Best AI tools for< Reduce Onboarding Time >

Snorkell.ai is an automated documentation generation tool that uses AI to create and update docstrings for GitHub projects. It supports multiple programming languages, including Python, JavaScript, TypeScript, Java, and Kotlin. Snorkell.ai integrates with GitHub and automatically generates docstrings whenever a pull request is merged, ensuring that documentation is always up-to-date with the codebase. It helps developers save time and effort by automating the documentation process, leading to improved code quality and reduced onboarding time.

CodexAtlas is an AI-powered tool designed to automate code documentation processes. It leverages the latest advancements in Artificial Intelligence to generate and maintain documentation for software projects, freeing developers from the time-consuming task of writing documentation. With features like real-time updates, onboarding time reduction, and use-case detection, CodexAtlas aims to streamline the documentation process and enhance developer productivity. The tool also offers code conversion capabilities, business domain knowledge integration, and the option for on-premise deployment to cater to diverse organizational needs.

Hermae Solutions offers an AI Assistant for Enterprise Design Systems, providing onboarding acceleration, contractor efficiency, design system adoption support, and knowledge distribution. The AI Documentation Assistant and AI Storybook Assistant help boost frontend productivity and enable continuous training of artificial intelligence profiles. The platform also includes features like crafted datasets, SDK Docs, API Docs, and Assistant Embed for Documentation. Hermae's process simplifies efficiency improvements by gathering information sources, processing data for AI supplementation, customizing integration, and supporting integration success. The AI assistant reduces engineering costs significantly, saving time and money for organizations.

Datuum is an AI-powered data onboarding solution that offers seamless integration for businesses. It simplifies the data onboarding process by automating manual tasks, generating code, and ensuring data accuracy with AI-driven validation. Datuum helps businesses achieve faster time to value, reduce costs, improve scalability, and enhance data quality and consistency.

Wonderway is an AI Sales Coach and Sales Training Platform that utilizes AI to provide automated sales coaching on every call. It helps sales teams train, upskill, and certify their members, leading to increased conversion rates and reduced ramp time. The platform offers personalized training, aligns teams faster, and improves sales onboarding processes. Wonderway uses AI to understand sales team needs and provide tailored recommendations for improvement, making salespeople improve 10x faster with access to their own personal sales coach.

Hoop.dev is an AI-powered application that provides live data masking in Rails console sessions. It offers shielded Rails console access, automated employee onboarding and off-boarding, and AI data masking to protect sensitive information. The application allows for passwordless authentication via Google SSO with MFA, auditability of console operations, and compliance with various security controls and regulations. Hoop.dev aims to streamline Rails console operations, reduce manual workflows, and enhance security measures for user convenience and data protection.

This application is an AI-powered developer relations agent that can automate and consolidate manual developer support. It can automate onboarding and support for developers, and provide insights to improve documentation. The application is trained on technical developer documentation to automate repetitive questions, leading to cost savings, reduced response waiting time, and increased automation of support requests.

Kapa.ai is an AI-powered answer engine that transforms your knowledge base into a reliable and production-ready AI assistant. It provides instant and accurate answers to technical product questions, helping to improve documentation and enhance user experience. With over 40 technical source connectors, Kapa.ai optimizes knowledge sources, acknowledges limitations, and synthesizes information from multiple sources to provide comprehensive answers. It is trusted by hundreds of enterprises and startups to power production-ready AI assistants, reducing support hours and improving user experience.

Guidejar is an AI-powered tool that allows users to create interactive product demos and step-by-step guides effortlessly. It simplifies complex processes by providing easy-to-follow guides with AI superpowers. Trusted by teams worldwide, Guidejar helps transform any process into an interactive demo or guide. Users can customize their guides, share them easily, and enhance them with AI magic, voiceovers, and translations. With features like browser extension, branding, step management, guide views, and call-to-action, Guidejar boosts user activation and conversion rates. It offers different pricing plans to cater to various user needs, from free basic features to premium plans with extensive customization and analytics.

Gaspar AI is an AI application that offers AI support capabilities for businesses. It uses Generative AI to automate tasks, streamline operations, and provide instant answers to employee helpdesk issues. The application aims to boost engagement, amplify productivity, and optimize knowledge management within companies. Gaspar AI integrates seamlessly with popular chat platforms like Slack, MS Teams, and Jira to provide an effortless support experience. With features such as Auto-resolve issues, Automate processes, Offer instant answers, Accelerate approvals, and Optimise knowledge management, Gaspar AI helps reduce manual work, automate repetitive tasks, and enhance overall business efficiency.

Pascal is an AI-powered risk-based KYC & AML screening and monitoring platform that enables users to assess findings faster and more accurately than traditional compliance tools. It leverages AI, machine learning, and Natural Language Processing to analyze open-source and client-specific data, providing insights to identify and assess risks. Pascal simplifies onboarding processes, offers continuous monitoring, reduces false positives, and facilitates better decision-making. The platform features an intuitive interface, supports collaboration, and ensures transparency through comprehensive audit trails. Pascal is a secure solution with ISAE 3402-II certification, exceeding industry standards in protecting organizations.

Briefly is an AI-powered briefing platform that helps users write effective briefs faster. It offers features like FastDrafts for quick draft generation, tailored feedback for improvement, personalized effectiveness case studies for inspiration, and business intelligence engine for strategic alignment. The platform ensures compliance, security, and measurable ROI, with fine-grained admin controls and personalized onboarding. Briefly is trusted by marketers worldwide, from startups to Fortune 500 companies, to enhance their marketing strategies and productivity.

DesignRoasts is a web-based tool that provides personalized AI insights to help you optimize your website or app. Simply upload a screenshot of your product and select your goal (e.g., increase conversions, improve onboarding, etc.), and DesignRoasts will generate a list of actionable feedback tailored to your specific needs. The feedback focuses on improving the user experience, visual design, copywriting, and more.

Newired is an AI-powered digital adoption solution that helps organizations enhance user interactions, secure data, and maintain transparency. It offers interactive step-by-step guidance within any application, cross-application journeys, and flexible deployment options. With Newired, users can significantly reduce learning curves, speed up trainings, and boost productivity. The platform caters to various sectors and applications, supporting digital transformation, global roll-outs, user engagement, customer care, onboarding services, support, and training. Newired's AI technology ensures smarter, fairer, and more reliable digital solutions.

FPT.AI Platform offers a suite of AI-powered products and services to help businesses automate tasks, improve customer engagement, and streamline operations. Its products include FPT AI Chat, an AI chatbot for customer service; FPT AI Engage, a conversational AI platform; FPT AI Read, an intelligent document processing platform; FPT AI eKYC, a digital customer onboarding solution; and Text to Speech, a text-to-speech conversion tool. FPT.AI Platform is designed to help businesses improve efficiency, reduce costs, and enhance the customer experience.

SS&C Blue Prism is an intelligent automation platform that offers a comprehensive suite of tools for automating business processes. It leverages AI and machine learning to accelerate automation journeys, make human-like decisions, and extract data accurately from documents. The platform enables human and digital worker collaboration, accelerates straight-through processing, and integrates process automations rapidly. SS&C Blue Prism is designed to help organizations optimize operations, improve productivity, and enhance customer experiences through intelligent automation solutions.

AR Genie is an AI-powered platform that offers remote visual assistance with augmented reality, revolutionizing operations and support by seamlessly integrating AR with the power of AI. The platform empowers companies to enhance their operations and support through innovative solutions, such as remote assistance, operations and maintenance support, onboarding and troubleshooting, and AR manuals for work instructions. AR Genie provides features like AR annotation tools, live camera streaming, AR glasses support, web portal integration, and mobile-to-mobile sessions. The platform offers benefits such as extending expert reach, minimizing costs, and maximizing uptime, with advantages including reduced technician dispatches, increased customer satisfaction, expanded knowledge, faster problem-solving, and reduced costs. However, some disadvantages include potential technical glitches, dependency on internet connectivity, and the need for user training.

Pongo is an AI-powered tool that helps reduce hallucinations in Large Language Models (LLMs) by up to 80%. It utilizes multiple state-of-the-art semantic similarity models and a proprietary ranking algorithm to ensure accurate and relevant search results. Pongo integrates seamlessly with existing pipelines, whether using a vector database or Elasticsearch, and processes top search results to deliver refined and reliable information. Its distributed architecture ensures consistent latency, handling a wide range of requests without compromising speed. Pongo prioritizes data security, operating at runtime with zero data retention and no data leaving its secure AWS VPC.

DailyBot is an AI-powered toolkit for teams that want automation, better reporting, and customization. It offers a range of features to enhance team visibility, reduce meetings, and improve collaboration. With DailyBot, teams can run asynchronous standups, retros, and other meetings, send kudos and recognition, create surveys and collect data, and access a variety of add-ons like watercoolers and random coffees. DailyBot also integrates with popular tools like Zapier, Jira, and Trello, making it easy to connect with the tools teams already use. Trusted by leading companies and backed by Y Combinator, DailyBot is a valuable tool for teams looking to improve their collaboration and productivity.

Nametag is an identity verification solution designed specifically for IT helpdesks. It helps businesses prevent social engineering attacks, account takeovers, and data breaches by verifying the identity of users at critical moments, such as password resets, MFA resets, and high-risk transactions. Nametag's unique approach to identity verification combines mobile cryptography, device telemetry, and proprietary AI models to provide unmatched security and better user experiences.

Contoso Chat is a Python sample demonstrating how to build, evaluate, and deploy a retail copilot application with Azure AI Studio using Promptflow with Prompty assets. The sample implements a Retrieval Augmented Generation approach to answer customer queries based on the company's product catalog and customer purchase history. It utilizes Azure AI Search, Azure Cosmos DB, Azure OpenAI, text-embeddings-ada-002, and GPT models for vectorizing user queries, AI-assisted evaluation, and generating chat responses. By exploring this sample, users can learn to build a retail copilot application, define prompts using Prompty, design, run & evaluate a copilot using Promptflow, provision and deploy the solution to Azure using the Azure Developer CLI, and understand Responsible AI practices for evaluation and content safety.

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.

Chat with your data using OpenAI and AI Search. This solution accelerator uses an Azure OpenAI GPT model and an Azure AI Search index generated from your data, which is integrated into a web application to provide a natural language interface, including speech-to-text functionality, for search queries. Users can drag and drop files, point to storage, and take care of technical setup to transform documents. There is a web app that users can create in their own subscription with security and authentication.

Dockershrink is an AI-powered Commandline Tool designed to help reduce the size of Docker images. It combines traditional Rule-based analysis with Generative AI techniques to optimize Image configurations. The tool supports NodeJS applications and aims to save costs on storage, data transfer, and build times while increasing developer productivity. By automatically applying advanced optimization techniques, Dockershrink simplifies the process for engineers and organizations, resulting in significant savings and efficiency improvements.

Lobe Icons is a collection of popular AI / LLM Model Brand SVG logos and icons. It features lightweight and scalable icons designed with highly optimized scalable vector graphics (SVG) for optimal performance. The collection is tree-shakable, allowing users to import only the icons they need to reduce the overall bundle size of their projects. Lobe Icons has an active community of designers and developers who can contribute and seek support on platforms like GitHub and Discord. The repository supports a wide range of brands across different models, providers, and applications, with more brands continuously being added through contributions. Users can easily install Lobe UI with the provided commands and integrate it with NextJS for server-side rendering. Local development can be done using Github Codespaces or by cloning the repository. Contributions are welcome, and users can contribute code by checking out the GitHub Issues. The project is MIT licensed and maintained by LobeHub.

Baal is an active learning library that supports both industrial applications and research use cases. It provides a framework for Bayesian active learning methods such as Monte-Carlo Dropout, MCDropConnect, Deep ensembles, and Semi-supervised learning. Baal helps in labeling the most uncertain items in the dataset pool to improve model performance and reduce annotation effort. The library is actively maintained by a dedicated team and has been used in various research papers for production and experimentation.

Voicechat2 is a fast, fully local AI voice chat tool that uses WebSockets for communication. It includes a WebSocket server for remote access, default web UI with VAD and Opus support, and modular/swappable SRT, LLM, TTS servers. Users can customize components like SRT, LLM, and TTS servers, and run different models for voice-to-voice communication. The tool aims to reduce latency in voice communication and provides flexibility in server configurations.

LMCache is a serving engine extension designed to reduce time to first token (TTFT) and increase throughput, particularly in long-context scenarios. It stores key-value caches of reusable texts across different locations like GPU, CPU DRAM, and Local Disk, allowing the reuse of any text in any serving engine instance. By combining LMCache with vLLM, significant delay savings and GPU cycle reduction are achieved in various large language model (LLM) use cases, such as multi-round question answering and retrieval-augmented generation (RAG). LMCache provides integration with the latest vLLM version, offering both online serving and offline inference capabilities. It supports sharing key-value caches across multiple vLLM instances and aims to provide stable support for non-prefix key-value caches along with user and developer documentation.

Consistency Large Language Models (CLLMs) is a family of efficient parallel decoders that reduce inference latency by efficiently decoding multiple tokens in parallel. The models are trained to perform efficient Jacobi decoding, mapping any randomly initialized token sequence to the same result as auto-regressive decoding in as few steps as possible. CLLMs have shown significant improvements in generation speed on various tasks, achieving up to 3.4 times faster generation. The tool provides a seamless integration with other techniques for efficient Large Language Model (LLM) inference, without the need for draft models or architectural modifications.

This repository contains codes related to Generative AI as per YouTube video. It includes various notebooks and files for different days covering topics like map reduce, text to SQL, LLM parameters, tagging, and Kaggle competition. The repository also includes resources like PDF files and databases for different projects related to Generative AI.

MaskLLM is a learnable pruning method that establishes Semi-structured Sparsity in Large Language Models (LLMs) to reduce computational overhead during inference. It is scalable and benefits from larger training datasets. The tool provides examples for running MaskLLM with Megatron-LM, preparing LLaMA checkpoints, pre-tokenizing C4 data for Megatron, generating prior masks, training MaskLLM, and evaluating the model. It also includes instructions for exporting sparse models to Huggingface.

The Medical_Image_Analysis repository focuses on X-ray image-based medical report generation using large language models. It provides pre-trained models and benchmarks for CheXpert Plus dataset, context sample retrieval for X-ray report generation, and pre-training on high-definition X-ray images. The goal is to enhance diagnostic accuracy and reduce patient wait times by improving X-ray report generation through advanced AI techniques.

Control large language models and AI tools through voice commands using the Talon Voice dictation engine. This tool is designed to help users quickly edit text, code by voice, reduce keyboard use for those with health issues, and speed up workflow by using AI commands across the desktop. It prompts and extends tools like Github Copilot and OpenAI API for text and image generation. Users can set up the tool by downloading the repo, obtaining an OpenAI API key, and customizing the endpoint URL for preferred models. The tool can be used without an OpenAI key and can be exclusively used with Copilot for those not needing LLM integration.

AutoGPTQ is an easy-to-use LLM quantization package with user-friendly APIs, based on GPTQ algorithm (weight-only quantization). It provides a simple and efficient way to quantize large language models (LLMs) to reduce their size and computational cost while maintaining their performance. AutoGPTQ supports a wide range of LLM models, including GPT-2, GPT-J, OPT, and BLOOM. It also supports various evaluation tasks, such as language modeling, sequence classification, and text summarization. With AutoGPTQ, users can easily quantize their LLM models and deploy them on resource-constrained devices, such as mobile phones and embedded systems.

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.

Codefuse-ModelCache is a semantic cache for large language models (LLMs) that aims to optimize services by introducing a caching mechanism. It helps reduce the cost of inference deployment, improve model performance and efficiency, and provide scalable services for large models. The project caches pre-generated model results to reduce response time for similar requests and enhance user experience. It integrates various embedding frameworks and local storage options, offering functionalities like cache-writing, cache-querying, and cache-clearing through RESTful API. The tool supports multi-tenancy, system commands, and multi-turn dialogue, with features for data isolation, database management, and model loading schemes. Future developments include data isolation based on hyperparameters, enhanced system prompt partitioning storage, and more versatile embedding models and similarity evaluation algorithms.

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.

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