Best AI tools for< Construction Supervisor >

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.

ganttLify is a project management application that offers a gamified approach to tracking, analyzing, and visualizing tasks using tools like Gantt charts, EVM, CPM, and curves. It helps both professionals and hobbyists manage projects efficiently by providing features such as Critical Path Method (CPM), Earned Value Management (EVM), Gantt Chart visualization, Cumulative Cost Curve monitoring, text notes & to-dos organization, sketch & draw capabilities, and upcoming AI, AR/VR, voice note, and team collaboration support.

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.

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.

Attentive.ai is an AI-powered platform designed to automate landscaping, paving, and construction businesses. It offers end-to-end automation solutions for various industry needs, such as takeoff measurements, workflow management, and bid automation. The platform utilizes advanced AI algorithms to provide accurate measurements, streamline workflows, and optimize business operations. With features like automated takeoffs, smart scheduling, and real-time insights, Attentive.ai aims to enhance sales efficiency, production optimization, and back-office operations for field service businesses. Trusted by over 750 field service businesses, Attentive.ai is a comprehensive solution for managing landscape maintenance and construction projects efficiently.

Intangles is an advanced fleet management and predictive analytics platform powered by AI technology. It offers a suite of solutions designed to optimize fleet operations, improve vehicle health monitoring, enhance driving behavior, track fuel consumption, automate operations, and provide accurate predictive analytics. Intangles caters to various industries such as trucking, construction, mining, farming, oil & gas, transit, marine engines, gensets, and waste management. The platform leverages state-of-the-art technology including Digital Twin Technology, Integrated Solution, and Predictive Analytics to deliver outstanding results. Intangles' mission is to spark a technology revolution in the mobility industry by helping businesses save time and money through predictive maintenance and real-time data insights.

Fieldproxy is an AI-powered Field Service Management (FSM) software that offers solutions for various industries such as HVAC, Solar Energy, Telecommunications, Electrical & Powergrid Systems, Pest Control Services, FMCG, Banking & Financial Services, Construction, and Facilities Management. The platform provides real-time oversight, automated ticket creation, predictive service scheduling, and asset lifecycle management. Fieldproxy aims to empower on-ground teams, increase productivity, automate workflows, and enhance customer service across different sectors.

SCALZ.AI is a cutting-edge AI-driven digital marketing and consulting platform that empowers businesses with advanced AI technologies to enhance online visibility, boost search engine rankings, and drive superior digital marketing strategies. Specializing in sectors like addiction treatment, healthcare, construction, and real estate, SCALZ.AI offers tailored solutions through detailed keyword research, competitive analysis, predictive AI trend spotting, SEO-optimized content creation, PPC and social media marketing, and more. The platform aims to transform businesses through customized AI-driven consulting services, market research, brand strategy development, digital transformation consulting, customer experience strategy, and sales funnel optimization.

Sanctuary Cognitive Systems Corporation is a company that develops and manufactures general-purpose robots. Their flagship product, Phoenix™, is the world's first humanoid general-purpose robot powered by Carbon™, their pioneering AI control system. Phoenix™ is designed for work and is the only general-purpose robot featured in TIME's Best Inventions 2023. Sanctuary's robots are remotely piloted or supervised by people and are designed to both train and work alongside them. When instructed to do so, their robots will use their own built-in autonomous control system to observe, assess, and act on tasks in an efficient and prosperous manner.

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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.

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.

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.

Buildlean AI is a cloud-based construction management software that helps contractors manage their projects more efficiently. It provides a central platform for managing all aspects of a construction project, from planning and scheduling to tracking progress and managing finances. Buildlean AI uses artificial intelligence to automate many of the tasks that are typically done manually, such as scheduling and resource allocation. This can save contractors time and money, and it can also help to improve the accuracy and efficiency of their 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.

Deep Space AI is an innovative platform that revolutionizes the construction industry by providing intelligent solutions for design and construction workflows. The platform offers collaborative data management, actionable insights, and coordination tools to streamline construction processes and improve operational efficiency. Deep Space AI enhances transparency, boosts productivity, and empowers teams to make informed decisions throughout all project phases. Trusted by leading teams in the design and construction industry, Deep Space AI is a game-changer in the AECO sector.

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.

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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.

Reinforcement Learning from AI Feedback (RLAIF) is a concept that describes a type of machine learning approach where **an AI agent learns by receiving feedback or guidance from another AI system**. This concept is closely related to the field of Reinforcement Learning (RL), which is a type of machine learning where an agent learns to make a sequence of decisions in an environment to maximize a cumulative reward. In traditional RL, an agent interacts with an environment and receives feedback in the form of rewards or penalties based on the actions it takes. It learns to improve its decision-making over time to achieve its goals. In the context of Reinforcement Learning from AI Feedback, the AI agent still aims to learn optimal behavior through interactions, but **the feedback comes from another AI system rather than from the environment or human evaluators**. This can be **particularly useful in situations where it may be challenging to define clear reward functions or when it is more efficient to use another AI system to provide guidance**. The feedback from the AI system can take various forms, such as: - **Demonstrations** : The AI system provides demonstrations of desired behavior, and the learning agent tries to imitate these demonstrations. - **Comparison Data** : The AI system ranks or compares different actions taken by the learning agent, helping it to understand which actions are better or worse. - **Reward Shaping** : The AI system provides additional reward signals to guide the learning agent's behavior, supplementing the rewards from the environment. This approach is often used in scenarios where the RL agent needs to learn from **limited human or expert feedback or when the reward signal from the environment is sparse or unclear**. It can also be used to **accelerate the learning process and make RL more sample-efficient**. Reinforcement Learning from AI Feedback is an area of ongoing research and has applications in various domains, including robotics, autonomous vehicles, and game playing, among others.

Taiyi (太一) is a bilingual large language model fine-tuned for diverse biomedical tasks. It aims to facilitate communication between healthcare professionals and patients, provide medical information, and assist in diagnosis, biomedical knowledge discovery, drug development, and personalized healthcare solutions. The model is based on the Qwen-7B-base model and has been fine-tuned using rich bilingual instruction data. It covers tasks such as question answering, biomedical dialogue, medical report generation, biomedical information extraction, machine translation, title generation, text classification, and text semantic similarity. The project also provides standardized data formats, model training details, model inference guidelines, and overall performance metrics across various BioNLP tasks.

Step-DPO is a method for enhancing long-chain reasoning ability of LLMs with a data construction pipeline creating a high-quality dataset. It significantly improves performance on math and GSM8K tasks with minimal data and training steps. The tool fine-tunes pre-trained models like Qwen2-7B-Instruct with Step-DPO, achieving superior results compared to other models. It provides scripts for training, evaluation, and deployment, along with examples and acknowledgements.

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.

Lantern is an open-source PostgreSQL database extension designed to store vector data, generate embeddings, and handle vector search operations efficiently. It introduces a new index type called 'lantern_hnsw' for vector columns, which speeds up 'ORDER BY ... LIMIT' queries. Lantern utilizes the state-of-the-art HNSW implementation called usearch. Users can easily install Lantern using Docker, Homebrew, or precompiled binaries. The tool supports various distance functions, index construction parameters, and operator classes for efficient querying. Lantern offers features like embedding generation, interoperability with pgvector, parallel index creation, and external index graph generation. It aims to provide superior performance metrics compared to other similar tools and has a roadmap for future enhancements such as cloud-hosted version, hardware-accelerated distance metrics, industry-specific application templates, and support for version control and A/B testing of embeddings.

MMOS (Mix of Minimal Optimal Sets) is a dataset designed for math reasoning tasks, offering higher performance and lower construction costs. It includes various models and data subsets for tasks like arithmetic reasoning and math word problem solving. The dataset is used to identify minimal optimal sets through reasoning paths and statistical analysis, with a focus on QA-pairs generated from open-source datasets. MMOS also provides an auto problem generator for testing model robustness and scripts for training and inference.

LLMBox is a comprehensive library designed for implementing Large Language Models (LLMs) with a focus on a unified training pipeline and comprehensive model evaluation. It serves as a one-stop solution for training and utilizing LLMs, offering flexibility and efficiency in both training and utilization stages. The library supports diverse training strategies, comprehensive datasets, tokenizer vocabulary merging, data construction strategies, parameter efficient fine-tuning, and efficient training methods. For utilization, LLMBox provides comprehensive evaluation on various datasets, in-context learning strategies, chain-of-thought evaluation, evaluation methods, prefix caching for faster inference, support for specific LLM models like vLLM and Flash Attention, and quantization options. The tool is suitable for researchers and developers working with LLMs for natural language processing tasks.

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.

DB-GPT-Hub is an experimental project leveraging Large Language Models (LLMs) for Text-to-SQL parsing. It includes stages like data collection, preprocessing, model selection, construction, and fine-tuning of model weights. The project aims to enhance Text-to-SQL capabilities, reduce model training costs, and enable developers to contribute to improving Text-to-SQL accuracy. The ultimate goal is to achieve automated question-answering based on databases, allowing users to execute complex database queries using natural language descriptions. The project has successfully integrated multiple large models and established a comprehensive workflow for data processing, SFT model training, prediction output, and evaluation.

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.

A-MEM is a novel agentic memory system designed for Large Language Model (LLM) agents to dynamically organize memories in an agentic way. It introduces advanced memory organization capabilities, intelligent indexing, and linking of memories, comprehensive note generation, interconnected knowledge networks, continuous memory evolution, and agent-driven decision making for adaptive memory management. The system facilitates agent construction and enables dynamic memory operations and flexible agent-memory interactions.

SeaLLMs are a family of language models optimized for Southeast Asian (SEA) languages. They were pre-trained from Llama-2, on a tailored publicly-available dataset, which comprises texts in Vietnamese 🇻🇳, Indonesian 🇮🇩, Thai 🇹🇭, Malay 🇲🇾, Khmer🇰🇭, Lao🇱🇦, Tagalog🇵🇭 and Burmese🇲🇲. The SeaLLM-chat underwent supervised finetuning (SFT) and specialized self-preferencing DPO using a mix of public instruction data and a small number of queries used by SEA language native speakers in natural settings, which **adapt to the local cultural norms, customs, styles and laws in these areas**. SeaLLM-13b models exhibit superior performance across a wide spectrum of linguistic tasks and assistant-style instruction-following capabilities relative to comparable open-source models. Moreover, they outperform **ChatGPT-3.5** in non-Latin languages, such as Thai, Khmer, Lao, and Burmese.

Awesome-Segment-Anything is a powerful tool for segmenting and extracting information from various types of data. It provides a user-friendly interface to easily define segmentation rules and apply them to text, images, and other data formats. The tool supports both supervised and unsupervised segmentation methods, allowing users to customize the segmentation process based on their specific needs. With its versatile functionality and intuitive design, Awesome-Segment-Anything is ideal for data analysts, researchers, content creators, and anyone looking to efficiently extract valuable insights from complex datasets.

agentUniverse is a multi-agent framework based on large language models, providing flexible capabilities for building individual agents. It focuses on multi-agent collaborative patterns, integrating domain experience to help agents solve problems in various fields. The framework includes pattern components like PEER and DOE for event interpretation, industry analysis, and financial report generation. It offers features for agent construction, multi-agent collaboration, and domain expertise integration, aiming to create intelligent applications with professional know-how.

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

Your expert on NEXCO Nagayoshi project.

Expert in building trades, providing informative insights on construction.

Assists with construction labor information.

Tu guía interactiva en geotecnia y cimentaciones, con respuestas basadas en textos de referencia.

Your expert guide to the intricate world of Swiss architecture, blending sustainability with innovation.

Informative guide on asbestos hazards and removal

Futuristic construction AI with interplanetary and nano-robotics integration

Provides Construction Support relating to Planning Permission, Building Regulations, Party Wall Act and Fire Safety in the UK. Obtain instant Guidance for your Construction Project.

Construction machinery expert, developed on OpenAI

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

Empowering beginners with lean construction knowledge by "Amir Zavichi"

A construction materials calculator for various projects.

Assistant for creating a construction project delivery handbook.

Architecture and Construction Firms handle sensitive project data, client information, and architectural plans, necessitating strict data privacy measures.

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)

Your go-to assistant for construction bidding. Upload photos or documents and start estimating!

Provides guidance on construction projects

I read and interpret Lithuanian construction norms.

A construction safety expert providing OSHA-cited advice