurance, and AI development assistance throughout the software delivery lifecycle.

PromptInterface.ai is an innovative prompt engineering solution that allows users to create personalized assistants for colleagues using intuitive forms with GPT-4 prompts. It revolutionizes businesses by optimizing collaborative work, boosting productivity, improving communication, and simplifying time-consuming tasks. The application offers clear and transparent pricing, secure payments, and the ability to manage subscriptions easily. With no limit on prompt templates and compatibility with smartphones, PromptInterface.ai is a powerful and user-friendly tool for businesses looking to automate processes and enhance team collaboration.

DevRev is an AI-native modern support platform that offers a comprehensive solution for customer experience enhancement. It provides data engineering, knowledge graph, and customizable LLMs to streamline support, product management, and software development processes. With features like in-browser analytics, consumer-grade social collaboration, and global scale API calls, DevRev aims to bring together different silos within a company to drive efficiency and collaboration. The platform caters to support people, product managers, and developers, automating tasks, assisting in decision-making, and elevating collaboration levels. DevRev is designed to empower digital product teams to assimilate customer feedback in real-time, ultimately powering the next generation of technology companies.

Edraw.AI is an AI-powered visual collaboration platform that empowers users to create various types of content including diagrams, charts, and presentations in seconds. It offers a wide range of features such as flowchart maker, mind map maker, org chart maker, and more. With a beginner-friendly interface and vast resources, Edraw.AI enables real-time collaboration and teamwork without the need for downloads. It caters to different industries like project management, research, engineering, marketing, consulting, education, and IT, providing tools for enhanced visualization, planning, and communication.

AI Checklist Generator is an AI tool that helps users create custom checklist templates for various processes across different industries. It leverages AI technology to streamline the checklist creation process, ensuring accuracy and efficiency. The tool offers a wide range of pre-designed checklist templates tailored to specific industries, such as accounting, advertising, agriculture, construction, consulting, e-commerce, education, engineering, financial services, hotel & hospitality, human resources, information technology, insurance, law firm, manufacturing, marketing, property management, real estate, restaurant, retail, software development, and transportation. Users can easily customize these templates or create their own checklists using AI-powered features.

Gitya is an AI-powered GitHub assistant designed to streamline your GitHub workflow by automating minor tasks and enhancing productivity. With features like GitHub App integration, AI-enhanced automation, PR management, and ticket automation, Gitya aims to help users spend less time on busywork and more time on high-impact engineering tasks. Users have praised Gitya for its ability to reduce time spent on bug fixes and PR management, ultimately leading to increased project efficiency and success.

OPS 360 is an AI-powered event management software that offers a comprehensive suite of solutions for organizing virtual, hybrid, and in-person events. The platform enables event organizers, service providers, and engineering teams to create personalized interactions that drive customer growth. OPS 360 simplifies event planning, enhances attendee engagement, and maximizes revenue generation through its innovative features and capabilities.

Pralin AI is an AI application that offers expert-level support and strategic guidance for Palantir implementations. Their services are designed to accelerate projects, reduce risks, and maximize the value of Foundry and AIP investments. With a focus on accelerating project timelines, improving outcomes, and building internal capabilities, Pralin AI provides field-validated data and AI mastery across various industries. Leveraging extensive Palantir experience and a network of industry experts, Pralin AI aims to revolutionize implementations and drive digital transformation for their clients.

AI on OpenShift is a site providing installation recipes, patterns, and demos for AI/ML tools and applications used in Data Science and Data Engineering projects running on OpenShift. It serves as a comprehensive resource for developers looking to deploy AI solutions on the OpenShift platform.

Awesome AI & Data GitHub-Repos is a curated list of essential GitHub repositories covering the AI & ML landscape. It includes resources for Natural Language Processing, Large Language Models, Computer Vision, Data Science, Machine Learning, MLOps, Data Engineering, SQL & Database, and Statistics. The repository aims to provide a comprehensive collection of projects and resources for individuals studying or working in the field of AI and data science.

Log10 is a one-line Python integration to manage your LLM data. It helps you log both closed and open-source LLM calls, compare and identify the best models and prompts, store feedback for fine-tuning, collect performance metrics such as latency and usage, and perform analytics and monitor compliance for LLM powered applications. Log10 offers various integration methods, including a python LLM library wrapper, the Log10 LLM abstraction, and callbacks, to facilitate its use in both existing production environments and new projects. Pick the one that works best for you. Log10 also provides a copilot that can help you with suggestions on how to optimize your prompt, and a feedback feature that allows you to add feedback to your completions. Additionally, Log10 provides prompt provenance, session tracking and call stack functionality to help debug prompt chains. With Log10, you can use your data and feedback from users to fine-tune custom models with RLHF, and build and deploy more reliable, accurate and efficient self-hosted models. Log10 also supports collaboration, allowing you to create flexible groups to share and collaborate over all of the above features.

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 |

Latitude is an open-source prompt engineering platform that helps developers and product teams build AI features with confidence. It simplifies prompt management, aids in testing AI responses, and provides detailed analytics on request performance. Latitude offers collaborative prompt management, support for advanced features, version control, API and SDKs for integration, observability, evaluations in batch or real-time, and is community-driven. It can be deployed on Latitude Cloud for a managed solution or self-hosted for control and customization.

Synmetrix (prev. MLCraft) is an open source data engineering platform and semantic layer for centralized metrics management. It provides a complete framework for modeling, integrating, transforming, aggregating, and distributing metrics data at scale. Key features include data modeling and transformations, semantic layer for unified data model, scheduled reports and alerts, versioning, role-based access control, data exploration, caching, and collaboration on metrics modeling. Synmetrix leverages Cube (Cube.js) for flexible data models that consolidate metrics from various sources, enabling downstream distribution via a SQL API for integration into BI tools, reporting, dashboards, and data science. Use cases include data democratization, business intelligence, embedded analytics, and enhancing accuracy in data handling and queries. The tool speeds up data-driven workflows from metrics definition to consumption by combining data engineering best practices with self-service analytics capabilities.

Synmetrix is an open source data engineering platform and semantic layer for centralized metrics management. It provides a complete framework for modeling, integrating, transforming, aggregating, and distributing metrics data at scale. Key features include data modeling and transformations, semantic layer for unified data model, scheduled reports and alerts, versioning, role-based access control, data exploration, caching, and collaboration on metrics modeling. Synmetrix leverages Cube.js to consolidate metrics from various sources and distribute them downstream via a SQL API. Use cases include data democratization, business intelligence and reporting, embedded analytics, and enhancing accuracy in data handling and queries. The tool speeds up data-driven workflows from metrics definition to consumption by combining data engineering best practices with self-service analytics capabilities.

EdgeChains is an open-source chain-of-thought engineering framework tailored for Large Language Models (LLMs)- like OpenAI GPT, LLama2, Falcon, etc. - With a focus on enterprise-grade deployability and scalability. EdgeChains is specifically designed to **orchestrate** such applications. At EdgeChains, we take a unique approach to Generative AI - we think Generative AI is a deployment and configuration management challenge rather than a UI and library design pattern challenge. We build on top of a tech that has solved this problem in a different domain - Kubernetes Config Management - and bring that to Generative AI. Edgechains is built on top of jsonnet, originally built by Google based on their experience managing a vast amount of configuration code in the Borg infrastructure.

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

The 'llms-tools' repository is a comprehensive collection of AI tools, open-source projects, and research related to Large Language Models (LLMs) and Chatbots. It covers a wide range of topics such as AI in various domains, open-source models, chats & assistants, visual language models, evaluation tools, libraries, devices, income models, text-to-image, computer vision, audio & speech, code & math, games, robotics, typography, bio & med, military, climate, finance, and presentation. The repository provides valuable resources for researchers, developers, and enthusiasts interested in exploring the capabilities of LLMs and related technologies.

Metaflow is a user-friendly library designed to assist scientists and engineers in developing and managing real-world data science projects. Initially created at Netflix, Metaflow aimed to enhance the productivity of data scientists working on diverse projects ranging from traditional statistics to cutting-edge deep learning. For further information, refer to Metaflow's website and documentation.

Learn Cloud Applied Generative AI Engineering (GenEng) is a course focusing on the application of generative AI technologies in various industries. The course covers topics such as the economic impact of generative AI, the role of developers in adopting and integrating generative AI technologies, and the future trends in generative AI. Students will learn about tools like OpenAI API, LangChain, and Pinecone, and how to build and deploy Large Language Models (LLMs) for different applications. The course also explores the convergence of generative AI with Web 3.0 and its potential implications for decentralized intelligence.

Airbyte is an open-source data integration platform that makes it easy to move data from any source to any destination. With Airbyte, you can build and manage data pipelines without writing any code. Airbyte provides a library of pre-built connectors that make it easy to connect to popular data sources and destinations. You can also create your own connectors using Airbyte's no-code Connector Builder or low-code CDK. Airbyte is used by data engineers and analysts at companies of all sizes to build and manage their data pipelines.

LangChain is an amazing framework to get LLM projects done in a matter of no time, and the ecosystem is growing fast. Here is an attempt to keep track of the initiatives around LangChain. Subscribe to the newsletter to stay informed about the Awesome LangChain. We send a couple of emails per month about the articles, videos, projects, and tools that grabbed our attention Contributions welcome. Add links through pull requests or create an issue to start a discussion. Please read the contribution guidelines before contributing.

Awesome AI is a curated list of artificial intelligence resources including courses, tools, apps, and open-source projects. It covers a wide range of topics such as machine learning, deep learning, natural language processing, robotics, conversational interfaces, data science, and more. The repository serves as a comprehensive guide for individuals interested in exploring the field of artificial intelligence and its applications across various domains.

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.

LinkedIn_AIHawk is an automated tool designed to revolutionize the job search and application process on LinkedIn. It leverages automation and artificial intelligence to efficiently apply to relevant positions, personalize responses, manage application volume, filter listings, generate dynamic resumes, and handle sensitive information securely. The tool aims to save time, increase application relevance, and enhance job search effectiveness in today's competitive landscape.

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.

Notes on AI state of the art, with a focus on generative and large language models. These are the "raw materials" for the https://lspace.swyx.io/ newsletter. This repo used to be called https://github.com/sw-yx/prompt-eng, but was renamed because Prompt Engineering is Overhyped. This is now an AI Engineering notes repo.

Awesome-LLM is a curated list of resources related to large language models, focusing on papers, projects, frameworks, tools, tutorials, courses, opinions, and other useful resources in the field. It covers trending LLM projects, milestone papers, other papers, open LLM projects, LLM training frameworks, LLM evaluation frameworks, tools for deploying LLM, prompting libraries & tools, tutorials, courses, books, and opinions. The repository provides a comprehensive overview of the latest advancements and resources in the field of large language models.

Formal and detailed guide on ABB.

Provides expert guidance in transportation engineering projects.

Cloud Engineer Expert, guiding in cloud tech, projects, career, and industry trends.

Advises on water resources management and infrastructure development.

Advises on sustainable engineering solutions to environmental challenges.

Enhances manufacturing operations through advanced mechanical engineering expertise.

Civil Engineering expert

Engineering Director | Delivery Management, and Client Engagement | Bridging the Gap Between Technology and Business Goals

Premier expert in engineering, architecture, design, construction, and project management, powered by OpenAI

AI Assistant for Geotechnical Engineering

A replacement to your Product Manager, Engineering Manager, and your Average Developer and Tester

Ondersteun die skep van prompt vir ChatGpt - Afrikaanse taal

A focused and precise CTO advisor

Your communication assistant, TechTalker, simplifies messaging for software engineers with clarity and ease.

Friendly process engineer for Coda.io

Empowering beginners with lean construction knowledge by "Amir Zavichi"

Expert in BIM Integration, leading with precision and innovation - Powered by OpenAI

A 3D Printed Construction wiz trained on expert interviews. Use creatively, don't depend on 3DCP Guru GPT for factually accurate info (although it's pretty darn good)

A helpful guide for biochemical engineers, offering insights and reassurance.

Friendly, creative mechanical design specialist