Best AI tools for< Scale Processes >

No Code Camp is an AI tool that offers a live, 5-week cohort-based course to turn strategy and operations people into automation experts with AI and No Code. The platform enables non-technical individuals to build applications, automate workflows, and develop web platforms using graphical interfaces, AI, and tool configuration instead of writing code. No Code Camp democratizes software development, making it accessible to a broader audience, speeding up the development process, and reducing the reliance on specialized software development skills. The course covers essential topics such as Data Architecture, Interface Design, AI Scaling, and No Code Automation, equipping participants with the skills needed to automate business processes and build internal tools.

Allchemy is a resource-aware AI platform for drug discovery. It combines state-of-the-art computational synthesis with AI algorithms to predict molecular properties. Within minutes, Allchemy creates thousands of synthesizable lead candidates meeting user-defined profiles of drug-likeness, affinity towards specific proteins, toxicity, and a range of other physical-chemical measures. Allchemy encompasses the entire resource-to-drug design process and has been used in academic, corporate and classified environments worldwide to: Design synthesizable leads targeting specific proteins Evolve scaffolds similar to desired drugs Design “circular” drug syntheses from renewable materials Interface with and instruct automated synthesis platforms and optimize pilot-scale processes Operate “iterative synthesis” schemes Predict side reactions and create forensic “synthetic signatures” of hazardous/toxic molecules Design synthetic degradation and recovery cycles for various types of feedstocks and functional target molecules

HeyMilo AI is a generative AI-powered voice agent application designed to help companies and recruiting agencies scale their interview processes. It offers AI-powered voice agents capable of conducting two-way conversational interviews, providing real-time candidate insights, and seamless integration with existing recruiting tools. HeyMilo aims to make interviewing easier, faster, and more effective by creating and sharing agents, inviting candidates for interviews, and analyzing interviews to provide comprehensive candidate reports.

Dhisana AI is an AI-powered platform that offers AI Assistants to automate and scale essential roles across organizations, including marketing, sales, customer support, and operations. It enables users to automate tasks, boost productivity, simplify booking processes, collaborate efficiently, and organize and track information effortlessly. The platform provides efficient assistance, personalized customer interactions, and smart solutions to enhance business operations and drive growth.

Voximplant is a cloud communications platform that provides a range of tools and services for businesses to build and scale their communications solutions. The platform includes a variety of features such as voice, video, messaging, natural language processing, and SIP trunking. Voximplant also offers a no-code drag-and-drop contact center solution called Voximplant Kit, which is designed to help businesses improve customer experience and automate processes. Voximplant is used by millions of users worldwide and is trusted by companies such as Airbnb, Uber, and Salesforce.

Clay is a sales automation tool that helps businesses scale their outbound campaigns. It combines data from over 50 sources, web scraping, and AI messaging to enrich data and automate outbound processes. With Clay, businesses can build lead lists, enrich data, write personalized emails, and automate inbound leads. It offers a 14-day free trial and integrates with various tools and CRMs.

Clay is an AI-powered data enrichment and outreach automation tool designed to help go-to-market teams scale personalized outbound campaigns. It combines 75+ data enrichment tools, AI capabilities, and automation features to streamline lead generation, data cleaning, and personalized messaging. With access to 50+ data providers, Clay offers comprehensive coverage of information and enables users to connect, enrich, and sync their CRM data effortlessly. The platform also features AI web scraping, personalized email building, automated inbound and outbound processes, and data formatting functionalities.

Infobip is a leading provider of omnichannel communications solutions, enabling businesses to connect with their customers through a variety of channels, including SMS, RCS, MMS, WhatsApp, Viber, and more. Infobip's platform is used by over 70,000 businesses worldwide, and it processes over 450 billion interactions per year. Infobip's solutions are designed to help businesses improve customer engagement, increase sales, and reduce costs.

IBM offers artificial intelligence solutions designed to help businesses leverage AI technologies for increased productivity and efficiency. Their adaptive AI solutions are tailored to solve real business problems, providing choice, flexibility, transparency, and trust. IBM's AI offerings include watsonx platform, Granite models, AI consulting services, and hybrid cloud solutions, enabling businesses to scale AI across various functions. From automation to decision-making, IBM's AI capabilities can optimize processes, drive insights, and accelerate value creation, enhancing competitive advantage across industries like finance, healthcare, and government.

The GTM AI Product Platform is an advanced AI tool designed to future-proof businesses by providing AI Marketing OS and AI Sales OS solutions. It offers an all-in-one marketing solution and an end-to-end sales solution, empowering users to scale campaigns and crush quotas. The platform includes features like competitor analysis, content creation, ad copy generation, press release generation, and LinkedIn profile insights. With a focus on automating workflows and generating high-quality outputs, the GTM AI Platform aims to streamline sales and marketing processes for businesses of all sizes.

Ultimate is a customer support automation platform powered by Generative AI. It offers AI-powered chat automation and ticket automation solutions for various industries such as Ecommerce, Financial Services, Travel, Telecommunications, and Healthtech. UltimateGPT is a bot that integrates with help centers to build bots in minutes. The platform provides backend integrations, analytics, and insights to enhance customer support processes and drive business growth.

Beam AI is a leading platform for Agentic Automation and AI Agents, offering solutions for automating manual workflows with AI agents to boost productivity. The platform is used by Fortune 500 companies and scale-ups, providing a seamless experience from start to finish. With features like pre-trained agents, integrations, and easy-to-navigate UI, Beam AI empowers users to create and deploy AI tools tailored to their specific needs. The platform is designed to scale any business, offering industry-specific solutions and world-class support for building AI-native organizations.

ORO is a GenAI procurement orchestration platform that simplifies procurement processes from request to payment by providing AI-driven guidance. It optimizes supplier onboarding, risk identification, and compliance management. ORO aims to enhance user experience, scale compliance, and adapt to changing laws and business strategies with its no-code platform. The platform offers features such as intake management, supplier onboarding, risk & compliance automation, resource center, and news updates.

EthonAI is a Manufacturing Analytics System that offers a suite of software tools to achieve operational excellence at scale in manufacturing industries. The system provides real-time insights to improve product quality and process efficiency by analyzing production data from various sources. EthonAI helps in root cause analysis, defect detection, process monitoring, product tracking, and material flow analysis, ultimately redefining operational excellence in manufacturing.

Spiral is an AI-powered tool designed to automate 80% of repeat writing, thinking, and creative tasks. It allows users to create Spirals to accelerate any writing task by training it on examples to generate outputs in their desired voice and style. The tool includes a powerful Prompt Builder to help users work faster and smarter, transforming content into tweets, PRDs, proposals, summaries, and more. Spiral extracts patterns from text to deduce voice and style, enabling users to iterate on outputs until satisfied. Users can share Spirals with their team to maximize quality and streamline processes.

Holly is an AI tool designed for recruitment and staffing agencies to streamline their hiring processes. It automates candidate sourcing, engagement, and relationship-building, providing unprecedented insights and workflow automation features to help agencies make more placements per recruiter and expand their talent pool effortlessly.

Lavo Life Sciences is an AI-accelerated crystal structure prediction application that aims to accelerate drug development processes. The platform provides solutions for de-risking pipelines, optimizing solid-state formulations, and avoiding late-stage surprises using AI technology. Lavo Life Sciences combines the expertise of chemists and engineers in AI and computational chemistry to offer innovative solutions for drug development teams.

unSkript is an AI-powered infrastructure health intelligence tool designed to ensure the health of your application infrastructure. It uses Generative AI and Intelligent Health Checks to proactively find, diagnose, and fix issues in your application infrastructure. With features like Proactive Health Checks, Generative AI based RCA, and Continuous Learning, unSkript helps streamline processes for cloud-operations teams and software teams. By leveraging AI technology, unSkript aims to minimize downtime, deliver real-time troubleshooting, and allow users to focus on strategic tasks.

The website is a B2B research AI agent that automates manual B2B research processes by curating, refining, and enriching lead databases with AI agents. It offers features like source, curate, aggregate data points, templates, and custom AI-powered enrichment. The application helps users gather the right data, speed up research processes, and target relevant companies. It provides a range of pricing plans, compliance with ISO 9001, and a mobile application. The AI agent is used by companies like UBS, Microsoft, and Airbnb, and utilizes technologies like MongoDB, Flutter, and Next.js.

The website is a comprehensive AI-powered automation and AI toolkit designed for social marketers and networkers. It offers a wide range of features to streamline social selling and networking processes, automate daily actions, reach more customers, and manage business growth effectively. The platform provides tools for content creation, list building, social media management, email marketing, automations, workflows, and more. With a focus on scalability and user-friendliness, Social Connector aims to empower marketers at every stage of their journey with AI-generated content, unlimited forms, and list building tools.

Awesome Large Weather Models (LWMs) is a curated collection of articles and resources related to large weather models used in AI for Earth and AI for Science. It includes information on various cutting-edge weather forecasting models, benchmark datasets, and research papers. The repository serves as a hub for researchers and enthusiasts to explore the latest advancements in weather modeling and forecasting.

This is the official repository for 'Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with Nothing'. Magpie is a tool designed to synthesize high-quality instruction data at scale by extracting it directly from an aligned Large Language Models (LLMs). It aims to democratize AI by generating large-scale alignment data and enhancing the transparency of model alignment processes. Magpie has been tested on various model families and can be used to fine-tune models for improved performance on alignment benchmarks such as AlpacaEval, ArenaHard, and WildBench.

Sophia is an open-source TypeScript platform designed for autonomous AI agents and LLM based workflows. It aims to automate processes, review code, assist with refactorings, and support various integrations. The platform offers features like advanced autonomous agents, reasoning/planning inspired by Google's Self-Discover paper, memory and function call history, adaptive iterative planning, and more. Sophia supports multiple LLMs/services, CLI and web interface, human-in-the-loop interactions, flexible deployment options, observability with OpenTelemetry tracing, and specific agents for code editing, software engineering, and code review. It provides a flexible platform for the TypeScript community to expand and support various use cases and integrations.

Nous is an open-source TypeScript platform for autonomous AI agents and LLM based workflows. It aims to automate processes, support requests, review code, assist with refactorings, and more. The platform supports various integrations, multiple LLMs/services, CLI and web interface, human-in-the-loop interactions, flexible deployment options, observability with OpenTelemetry tracing, and specific agents for code editing, software engineering, and code review. It offers advanced features like reasoning/planning, memory and function call history, hierarchical task decomposition, and control-loop function calling options. Nous is designed to be a flexible platform for the TypeScript community to expand and support different use cases and integrations.

LLM-on-Ray is a comprehensive solution for building, customizing, and deploying Large Language Models (LLMs). It simplifies complex processes into manageable steps by leveraging the power of Ray for distributed computing. The tool supports pretraining, finetuning, and serving LLMs across various hardware setups, incorporating industry and Intel optimizations for performance. It offers modular workflows with intuitive configurations, robust fault tolerance, and scalability. Additionally, it provides an Interactive Web UI for enhanced usability, including a chatbot application for testing and refining models.

CAMEL is an open-source library designed for the study of autonomous and communicative agents. We believe that studying these agents on a large scale offers valuable insights into their behaviors, capabilities, and potential risks. To facilitate research in this field, we implement and support various types of agents, tasks, prompts, models, and simulated environments.

Ray is a unified framework for scaling AI and Python applications. It consists of a core distributed runtime and a set of AI libraries for simplifying ML compute, including Data, Train, Tune, RLlib, and Serve. Ray runs on any machine, cluster, cloud provider, and Kubernetes, and features a growing ecosystem of community integrations. With Ray, you can seamlessly scale the same code from a laptop to a cluster, making it easy to meet the compute-intensive demands of modern ML workloads.

Infinity is an AI-native database designed for LLM applications, providing incredibly fast full-text and vector search capabilities. It supports a wide range of data types, including vectors, full-text, and structured data, and offers a fused search feature that combines multiple embeddings and full text. Infinity is easy to use, with an intuitive Python API and a single-binary architecture that simplifies deployment. It achieves high performance, with 0.1 milliseconds query latency on million-scale vector datasets and up to 15K QPS.

Pai-Megatron-Patch is a deep learning training toolkit built for developers to train and predict LLMs & VLMs by using Megatron framework easily. With the continuous development of LLMs, the model structure and scale are rapidly evolving. Although these models can be conveniently manufactured using Transformers or DeepSpeed training framework, the training efficiency is comparably low. This phenomenon becomes even severer when the model scale exceeds 10 billion. The primary objective of Pai-Megatron-Patch is to effectively utilize the computational power of GPUs for LLM. This tool allows convenient training of commonly used LLM with all the accelerating techniques provided by Megatron-LM.

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.

The Data Scientist Roadmap2024 provides a comprehensive guide to mastering essential tools for data science success. It includes programming languages, machine learning libraries, cloud platforms, and concepts categorized by difficulty. The roadmap covers a wide range of topics from programming languages to machine learning techniques, data visualization tools, and DevOps/MLOps tools. It also includes web development frameworks and specific concepts like supervised and unsupervised learning, NLP, deep learning, reinforcement learning, and statistics. Additionally, it delves into DevOps tools like Airflow and MLFlow, data visualization tools like Tableau and Matplotlib, and other topics such as ETL processes, optimization algorithms, and financial modeling.

LazyLLM is a low-code development tool for building complex AI applications with multiple agents. It assists developers in building AI applications at a low cost and continuously optimizing their performance. The tool provides a convenient workflow for application development and offers standard processes and tools for various stages of application development. Users can quickly prototype applications with LazyLLM, analyze bad cases with scenario task data, and iteratively optimize key components to enhance the overall application performance. LazyLLM aims to simplify the AI application development process and provide flexibility for both beginners and experts to create high-quality applications.

This repository contains a comprehensive collection of 63 must-know Large Language Models (LLMs) interview questions. It covers topics such as the architecture of LLMs, transformer models, attention mechanisms, training processes, encoder-decoder frameworks, differences between LLMs and traditional statistical language models, handling context and long-term dependencies, transformers for parallelization, applications of LLMs, sentiment analysis, language translation, conversation AI, chatbots, and more. The readme provides detailed explanations, code examples, and insights into utilizing LLMs for various tasks.

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.

rLLM (relationLLM) is a Pytorch library for Relational Table Learning (RTL) with LLMs. It breaks down state-of-the-art GNNs, LLMs, and TNNs as standardized modules and facilitates novel model building in a 'combine, align, and co-train' way using these modules. The library is LLM-friendly, processes various graphs as multiple tables linked by foreign keys, introduces new relational table datasets, and is supported by students and teachers from Shanghai Jiao Tong University and Tsinghua University.

OpenAdapt is an open-source software adapter between Large Multimodal Models (LMMs) and traditional desktop and web Graphical User Interfaces (GUIs). It aims to automate repetitive GUI workflows by leveraging the power of LMMs. OpenAdapt records user input and screenshots, converts them into tokenized format, and generates synthetic input via transformer model completions. It also analyzes recordings to generate task trees and replay synthetic input to complete tasks. OpenAdapt is model agnostic and generates prompts automatically by learning from human demonstration, ensuring that agents are grounded in existing processes and mitigating hallucinations. It works with all types of desktop GUIs, including virtualized and web, and is open source under the MIT license.

llm-swarm is a tool designed to manage scalable open LLM inference endpoints in Slurm clusters. It allows users to generate synthetic datasets for pretraining or fine-tuning using local LLMs or Inference Endpoints on the Hugging Face Hub. The tool integrates with huggingface/text-generation-inference and vLLM to generate text at scale. It manages inference endpoint lifetime by automatically spinning up instances via `sbatch`, checking if they are created or connected, performing the generation job, and auto-terminating the inference endpoints to prevent idling. Additionally, it provides load balancing between multiple endpoints using a simple nginx docker for scalability. Users can create slurm files based on default configurations and inspect logs for further analysis. For users without a Slurm cluster, hosted inference endpoints are available for testing with usage limits based on registration status.

Data Prep Kit is a community project aimed at democratizing and speeding up unstructured data preparation for LLM app developers. It provides high-level APIs and modules for transforming data (code, language, speech, visual) to optimize LLM performance across different use cases. The toolkit supports Python, Ray, Spark, and Kubeflow Pipelines runtimes, offering scalability from laptop to datacenter-scale processing. Developers can contribute new custom modules and leverage the data processing library for building data pipelines. Automation features include workflow automation with Kubeflow Pipelines for transform execution.

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Optimizes production processes for efficient large-scale operations.

Generates items for psychometric instruments to measure psychological constructs.

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