Best AI tools for< Construction Engineer >

Skillroads is a trusted AI resume maker that empowers users in their job search process. The platform offers a range of services including resume writing, editing, LinkedIn profile makeover, AI resume checker, and career tips. Skillroads leverages Artificial Intelligence to create tailored resumes, cover letters, and job matches for users. The application simplifies the job application process by providing personalized job openings from top companies and career development plans. Users can access various career services, including resume creation, cover letter writing, and interview help, to enhance their job search experience.

IFS.ai is an Industrial AI application that delivers actionable insights to reduce risk, automate production, and drive innovation across various industries such as Aerospace and Defense, Energy Utilities and Resources, Construction and Engineering, Manufacturing, and Service Industries. It harnesses data and AI capabilities to supercharge insights, optimize processes, enhance productivity, and achieve sustainability goals. IFS.ai empowers users to make informed decisions, adapt dynamically to changing conditions, and drive transformative change in their operations.

Observance is an AI-powered construction management platform developed by Inkers.ai. It integrates advanced AI technologies to provide features such as 4D BIM, Snag List, Project Milestones, Scan to BIM, Thermals Analytics, and Deviation Analysis. The platform offers real-time tracking, smart scheduling, BIM integration, analytics dashboard, and next-generation construction AI capabilities. Observance helps owners, contractors, and architects in tracking, managing, and executing construction projects efficiently. It also offers defect detection, mesh segmentation, objects identification, and health & safety monitoring using AI algorithms.

AI Clearing is an AI-powered progress tracking tool with quality control reporting specifically designed for construction projects. It allows users to monitor progress, track production, and align with schedules seamlessly. The tool is fully driven by site and project data, providing actionable insights to boost teams' performance, save resources, and cut administrative and supervision time. AI Clearing is trusted by industry professionals and offers a comprehensive solution to overcome challenges in the construction industry.

Doxel is an AI-powered construction progress tracking tool that provides a comprehensive solution for stakeholders in various industries. It automates progress tracking, reduces schedule risks, and speeds up construction processes by capturing and analyzing detailed data using advanced image recognition technology. Doxel offers powerful tools for both office and field use, enabling project leaders to mitigate risks, increase reliability, and predictability. With its objective visibility and automation features, Doxel helps stakeholders save time, make informed decisions, and improve project efficiency.

Constructable is a team-first construction management tool designed for modern construction teams. It empowers commercial construction teams to focus on building amazing projects by providing high performance features across devices. Constructable offers effortless collaboration, intuitive design, and AI-powered search capabilities to enhance team productivity and decision-making. The application includes tools for drawings, photos, AI search, daily logs, punch lists, RFIs, submittals, and financial management. With simple pricing and enterprise-ready security, Constructable ensures a seamless user experience and efficient project management.

viAct.ai is an AI-powered construction management software and app that utilizes computer vision and video analytics for workplace safety. The platform offers scenario-based AI vision technology to simplify monitoring processes in industries such as construction, oil & gas, mining, manufacturing, and more. viAct.ai helps in automating monitoring tasks, empowering jobsites with automated construction management software powered by AI video analytics.

Slate Technologies Solutions is an AI-powered data analytics software that leverages predictive AI, generative AI, and conversational AI to provide a powerful toolkit for next-generation construction. The software connects, contextualizes, and enhances relevant information within existing data sources, allowing users to query, interact, and make decisions based on data insights and recommendations. Slate aims to address real-world construction problems by empowering teams with AI-driven intelligence, optimizing data, and turning unstructured information into actionable insights. The application improves operational efficiency, provides real-time progress reporting, and enables teams to make smarter decisions, ultimately driving profitability and success in construction projects.

Proxy is an AI-powered platform that focuses on utility scale renewables projects. It aims to automate renewable energy projects to power communities, businesses, and homes. Proxy provides intelligent financing solutions, project coordination services, and energy market integrations to streamline the process of generating renewable power. As an innovation partner with the U.S. Department of Energy, Proxy is committed to offsetting carbon emissions and making a significant impact on the environment.

Beam AI is the #1 end-to-end automated takeoff software designed for General Contractors, Subcontractors, and Suppliers in the construction industry. It leverages cutting-edge Artificial Intelligence technology to provide accurate and fast quantity takeoffs for various trades, saving up to 90% of the time typically spent on manual takeoffs. With Beam AI, users can streamline their bidding process, send out more estimates, and focus on value engineering to build competitive estimates. The software offers features such as cloud-based collaboration, 100% done-for-you quantity takeoffs, auto-detection of spec details, and the ability to process multiple takeoffs in parallel.

XKool Technology is an AI cloud platform offering comprehensive solutions for the building industry. It provides digital and intelligent empowerment for design, construction, and management processes. The platform integrates AI technology to enhance building industrial upgrades and offers AI-assisted content creation, model marketplace, AI toolbox, and various design and management solutions.

Widya Robotics is an AI, Automation, and Robotics solutions provider that offers a range of innovative products and solutions for various industries such as construction, manufacturing, retail, and traffic and transportation. The company specializes in technologies like LiDAR for load scanning, gas monitoring, and AI-driven solutions to enhance efficiency, safety, and profitability for businesses. Widya Robotics has received recognition for its cutting-edge technology and commitment to helping companies achieve their financial and branding goals.

OpenSpace is an AI-powered reality intelligence platform that provides complete visual records of construction projects, enabling efficient project management. It uses Spatial AI technology to automate site capture and simplify documentation, helping teams save time, increase productivity, and reduce risks. With features like field notes, mobile app, and quick image mapping, OpenSpace streamlines workflows for QA/QC, RFIs, and punch lists. The platform offers clear visual proof of site conditions, reducing rework and insurance costs. OpenSpace is known for its reliability, speed, and power, making it a trusted solution for industry leaders in construction.

Opteam is a construction project management software designed to help construction companies manage their projects efficiently. It offers features such as progress tracking, schedule analysis, real-time dashboards, and automated progress requests. Opteam aims to address the shortcomings of traditional construction project management software by providing dynamic solutions for smarter infrastructure management. The platform is user-friendly and allows users to track, monitor, and share project progress seamlessly.

Runopt is an AI-powered software for land development that revolutionizes the design process by integrating layout, grading, drainage, and utilities into one optimization problem. It aims to deliver cost-effective, sustainable designs in minutes, offering ecological and environmental benefits to developers, engineers, governments, and NGOs. Runopt automates complex calculations, enhances decision-making, and streamlines collaboration, making it a valuable tool for civil engineers, urban planners, and construction firms.

UpCodes is a searchable platform that provides access to building codes, assemblies, and building products libraries. It offers a comprehensive database of regulations and standards for construction projects, enabling users to easily search and reference relevant information. With UpCodes, architects, engineers, contractors, and other industry professionals can streamline their workflow, ensure compliance with codes, and enhance the quality of their designs. The platform is designed to simplify the process of accessing and interpreting building codes, saving time and reducing errors in construction projects.

EvolveLab is a digital solutions provider specializing in BIM management and app development for the AEC (Architecture, Engineering, and Construction) industry. They offer a range of powerful apps and services designed to empower architects, engineers, and contractors to streamline their workflows and bring their ideas to life more efficiently. With a focus on data-driven design and AI technology, EvolveLab's innovative tools help users enhance productivity and turn concepts into reality.

Aiternus is an AI Computer Vision and Data Analysis System that is revolutionizing industries with cutting-edge technology. It offers advanced solutions for various sectors such as manufacturing, construction, logistics, healthcare, retail, sports tech, electronics, and office spaces. Aiternus leverages AI to streamline processes, boost productivity, enhance safety and quality standards, and develop tailor-made solutions for clients' unique needs. The application provides features like work process monitoring, route optimization, AI chatbot support, demand predictions, quality control, performance analysis, and automation of tasks in office spaces.

Haystack is a production-ready open-source AI framework designed to facilitate building AI applications. It offers a flexible components and pipelines architecture, allowing users to customize and build applications according to their specific requirements. With partnerships with leading LLM providers and AI tools, Haystack provides freedom of choice for users. The framework is built for production, with fully serializable pipelines, logging, monitoring integrations, and deployment guides for full-scale deployments on various platforms. Users can build Haystack apps faster using deepset Studio, a platform for drag-and-drop construction of pipelines, testing, debugging, and sharing prototypes.

AIM is an AI application that transforms existing heavy equipment into an autonomous fleet, enhancing safety and productivity in mining and construction operations. The AIM Technology Platform offers a plug-and-play solution for various heavy equipment fleets, enabling partners to transition to autonomous operation seamlessly. With real-time KPI data delivery and rigorous safety measures, AIM ensures maximally safe and efficient operations, with ground staff out of harm's way. The application is developed by a team with expertise in heavy industries, robotics, and advanced AI, ensuring cutting-edge solutions for the industry.

Autonomous agents are designed to achieve specific objectives through self-guided instructions. With the emergence and growth of large language models (LLMs), there is a growing trend in utilizing LLMs as fundamental controllers for these autonomous agents. This repository conducts a comprehensive survey study on the construction, application, and evaluation of LLM-based autonomous agents. It explores essential components of AI agents, application domains in natural sciences, social sciences, and engineering, and evaluation strategies. The survey aims to be a resource for researchers and practitioners in this rapidly evolving field.

KWeaver is an open-source cognitive intelligence development framework that provides data scientists, application developers, and domain experts with the ability for rapid development, comprehensive openness, and high-performance knowledge network generation and cognitive intelligence large model framework. It offers features such as automated and visual knowledge graph construction, visualization and analysis of knowledge graph data, knowledge graph integration, knowledge graph resource management, large model prompt engineering and debugging, and visual configuration for large model access.

This project is a tutorial on developing large model applications for novice developers. It aims to provide a comprehensive introduction to large model development, focusing on Alibaba Cloud servers and integrating personal knowledge assistant projects. The tutorial covers the following topics: 1. **Introduction to Large Models**: A simplified introduction for novice developers on what large models are, their characteristics, what LangChain is, and how to develop an LLM application. 2. **How to Call Large Model APIs**: This section introduces various methods for calling APIs of well-known domestic and foreign large model products, including calling native APIs, encapsulating them as LangChain LLMs, and encapsulating them as Fastapi calls. It also provides a unified encapsulation for various large model APIs, such as Baidu Wenxin, Xunfei Xinghuo, and Zh譜AI. 3. **Knowledge Base Construction**: Loading, processing, and vector database construction of different types of knowledge base documents. 4. **Building RAG Applications**: Integrating LLM into LangChain to build a retrieval question and answer chain, and deploying applications using Streamlit. 5. **Verification and Iteration**: How to implement verification and iteration in large model development, and common evaluation methods. The project consists of three main parts: 1. **Introduction to LLM Development**: A simplified version of V1 aims to help beginners get started with LLM development quickly and conveniently, understand the general process of LLM development, and build a simple demo. 2. **LLM Development Techniques**: More advanced LLM development techniques, including but not limited to: Prompt Engineering, processing of multiple types of source data, optimizing retrieval, recall ranking, Agent framework, etc. 3. **LLM Application Examples**: Introduce some successful open source cases, analyze the ideas, core concepts, and implementation frameworks of these application examples from the perspective of this course, and help beginners understand what kind of applications they can develop through LLM. Currently, the first part has been completed, and everyone is welcome to read and learn; the second and third parts are under creation. **Directory Structure Description**: requirements.txt: Installation dependencies in the official environment notebook: Notebook source code file docs: Markdown documentation file figures: Pictures data_base: Knowledge base source file used

Construction-Hazard-Detection is an AI-driven tool focused on improving safety at construction sites by utilizing the YOLOv8 model for object detection. The system identifies potential hazards like overhead heavy loads and steel pipes, providing real-time analysis and warnings. Users can configure the system via a YAML file and run it using Docker. The primary dataset used for training is the Construction Site Safety Image Dataset enriched with additional annotations. The system logs are accessible within the Docker container for debugging, and notifications are sent through the LINE messaging API when hazards are detected.

The 'awesome-ai4db-paper' repository is a curated paper list focusing on AI for database (AI4DB) theory, frameworks, resources, and tools for data engineers. It includes a collection of research papers related to learning-based query optimization, training data set preparation, cardinality estimation, query-driven approaches, data-driven techniques, hybrid methods, pretraining models, plan hints, cost models, SQL embedding, join order optimization, query rewriting, end-to-end systems, text-to-SQL conversion, traditional database technologies, storage solutions, learning-based index design, and a learning-based configuration advisor. The repository aims to provide a comprehensive resource for individuals interested in AI applications in the field of database management.

RoboMatrix is a skill-centric hierarchical framework for scalable robot task planning and execution in an open-world environment. It provides a structured approach to robot task execution using a combination of hardware components, environment configuration, installation procedures, and data collection methods. The framework is developed using the ROS2 framework on Ubuntu and supports robots from DJI's RoboMaster series. Users can follow the provided installation guidance to set up RoboMatrix and utilize it for various tasks such as data collection, task execution, and dataset construction. The framework also includes a supervised fine-tuning dataset and aims to optimize communication and release additional components in the future.

The Cheat-Sheet Collection for DevOps, Engineers, IT professionals, and more is a curated list of cheat sheets for various tools and technologies commonly used in the software development and IT industry. It includes cheat sheets for Nginx, Docker, Ansible, Python, Go (Golang), Git, Regular Expressions (Regex), PowerShell, VIM, Jenkins, CI/CD, Kubernetes, Linux, Redis, Slack, Puppet, Google Cloud Developer, AI, Neural Networks, Machine Learning, Deep Learning & Data Science, PostgreSQL, Ajax, AWS, Infrastructure as Code (IaC), System Design, and Cyber Security.

MATLAB-Simulink-Challenge-Project-Hub is a repository aimed at contributing to the progress of engineering and science by providing challenge projects with real industry relevance and societal impact. The repository offers a wide range of projects covering various technology trends such as Artificial Intelligence, Autonomous Vehicles, Big Data, Computer Vision, and Sustainability. Participants can gain practical skills with MATLAB and Simulink while making a significant contribution to science and engineering. The projects are designed to enhance expertise in areas like Sustainability and Renewable Energy, Control, Modeling and Simulation, Machine Learning, and Robotics. By participating in these projects, individuals can receive official recognition for their problem-solving skills from technology leaders at MathWorks and earn rewards upon project completion.

ReEdgeGPT is a tool designed for reverse engineering the chat feature of the new version of Bing. It provides documentation and guidance on how to collect and use cookies to access the chat feature. The tool allows users to create a chatbot using the collected cookies and interact with the Bing GPT chatbot. It also offers support for different modes like Copilot and Bing, along with plugins for various tasks. The tool covers historical information about Rome, the Lazio region, and provides troubleshooting tips for common issues encountered while using the tool.

HEC-Commander Tools is a suite of python notebooks developed with AI assistance for water resource engineering workflows, providing automation for HEC-RAS and HEC-HMS through Jupyter Notebooks. It contains automation scripts for HEC-HMS, HEC-RAS, and DSS, along with miscellaneous tools. The repository also includes blog posts, ChatGPT assistants, and presentations related to H&H modeling and water resources workflows. Developed to support Region 4 of the Louisiana Watershed Initiative by Fenstermaker.

DevDocs is a platform designed to simplify the process of digesting technical documentation for software engineers and developers. It automates the extraction and conversion of web content into markdown format, making it easier for users to access and understand the information. By crawling through child pages of a given URL, DevDocs provides a streamlined approach to gathering relevant data and integrating it into various tools for software development. The tool aims to save time and effort by eliminating the need for manual research and content extraction, ultimately enhancing productivity and efficiency in the development process.

Awesome Embodied AI Job is a curated list of resources related to jobs in the field of Embodied Artificial Intelligence. It includes job boards, companies hiring, and resources for job seekers interested in roles such as robotics engineer, computer vision specialist, AI researcher, machine learning engineer, and data scientist.

HEC-Commander Tools is a suite of python notebooks developed with AI assistance for water resource engineering workflows, focused on providing automation for HEC-RAS and HEC-HMS through Jupyter Notebooks. It contains automation scripts for HEC-HMS and HEC-RAS, tools for plotting results, and miscellaneous scripts for workflow assistance. The repository also includes blog posts, ChatGPT assistants, and presentations related to H&H modeling and the use of LLM's for water resources workflows.

LLMs is a Chinese large language model technology stack for practical use. It includes high-availability pre-training, SFT, and DPO preference alignment code framework. The repository covers pre-training data cleaning, high-concurrency framework, SFT dataset cleaning, data quality improvement, and security alignment work for Chinese large language models. It also provides open-source SFT dataset construction, pre-training from scratch, and various tools and frameworks for data cleaning, quality optimization, and task alignment.

The LLM course is divided into three parts: 1. 🧩 **LLM Fundamentals** covers essential knowledge about mathematics, Python, and neural networks. 2. 🧑‍🔬 **The LLM Scientist** focuses on building the best possible LLMs using the latest techniques. 3. 👷 **The LLM Engineer** focuses on creating LLM-based applications and deploying them. For an interactive version of this course, I created two **LLM assistants** that will answer questions and test your knowledge in a personalized way: * 🤗 **HuggingChat Assistant**: Free version using Mixtral-8x7B. * 🤖 **ChatGPT Assistant**: Requires a premium account. ## 📝 Notebooks A list of notebooks and articles related to large language models. ### Tools | Notebook | Description | Notebook | |----------|-------------|----------| | 🧐 LLM AutoEval | Automatically evaluate your LLMs using RunPod |  | | 🥱 LazyMergekit | Easily merge models using MergeKit in one click. |  | | 🦎 LazyAxolotl | Fine-tune models in the cloud using Axolotl in one click. |  | | ⚡ AutoQuant | Quantize LLMs in GGUF, GPTQ, EXL2, AWQ, and HQQ formats in one click. |  | | 🌳 Model Family Tree | Visualize the family tree of merged models. |  | | 🚀 ZeroSpace | Automatically create a Gradio chat interface using a free ZeroGPU. |  |

AI By Doing is a hands-on artificial intelligence tutorial series that aims to help beginners understand the principles of machine learning and deep learning while providing practical applications. The content covers various supervised and unsupervised learning algorithms, machine learning engineering, deep learning fundamentals, frameworks like TensorFlow and PyTorch, and applications in computer vision and natural language processing. The tutorials are written in Jupyter Notebook format, combining theory, mathematical derivations, and Python code implementations to facilitate learning and understanding.

Awesome LLM Courses is a curated list of online courses focused on Large Language Models (LLMs). The repository aims to provide a comprehensive collection of free available courses covering various aspects of LLMs, including fundamentals, engineering, and applications. The courses are suitable for individuals interested in natural language processing, AI development, and machine learning. The list includes courses from reputable platforms such as Hugging Face, Udacity, DeepLearning.AI, Cohere, DataCamp, and more, offering a wide range of topics from pretraining LLMs to building AI applications with LLMs. Whether you are a beginner looking to understand the basics of LLMs or an intermediate developer interested in advanced topics like prompt engineering and generative AI, this repository has something for everyone.

LLM4EC is an interdisciplinary research repository focusing on the intersection of Large Language Models (LLM) and Evolutionary Computation (EC). It provides a comprehensive collection of papers and resources exploring various applications, enhancements, and synergies between LLM and EC. The repository covers topics such as LLM-assisted optimization, EA-based LLM architecture search, and applications in code generation, software engineering, neural architecture search, and other generative tasks. The goal is to facilitate research and development in leveraging LLM and EC for innovative solutions in diverse domains.

WritingAIPaper is a comprehensive guide for beginners on crafting AI conference papers. It covers topics like paper structure, core ideas, framework construction, result analysis, and introduction writing. The guide aims to help novices navigate the complexities of academic writing and contribute to the field with clarity and confidence. It also provides tips on readability improvement, logical strength, defensibility, confusion time reduction, and information density increase. The appendix includes sections on AI paper production, a checklist for final hours, common negative review comments, and advice on dealing with paper rejection.

Empowering beginners with lean construction knowledge by "Amir Zavichi"

Expert in construction project management and document analysis.

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

Construction machinery expert, developed on OpenAI

Futuristic construction AI with interplanetary and nano-robotics integration

I organize my thoughts using ontology matrices, for detailed CWP advice.

Advises on geotechnical engineering to enhance infrastructure stability and longevity.

Upload a site photo to assess the potential hazard and seek advises from experience AI Safety Officer

Assistant for creating a construction project delivery handbook.

Informative guide on road construction, maintenance, and traffic disruptions.

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)

I read and interpret Lithuanian construction norms.

Civil Engineering expert

A friendly assistant for GPT configuration, offering step-by-step guidance for advanced and simple GPT construction.

AI Assistant for Geotechnical Engineering

Provides expert guidance in transportation engineering projects.

Provides guidance on construction projects

Expert in building construction, design, and architecture.

Building and Construction Information for Australia - no guarantee of this information, use at your own risk

Expert software architect with experience in design, construction, development, testing and deployment of Web, Mobile and Standalone software architectures