Best AI tools for< Allocate Resources >

FYLD is a fieldwork execution platform powered by AI that revolutionizes the way work is done. It provides true visibility into fieldwork operations, enabling smarter and faster decision-making that impacts productivity, safety, sustainability, and revenue for organizations worldwide.

Likely.AI is an AI-powered platform designed for the real estate industry, offering innovative solutions to enhance database management, marketing content creation, and predictive analytics. The platform utilizes advanced AI models to predict likely sellers, update contact information, and trigger automated notifications, ensuring real estate professionals stay ahead of the competition. With features like contact enrichment, predictive modeling, 24/7 contact monitoring, and AI-driven marketing content generation, Likely.AI revolutionizes how real estate businesses operate and engage with their clients. The platform aims to streamline workflows, improve lead generation, and maximize ROI for users in the residential real estate sector.

Epicflow is an AI-based multi-project and resource management software designed to help organizations deliver more projects on time with available resources, increase profitability, and make informed project decisions using real-time data and predictive analytics. The software bridges demand and supply by matching talent based on competencies, experience, and availability. It offers features like AI assistant, What-If Analysis, Future Load Graph, Historical Load Graph, Task List, and Competence Management Pipeline. Epicflow is trusted by leading companies in various industries for high performance and flawless project delivery.

Connected-Stories is the next generation of Creative Management Platforms powered by AI. It is a cloud-based platform that helps creative teams to manage their projects, collaborate with each other, and track their progress. Connected-Stories uses AI to automate many of the tasks that are typically associated with creative management, such as scheduling, budgeting, and resource allocation. This allows creative teams to focus on their work and be more productive.

Mudder AI is a data-powered coordination platform designed for resilient emergency response. The platform offers intelligent solutions for faster community recovery by uniting data, optimizing disaster response, and empowering emergency management through integrated intelligence. It combines data integration and harmonization, real-time situational awareness, predictive analytics and modeling, intelligent resource allocation and deployment, collaborative decision support, and post-disaster assessment and recovery. Mudder AI provides a comprehensive suite of professional services for a diverse clientele, from homeowners to commercial developers, to enhance disaster management capabilities and ensure efficient resource allocation during emergencies.

Mosaic is a modern, automated, and AI-powered resource planning, management, and forecasting software designed to maximize profitability by providing a fast, easy, and visual way to plan resource allocation, assemble project teams, and understand workload capacity. It offers features such as AI team building, workload forecasting, headcount planning, and capacity planning. Mosaic helps organizations improve planning efficiency, drive profitability, and reduce burnout by visualizing workload, managing people together, and building project schedules around actual capacity. The software provides real-time reports, out-of-the-box reporting, and dashboard analytics for better decision-making. Mosaic is collaborative, intuitive, and automated, making complex processes visual and easy to use.

Fuel50 is an AI Talent Marketplace that offers personalized skill development paths and growth opportunities for employees. It leverages expert-driven skills ontology to align individual aspirations with organizational goals, enhance internal mobility, boost employee engagement, and increase retention. Fuel50 provides deep insights into workforce capabilities, enabling data-driven decisions for creating agile, resilient teams. The platform offers features like automated skill to role mapping, talent allocation, employee-driven career pathways, and holistic employee growth.

BrightBid is an AI-powered advertising optimization tool that helps users maximize the performance of their ad campaigns. By leveraging AI and automation, BrightBid enables users to make data-driven decisions, automate bids, find keywords, create ad copy, and allocate budgets easily. The tool provides intuitive dashboards for tracking ad performance, monitoring targets and metrics, controlling budget spend, and gaining competitive insights by tracking competitors. BrightBid aims to supercharge ads and boost ROI by utilizing AI technology to optimize advertising strategies and increase return on investment.

Flyte is an open-source orchestrator that facilitates building production-grade data and ML pipelines. It is built for scalability and reproducibility, leveraging Kubernetes as its underlying platform. With Flyte, user teams can construct pipelines using the Python SDK, and seamlessly deploy them on both cloud and on-premises environments, enabling distributed processing and efficient resource utilization.

AIShield Watchtower is a tool designed to fortify the security of AI/ML models and Jupyter notebooks by automating model and notebook discoveries, conducting vulnerability scans, and categorizing risks into 'low,' 'medium,' 'high,' and 'critical' levels. It supports scanning of public GitHub repositories, Hugging Face repositories, AWS S3 buckets, and local systems. The tool generates comprehensive reports, offers a user-friendly interface, and aligns with industry standards like OWASP, MITRE, and CWE. It aims to address the security blind spots surrounding Jupyter notebooks and AI models, providing organizations with a tailored approach to enhancing their security efforts.

Meta Lingua is a minimal and fast LLM training and inference library designed for research. It uses easy-to-modify PyTorch components to experiment with new architectures, losses, and data. The codebase enables end-to-end training, inference, and evaluation, providing tools for speed and stability analysis. The repository contains essential components in the 'lingua' folder and scripts that combine these components in the 'apps' folder. Researchers can modify the provided templates to suit their experiments easily. Meta Lingua aims to lower the barrier to entry for LLM research by offering a lightweight and focused codebase.

A fast, easy-to-use, open source AI constraint solver for software developers. OptaPlanner is a powerful tool that helps developers solve complex optimization problems by providing a constraint satisfaction solver. It allows users to model and solve planning and scheduling problems efficiently, improving decision-making processes and resource allocation. With OptaPlanner, developers can easily integrate optimization capabilities into their applications, leading to better performance and cost-effectiveness.

Timefold Solver is an optimization engine evolved from OptaPlanner. Developed by the original OptaPlanner team, our aim is to free the world of wasteful planning.

Backend.AI Web UI is a user-friendly web and app interface designed to make AI accessible for end-users, DevOps, and SysAdmins. It provides features for session management, inference service management, pipeline management, storage management, node management, statistics, configurations, license checking, plugins, help & manuals, kernel management, user management, keypair management, manager settings, proxy mode support, service information, and integration with the Backend.AI Web Server. The tool supports various devices, offers a built-in websocket proxy feature, and allows for versatile usage across different platforms. Users can easily manage resources, run environment-supported apps, access a web-based terminal, use Visual Studio Code editor, manage experiments, set up autoscaling, manage pipelines, handle storage, monitor nodes, view statistics, configure settings, and more.

Awesome-LLM-Quantization is a curated list of resources related to quantization techniques for Large Language Models (LLMs). Quantization is a crucial step in deploying LLMs on resource-constrained devices, such as mobile phones or edge devices, by reducing the model's size and computational requirements.

This repository contains a hand-curated list of great machine (deep) learning resources for Natural Language Processing (NLP) with a focus on Generative Pre-trained Transformer (GPT), Bidirectional Encoder Representations from Transformers (BERT), attention mechanism, Transformer architectures/networks, Chatbot, and transfer learning in NLP.

Azure OpenAI Service is a central capability with Azure API Management, providing guidance and tools for organizations to implement Azure OpenAI in a production environment with an emphasis on cost control, secure access, and usage monitoring. It includes infrastructure-as-code templates, CI/CD pipelines, secure access management, usage monitoring, load balancing, streaming requests, and end-to-end samples like ChatApp and Azure Dashboards.

This repository provides configuration and scripts for running Ollama LLM server on Apple Silicon Macs in headless mode, optimized for performance and resource usage. It includes features like automatic startup, system resource optimization, external network access, proper logging setup, and SSH-based remote management. Users can customize the Ollama service configuration and enable optional GPU memory optimization and Docker autostart for container applications. The installation process disables unnecessary system services, configures power management, and optimizes for background operation while maintaining Screen Sharing capability for remote management. Performance considerations focus on reducing memory usage, disabling GUI-related services, minimizing background processes, preventing sleep/hibernation, and optimizing for headless operation.

cuVS is a library that contains state-of-the-art implementations of several algorithms for running approximate nearest neighbors and clustering on the GPU. It can be used directly or through the various databases and other libraries that have integrated it. The primary goal of cuVS is to simplify the use of GPUs for vector similarity search and clustering.

RAFT (Reusable Accelerated Functions and Tools) is a C++ header-only template library with an optional shared library that contains fundamental widely-used algorithms and primitives for machine learning and information retrieval. The algorithms are CUDA-accelerated and form building blocks for more easily writing high performance applications.

TornadoVM is a plug-in to OpenJDK and GraalVM that allows programmers to automatically run Java programs on heterogeneous hardware. TornadoVM targets OpenCL, PTX and SPIR-V compatible devices which include multi-core CPUs, dedicated GPUs (Intel, NVIDIA, AMD), integrated GPUs (Intel HD Graphics and ARM Mali), and FPGAs (Intel and Xilinx).

Swarms provides simple, reliable, and agile tools to create your own Swarm tailored to your specific needs. Currently, Swarms is being used in production by RBC, John Deere, and many AI startups.

Simple-OpenAI is a Java library that provides a simple way to interact with the OpenAI API. It offers consistent interfaces for various OpenAI services like Audio, Chat Completion, Image Generation, and more. The library uses CleverClient for HTTP communication, Jackson for JSON parsing, and Lombok to reduce boilerplate code. It supports asynchronous requests and provides methods for synchronous calls as well. Users can easily create objects to communicate with the OpenAI API and perform tasks like text-to-speech, transcription, image generation, and chat completions.

Kobold-Assistant is a fully offline voice assistant interface to KoboldAI's large language model API. It can work online with the KoboldAI horde and online speech-to-text and text-to-speech models. The assistant, called Jenny by default, uses the latest coqui 'jenny' text to speech model and openAI's whisper speech recognition. Users can customize the assistant name, speech-to-text model, text-to-speech model, and prompts through configuration. The tool requires system packages like GCC, portaudio development libraries, and ffmpeg, along with Python >=3.7, <3.11, and runs on Ubuntu/Debian systems. Users can interact with the assistant through commands like 'serve' and 'list-mics'.

HAMi is a Heterogeneous AI Computing Virtualization Middleware designed to manage Heterogeneous AI Computing Devices in a Kubernetes cluster. It allows for device sharing, device memory control, device type specification, and device UUID specification. The tool is easy to use and does not require modifying task YAML files. It includes features like hard limits on device memory, partial device allocation, streaming multiprocessor limits, and core usage specification. HAMi consists of components like a mutating webhook, scheduler extender, device plugins, and in-container virtualization techniques. It is suitable for scenarios requiring device sharing, specific device memory allocation, GPU balancing, low utilization optimization, and scenarios needing multiple small GPUs. The tool requires prerequisites like NVIDIA drivers, CUDA version, nvidia-docker, Kubernetes version, glibc version, and helm. Users can install, upgrade, and uninstall HAMi, submit tasks, and monitor cluster information. The tool's roadmap includes supporting additional AI computing devices, video codec processing, and Multi-Instance GPUs (MIG).

Coordinates project timelines ensuring efficient workflow and productivity.

Agile assistant for story points estimation.

Guides budget planning and control within projects.

Structured process for prioritizing marketing tasks based on strategic alignment. Outputs in Eisenhower, RACI and other methodologies.

Optimizes project resources to ensure efficient delivery.