Best AI tools for< Reduce Workload >

TeacherMatic is the ultimate AI platform designed for educators to reduce workload and elevate teaching and learning. It offers over 70 AI-assisted generators to create high-quality resources for the classroom, including lesson plans, activities, worksheets, and more. The platform was developed with input from over 300 teachers to ensure it meets the needs of educators, making it one of the best AI tools available for teachers.

Watermelon is an AI customer service tool that integrates with OpenAI's latest model, GPT-4o. It allows users to build chatbots powered by GPT-4o to automate customer interactions, handle frequently asked questions, and collaborate seamlessly between chatbots and human agents. Watermelon offers features such as chatbot building, customizable chat widgets, statistics tracking, inbox collaboration, and various integrations with APIs and webhooks. The application caters to industries like e-commerce, education, healthcare, and financial services, providing solutions for sales support, lead generation, marketing, HR, and customer service.

Watermelon is an AI customer service tool that helps businesses automate up to 96% of their support questions. With Watermelon, businesses can build GPT-4 chatbots that are trained on their own data, no coding required. Watermelon's chatbots can speak any language and pull precise answers from various sources like documents, websites, and databases. In addition to chatbots, Watermelon also offers a range of other features to help businesses improve their customer service, such as a chat widget, inbox, and analytics.

ASKTOWEB is an AI-powered service that enhances websites by adding AI search buttons to SaaS landing pages, software documentation pages, and other websites. It allows visitors to easily search for information without needing specific keywords, making websites more user-friendly and useful. ASKTOWEB analyzes user questions to improve site content and discover customer needs. The service offers multi-model accuracy verification, direct reference jump links, multilingual chatbot support, effortless attachment with a single line of script, and a simple UI without annoying pop-ups. ASKTOWEB reduces the burden on customer support by acting as a buffer for inquiries about available information on the website.

Abridge is an enterprise-grade AI platform for clinical conversations, transforming patient-clinician interactions into structured clinical notes in real-time. It is trusted by leading healthcare systems and offers auditable AI infrastructure. The platform aims to improve clinician efficiency, patient care, and overall healthcare outcomes through advanced AI technology.

Knowbo is a custom chatbot tool that allows users to create a chatbot for their website in just 2 minutes. The chatbot learns directly from the website or documentation, providing up-to-date information to users. With features like easy deployment, chat history tracking, and customization options, Knowbo aims to revolutionize customer experience by reducing the load on support teams and offering a seamless way for users to get their questions answered quickly.

Qventus is an AI-powered platform that simplifies healthcare operations by utilizing AI, machine learning, and behavioral science to automate processes, predict bottlenecks, and optimize care flows. It offers solutions for surgical growth, inpatient capacity management, and perioperative care coordination. Qventus empowers care teams to operate at the top of their license, improve patient outcomes, and enhance operational efficiency in healthcare settings.

BetterMedicine is an AI software designed for cancer diagnostics and detection. It offers AI-powered solutions to enhance patient outcomes and drive efficiency in radiology workflows. The software is expertly designed by medical professionals and AI specialists, providing trusted and clinically validated solutions. BetterMedicine aims to address inefficiencies in radiology by integrating AI-powered software for detecting lesions on CT scans seamlessly into the workflow, thereby improving efficiency and reducing the risk of oversight. The application focuses on improving patient outcomes, reducing errors, and enhancing the wellbeing of radiology professionals.

SpamSpy is a community-powered AI platform designed to combat spam and malicious content online. It offers a range of pricing plans to suit different needs, from free options to enterprise solutions. The platform leverages supervised and unsupervised algorithms for accurate assessment of relevance, and personalized reinforcement models to enhance response quality. SpamSpy encourages community involvement and contributions to improve its spam detection capabilities.

Sendient.ai is an AI application that offers AI solutions and services, specifically tailored for the education and assessment sectors. The platform leverages cutting-edge Artificial Intelligence to automate grading, streamline administrative tasks, and provide personalized learning experiences. Sendient aims to transform education and assessment by delivering unparalleled solutions that drive innovation and efficiency in teaching and learning processes.

Business Automated is an independent automation consultancy that offers custom automation solutions for businesses. They provide services to streamline processes, increase efficiency, and reduce manual workloads. The company specializes in integrating AI technologies like GPT3.5, GPT4, and ChatGPT with platforms such as Airtable, Google Sheets, and Webflow. Through their products and services, Business Automated aims to empower businesses to leverage automation for improved productivity and performance.

Aidemia is an ultimate teaching workflow toolkit that simplifies teaching using the power of 30 AI engines. It helps teachers from 48201 schools and institutions replace other AI tools. With Aidemia, teachers can reduce their workload by 90 minutes a day. It offers various features such as lesson plans, creative ideas, workflow automation, advice, quiz creator, restyling, homework, presentations, discussions, essay grading, stories, parent meetings, rewriting, plagiarism check, and more. Aidemia is used by leading teachers and institutions in 74 countries with a 96% teacher satisfaction rate.

Flavor is an AI-powered accounting automation tool that revolutionizes the month-end close process. It automates tasks such as book closure management, general ledger reconciliations, consolidation & reporting, financial analysis, and accruals management. Flavor combines AI technology with human validation to ensure accurate, compliant, and audit-ready financial records. The tool offers customizable checklists, real-time insights, and dynamic reports for faster decision-making. With Flavor, users can reduce manual workload, eliminate errors, and focus on strategic growth initiatives.

Stundenheld.com is an AI tool designed for small and medium-sized businesses to automate daily tasks using artificial intelligence. It allows users to create and utilize their own AI tools easily, enhancing productivity and efficiency in the workplace. The platform offers features such as converting business language into colloquial language, translating from German to any language, generating personalized email responses, and more. By automating repetitive tasks, Stundenheld.com helps teams save time and reduce administrative workload.

VEGA AI is an AI-powered virtual entity designed for guidance and assistance in the field of education. It offers an AI-first learning platform that allows users to effortlessly create personalized courses, gain learning insights, and support students with the help of an AI avatar. Trusted by leading institutions worldwide, VEGA AI helps educators deploy adaptive learning environments, build personalized learning paths, and provide 24/7 AI avatar support. The platform aims to transform teaching by automating workflows, reducing workload, and boosting student outcomes through AI automation and personalized learning journeys.

Lacework is a cloud security platform that provides comprehensive security solutions for DevOps, Containers, and Cloud Environments. It offers features such as Code Security, Workload Protection, Identities and Entitlements management, Posture Management, Kubernetes Security, Data Posture Management, Infrastructure as Code security, Software Composition Analysis, Application Security Testing, Edge Security, and Platform Overview. Lacework empowers users to secure their entire cloud infrastructure, prioritize risks, protect workloads, and stay compliant by leveraging AI-driven technologies and behavior-based threat detection. The platform helps automate compliance reporting, fix vulnerabilities, and reduce alerts, ultimately enhancing cloud security and operational efficiency.

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.

InsightPro is a workforce analytics platform specifically designed for healthcare payers. It integrates claims processing, quality assurance, training, and contact center functionalities, all powered by AI and machine learning. The platform offers capabilities such as dashboards, team productivity, workforce optimization, workload management, workforce access, real-time monitoring, and training management. InsightPro aims to improve operational efficiencies, reduce costs, enhance workforce planning, and foster team collaboration within payer organizations.

GPUX is a cloud platform that provides access to GPUs for running AI workloads. It offers a variety of features to make it easy to deploy and run AI models, including a user-friendly interface, pre-built templates, and support for a variety of programming languages. GPUX is also committed to providing a sustainable and ethical platform, and it has partnered with organizations such as the Climate Leadership Council to reduce its carbon footprint.

Deflekt.ai is an AI-powered application designed to automate replies on all support channels. It helps businesses deflect customer and coworker support tickets by answering questions automatically. The tool can be integrated with various channels like web chat, email, Slack, and Teams, making it a versatile solution for support teams. Deflekt.ai allows users to customize content, localize responses, and provide human support when needed. With features like document hosting, channel activation, and conversation monitoring, Deflekt.ai streamlines support processes and reduces workload.

AnnA is a Python script designed to create filtered decks in optimal review order for Anki flashcards. It uses Machine Learning / AI to ensure semantically linked cards are reviewed far apart. The script helps users manage their daily reviews by creating special filtered decks that prioritize reviewing cards that are most different from the rest. It also allows users to reduce the number of daily reviews while increasing retention and automatically identifies semantic neighbors for each note.

AutoPilot Observability (APO) is an out-of-the-box observability platform that provides one-click installation and ready-to-use capabilities. APO's OneAgent supports one-click configuration-free installation of Tracing probes, collects application fault scene logs, infrastructure metrics, network metrics of applications and downstream dependencies, and Kubernetes events. It supports collecting causality metrics based on eBPF implementation. APO integrates OpenTelemetry probes, otel-collector, Jaeger, ClickHouse, and VictoriaMetrics, reducing user configuration work. APO innovatively integrates eBPF technology with the OpenTelemetry ecosystem, significantly reducing data storage volume. It offers guided troubleshooting using eBPF technology to assist users in pinpointing fault causes on a single page.

This repository contains an implementation of Ring Attention, a technique for processing large sequences in transformers. Ring Attention splits the data across the sequence dimension and applies ring reduce to the processing of the tiles of the attention matrix, similar to flash attention. It also includes support for Striped Attention, a follow-up paper that permutes the sequence for better workload balancing for autoregressive transformers, and grouped query attention, which saves on communication costs during the ring reduce. The repository includes a CUDA version of the flash attention kernel, which is used for the forward and backward passes of the ring attention. It also includes logic for splitting the sequence evenly among ranks, either within the attention function or in the external ring transformer wrapper, and basic test cases with two processes to check for equivalent output and gradients.

KIVI is a plug-and-play 2bit KV cache quantization algorithm optimizing memory usage by quantizing key cache per-channel and value cache per-token to 2bit. It enables LLMs to maintain quality while reducing memory usage, allowing larger batch sizes and increasing throughput in real LLM inference workloads.

Evedel is an Emacs package designed to streamline the interaction with LLMs during programming. It aims to reduce manual code writing by creating detailed instruction annotations in the source files for LLM models. The tool leverages overlays to track instructions, categorize references with tags, and provide a seamless workflow for managing and processing directives. Evedel offers features like saving instruction overlays, complex query expressions for directives, and easy navigation through instruction overlays across all buffers. It is versatile and can be used in various types of buffers beyond just programming buffers.

Distributed Llama is a tool that allows you to run large language models (LLMs) on weak devices or make powerful devices even more powerful by distributing the workload and dividing the RAM usage. It uses TCP sockets to synchronize the state of the neural network, and you can easily configure your AI cluster by using a home router. Distributed Llama supports models such as Llama 2 (7B, 13B, 70B) chat and non-chat versions, Llama 3, and Grok-1 (314B).

This repository documents how to optimize common algorithms based on CUDA. It includes subdirectories with code implementations for specific optimizations. The optimizations cover topics such as compiling PyTorch from source, NVIDIA's reduce optimization, OneFlow's elementwise template, fast atomic add for half data types, upsample nearest2d optimization in OneFlow, optimized indexing in PyTorch, OneFlow's softmax kernel, linear attention optimization, and more. The repository also includes learning resources related to deep learning frameworks, compilers, and optimization techniques.

ReaLHF is a distributed system designed for efficient RLHF training with Large Language Models (LLMs). It introduces a novel approach called parameter reallocation to dynamically redistribute LLM parameters across the cluster, optimizing allocations and parallelism for each computation workload. ReaL minimizes redundant communication while maximizing GPU utilization, achieving significantly higher Proximal Policy Optimization (PPO) training throughput compared to other systems. It supports large-scale training with various parallelism strategies and enables memory-efficient training with parameter and optimizer offloading. The system seamlessly integrates with HuggingFace checkpoints and inference frameworks, allowing for easy launching of local or distributed experiments. ReaLHF offers flexibility through versatile configuration customization and supports various RLHF algorithms, including DPO, PPO, RAFT, and more, while allowing the addition of custom algorithms for high efficiency.

Lance is a modern columnar data format optimized for ML workflows and datasets. It offers high-performance random access, vector search, zero-copy automatic versioning, and ecosystem integrations with Apache Arrow, Pandas, Polars, and DuckDB. Lance is designed to address the challenges of the ML development cycle, providing a unified data format for collection, exploration, analytics, feature engineering, training, evaluation, deployment, and monitoring. It aims to reduce data silos and streamline the ML development process.

ClearML Fractional GPU is a tool designed to optimize GPU resource utilization by allowing multiple containers to run on the same GPU with driver-level memory limitation and compute time-slicing. It supports CUDA 11.x & CUDA 12.x, preventing greedy processes from grabbing the entire GPU memory. The tool offers options like Dynamic GPU Slicing, Container-based Memory Limits, and Kubernetes-based Static MIG Slicing to enhance hardware utilization and workload performance for AI development.

LARS is an application that enables users to run Large Language Models (LLMs) locally on their devices, upload their own documents, and engage in conversations where the LLM grounds its responses with the uploaded content. The application focuses on Retrieval Augmented Generation (RAG) to increase accuracy and reduce AI-generated inaccuracies. LARS provides advanced citations, supports various file formats, allows follow-up questions, provides full chat history, and offers customization options for LLM settings. Users can force enable or disable RAG, change system prompts, and tweak advanced LLM settings. The application also supports GPU-accelerated inferencing, multiple embedding models, and text extraction methods. LARS is open-source and aims to be the ultimate RAG-centric LLM application.

Mosec is a high-performance and flexible model serving framework for building ML model-enabled backend and microservices. It bridges the gap between any machine learning models you just trained and the efficient online service API. * **Highly performant** : web layer and task coordination built with Rust 🦀, which offers blazing speed in addition to efficient CPU utilization powered by async I/O * **Ease of use** : user interface purely in Python 🐍, by which users can serve their models in an ML framework-agnostic manner using the same code as they do for offline testing * **Dynamic batching** : aggregate requests from different users for batched inference and distribute results back * **Pipelined stages** : spawn multiple processes for pipelined stages to handle CPU/GPU/IO mixed workloads * **Cloud friendly** : designed to run in the cloud, with the model warmup, graceful shutdown, and Prometheus monitoring metrics, easily managed by Kubernetes or any container orchestration systems * **Do one thing well** : focus on the online serving part, users can pay attention to the model optimization and business logic

T-MAC is a kernel library that directly supports mixed-precision matrix multiplication without the need for dequantization by utilizing lookup tables. It aims to boost low-bit LLM inference on CPUs by offering support for various low-bit models. T-MAC achieves significant speedup compared to SOTA CPU low-bit framework (llama.cpp) and can even perform well on lower-end devices like Raspberry Pi 5. The tool demonstrates superior performance over existing low-bit GEMM kernels on CPU, reduces power consumption, and provides energy savings. It achieves comparable performance to CUDA GPU on certain tasks while delivering considerable power and energy savings. T-MAC's method involves using lookup tables to support mpGEMM and employs key techniques like precomputing partial sums, shift and accumulate operations, and utilizing tbl/pshuf instructions for fast table lookup.

Liger Kernel is a collection of Triton kernels designed for LLM training, increasing training throughput by 20% and reducing memory usage by 60%. It includes Hugging Face Compatible modules like RMSNorm, RoPE, SwiGLU, CrossEntropy, and FusedLinearCrossEntropy. The tool works with Flash Attention, PyTorch FSDP, and Microsoft DeepSpeed, aiming to enhance model efficiency and performance for researchers, ML practitioners, and curious novices.

AIBrix is an open-source initiative providing essential building blocks for scalable GenAI inference infrastructure. It delivers a cloud-native solution optimized for deploying, managing, and scaling large language model (LLM) inference, tailored to enterprise needs. Key features include High-Density LoRA Management, LLM Gateway and Routing, LLM App-Tailored Autoscaler, Unified AI Runtime, Distributed Inference, Distributed KV Cache, Cost-efficient Heterogeneous Serving, and GPU Hardware Failure Detection.

LitData is a tool designed for blazingly fast, distributed streaming of training data from any cloud storage. It allows users to transform and optimize data in cloud storage environments efficiently and intuitively, supporting various data types like images, text, video, audio, geo-spatial, and multimodal data. LitData integrates smoothly with frameworks such as LitGPT and PyTorch, enabling seamless streaming of data to multiple machines. Key features include multi-GPU/multi-node support, easy data mixing, pause & resume functionality, support for profiling, memory footprint reduction, cache size configuration, and on-prem optimizations. The tool also provides benchmarks for measuring streaming speed and conversion efficiency, along with runnable templates for different data types. LitData enables infinite cloud data processing by utilizing the Lightning.ai platform to scale data processing with optimized machines.

Awesome European Tech is an up-to-date list of recommended European projects and companies curated by the community to support and strengthen the European tech ecosystem. It focuses on privacy and sustainability, showcasing companies that adhere to GDPR compliance and sustainability standards. The project aims to highlight and support European startups and projects excelling in privacy, sustainability, and innovation to contribute to a more diverse, resilient, and interconnected global tech landscape.

Call Center AI is an AI-powered call center solution leveraging Azure and OpenAI GPT. It allows for AI agent-initiated phone calls or direct calls to the bot from a configured phone number. The bot is customizable for various industries like insurance, IT support, and customer service, with features such as accessing claim information, conversation history, language change, SMS sending, and more. The project is a proof of concept showcasing the integration of Azure Communication Services, Azure Cognitive Services, and Azure OpenAI for an automated call center solution.

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