Best AI tools for< Accelerate Search Process >

ModernQuery is an AI-powered search solution that enhances website search functionality with ChatGPT's conversational search technology. It offers a no-code solution for easy integration, allowing users to improve their on-site search experience without the need for technical expertise. With features like plug-and-play setup, manual search result adjustments, and autocomplete functionality, ModernQuery aims to provide a seamless and efficient search experience for website visitors. The application supports popular CMS platforms like WordPress and Drupal, as well as custom website integrations through JavaScript embedding.

ApplyFox.ai is an AI-powered job application tool that automates the job search process by allowing users to upload their resume and preferences, and then auto-applies to hundreds of job listings on their behalf. The tool helps users save time, increase their chances of landing interviews, and ensures professional and tailored applications across various industries and skill levels.

EarnBetter is an AI-powered platform that offers assistance in creating professional resumes, cover letters, and job search support. The platform utilizes artificial intelligence to rewrite and reformat resumes, generate tailored cover letters, provide personalized job matches, and offer interview support. Users can upload their current resume to get started and access a range of features to enhance their job search process. EarnBetter aims to streamline the job search experience by providing free, unlimited, and professional document creation services.

Jobsolv is an all-in-one job search platform that simplifies the application process for high-paying remote and hybrid roles. It offers a personalized AI-smart job board, automated resume tailoring, and one-click job applications. With Jobsolv, job seekers can efficiently apply to multiple jobs, increasing their chances of securing interviews and landing their dream jobs.

Swiftly AI is an AI-powered recruiting tool designed to streamline the candidate selection process for businesses. By leveraging artificial intelligence, Swiftly AI helps recruiters quickly identify and rank qualified candidates based on specified role requirements. The platform enables users to efficiently filter through a large pool of applicants, saving time and resources in the recruitment process. With Swiftly AI, companies can accelerate their talent search and make data-driven hiring decisions to recruit the most suitable candidates at scale.

Seamless is an AI-powered literature review tool and scholarship search assistant designed to accelerate the academic journey of students and researchers. It utilizes advanced AI technology to generate comprehensive literature reviews, provide AI-driven scholarship search and application tools, and offer essay writing assistance. With access to a vast database of scientific papers, Seamless helps users draft literature reviews, find relevant papers, and apply for scholarships efficiently. The tool aims to redefine the creation of literature reviews through its innovative AI capabilities, making the research process faster and more effective.

ScholarAI is an AI-powered scientific research tool that offers a wide range of features to help users navigate and extract insights from scientific literature. With access to over 200 million peer-reviewed articles, ScholarAI allows users to conduct abstract searches, literature mapping, PDF reading, literature reviews, gap analysis, direct Q&A, table and figure extraction, citation management, and project management. The tool is designed to accelerate the research process and provide tailored scientific insights to users.

Kira Systems is a machine learning contract search, review, and analysis software that helps businesses identify, extract, and analyze content in their contracts and documents. It uses patented machine learning technology to extract concepts and data points with high efficiency and accuracy. Kira also has built-in intelligence that streamlines the contract review process with out-of-the-box smart fields. Businesses can also create their own smart fields to find specific data points using Kira's no-code machine learning tool. Kira's adaptive workflows allow businesses to organize, track, and export results. Kira has a partner ecosystem that allows businesses to transform how teams work with their contracts.

AI Suite is a secure AI automation platform designed for businesses to streamline various processes through AI-powered solutions. The platform offers features such as content automation, meeting documentation, translation & localization, AI-first chatbots, smart search, and services tailored for finance & insurance and medical professionals. AI Suite aims to transform companies into AI-first businesses by saving time on manual tasks and enhancing efficiency through AI technologies.

Toloka AI is a data labeling platform that empowers AI development by combining human insight with machine learning models. It offers adaptive AutoML, human-in-the-loop workflows, large language models, and automated data labeling. The platform supports various AI solutions with human input, such as e-commerce services, content moderation, computer vision, and NLP. Toloka AI aims to accelerate machine learning processes by providing high-quality human-labeled data and leveraging the power of the crowd.

Procurement Sciences is a leading AI platform designed for government contracting, offering a comprehensive suite of AI-driven tools to help government contractors save time, accelerate proposals, and win more bids. From opportunity search to proposal automation, the platform revolutionizes the government contracting process by driving efficiency, success, and competitive advantage. Trusted by thousands of government contractors, Procurement Sciences provides unmatched expertise, proven ROI, and secure hosting solutions tailored for the nation's top defense contractors.

QueryHub is an academic platform that combines collaborative learning with AI-powered solutions. It offers an interactive forum, AI chatbot assistance, and a smart search capability to enhance the academic experience of students. Users can engage in discussions, get instant answers to their queries, and access a pool of shared resources to accelerate their learning. QueryHub's user-driven innovation and personalized learning experience make it a valuable tool for students seeking academic success.

Cypris is an AI-powered platform designed for Research & Development (R&D) and Intellectual Property (IP) professionals. It provides actionable innovation intelligence to accelerate product development, streamline competitive monitoring, and drive long-term innovation strategies. Cypris offers real-time insights from trusted innovation data sources, custom expert-driven research, and access to a vast innovation-focused database. The platform utilizes AI technology, semantic search, and predictive intelligence to deliver tailored insights on competitive intelligence, trend monitoring, and technology scouting.

Transcript.LOL is a transcription tool designed to save time and enhance productivity for creators and small to medium-sized businesses. It offers a platform to transcribe audio, video, and meeting recordings, supporting over 1500 platforms. The tool provides summaries, categorizes key themes, and offers contextual Q&A based on the transcriptions. With speaker identification and readable transcripts, users can easily navigate and understand the content. Transcript.LOL aims to streamline the transcription process and provide valuable insights faster than ever before.

AutoSEO is an AI-powered tool designed to transform the content creation process on WordPress websites. By utilizing advanced artificial intelligence technology, AutoSEO automates and accelerates the production of SEO-optimized web content, enabling users to generate a large quantity of high-quality articles efficiently. The tool integrates seamlessly with WordPress and leverages OpenAI's technology to create content in multiple languages, making it a versatile solution for global content creation.

Wrangle is an AI-powered job search and resume builder platform designed to help job seekers find jobs faster and more efficiently. The platform offers personalized AI copilot assistance, extensive job information, resume creation tools, job tracking features, and a learning algorithm to improve job matches. Wrangle provides a user-friendly experience with a focus on data security and no ads or subscriptions.

Elastic is a Search AI Company that offers a platform for building tailored experiences, search and analytics, data ingestion, visualization, and generative AI solutions. The company provides services like Elastic Cloud for real-time insights, Elastic AI Assistant for retrieval and generation, and Search AI Lake for faster integration with LLMs. Elastic aims to help businesses scale with low-latency search AI and accelerate problem resolution with observability powered by advanced ML and analytics.

Search Atlas is the #1 AI SEO Automation Platform designed for agencies and brands. It offers a comprehensive suite of tools for managing Google Ads with AI, automating SEO tasks, generating AI content, conducting keyword research, and optimizing website performance. The platform is known for its enterprise SEO software, local citation builder, content tools like AI content writer and content planner, research tools like outreach tool and site explorer, and customization options for branding. Search Atlas helps agencies and brands improve strategy, accelerate workflows, and deliver quicker wins in organic marketing campaigns.

Objective is an AI-native search platform designed for developers to build modern search experiences for web and mobile applications. It offers a multimodal search API that understands human language, images, and text relationships. The platform integrates various search techniques to provide natural and relevant search results, even with inconsistent data. Objective is trusted by great companies and accelerates data science roadmaps through its efficient search capabilities.

Tellius is an AI Augmented Analytics Software and Decision Intelligence platform that empowers users to get faster insights from data, break silos between Business Intelligence (BI) and AI, and accelerate complex data analysis with AI-driven automation. The platform offers guided insights, data preparation, natural language search, automated machine learning, and self-service analytics & reporting. Tellius is loved by analytics and business teams for providing instant ad hoc answers, simplifying complex analysis, and surfacing hidden key drivers and anomalies through best-in-class automated insights.

This repository contains examples, applications, starter code, & tutorials to help you kickstart your GenAI projects. * These are built using LanceDB, a free, open-source, serverless vectorDB that **requires no setup**. * It **integrates into python data ecosystem** so you can simply start using these in your existing data pipelines in pandas, arrow, pydantic etc. * LanceDB has **native Typescript SDK** using which you can **run vector search** in serverless functions! This repository is divided into 3 sections: - Examples - Get right into the code with minimal introduction, aimed at getting you from an idea to PoC within minutes! - Applications - Ready to use Python and web apps using applied LLMs, VectorDB and GenAI tools - Tutorials - A curated list of tutorials, blogs, Colabs and courses to get you started with GenAI in greater depth.

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.

This paper list is about Large Language Model-enhanced Recommender System. It also contains some related works. Keywords: recommendation system, large language models

The LLM RAG Workshop repository provides a workshop on using Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) to generate and understand text in a human-like manner. It includes instructions on setting up the environment, indexing Zoomcamp FAQ documents, creating a Q&A system, and using OpenAI for generation based on retrieved information. The repository focuses on enhancing language model responses with retrieved information from external sources, such as document databases or search engines, to improve factual accuracy and relevance of generated text.

This repository is dedicated to the pruning of large language models (LLMs). It aims to serve as a comprehensive resource for researchers and practitioners interested in the efficient reduction of model size while maintaining or enhancing performance. The repository contains various papers, summaries, and links related to different pruning approaches for LLMs, along with author information and publication details. It covers a wide range of topics such as structured pruning, unstructured pruning, semi-structured pruning, and benchmarking methods. Researchers and practitioners can explore different pruning techniques, understand their implications, and access relevant resources for further study and implementation.

The Awesome-LLM-Post-training repository is a curated collection of influential papers, code implementations, benchmarks, and resources related to Large Language Models (LLMs) Post-Training Methodologies. It covers various aspects of LLMs, including reasoning, decision-making, reinforcement learning, reward learning, policy optimization, explainability, multimodal agents, benchmarks, tutorials, libraries, and implementations. The repository aims to provide a comprehensive overview and resources for researchers and practitioners interested in advancing LLM technologies.

Data-to-paper is an AI-driven framework designed to guide users through the process of conducting end-to-end scientific research, starting from raw data to the creation of comprehensive and human-verifiable research papers. The framework leverages a combination of LLM and rule-based agents to assist in tasks such as hypothesis generation, literature search, data analysis, result interpretation, and paper writing. It aims to accelerate research while maintaining key scientific values like transparency, traceability, and verifiability. The framework is field-agnostic, supports both open-goal and fixed-goal research, creates data-chained manuscripts, involves human-in-the-loop interaction, and allows for transparent replay of the research process.

This repository is a curated collection of powerful AI tools that accelerate and enhance game development. It provides tools for asset, texture, image, code generation, animation video mocap, voice generation, speech recognition, conversational models, game design, search engine, AI NPC, Python libraries, and C# libraries. These tools streamline the creation process, save time, automate tasks, and unlock creative possibilities for game developers, whether indie or part of a studio. The repository aims to speed up development and enable the creation of immersive games by leveraging cutting-edge AI technologies.

R1-searcher is a tool designed to incentivize the search capability in large reasoning models (LRMs) via reinforcement learning. It enables LRMs to invoke web search and obtain external information during the reasoning process by utilizing a two-stage outcome-supervision reinforcement learning approach. The tool does not require instruction fine-tuning for cold start and is compatible with existing Base LLMs or Chat LLMs. It includes training code, inference code, model checkpoints, and a detailed technical report.

AITreasureBox is a comprehensive collection of AI tools and resources designed to simplify and accelerate the development of AI projects. It provides a wide range of pre-trained models, datasets, and utilities that can be easily integrated into various AI applications. With AITreasureBox, developers can quickly prototype, test, and deploy AI solutions without having to build everything from scratch. Whether you are working on computer vision, natural language processing, or reinforcement learning projects, AITreasureBox has something to offer for everyone. The repository is regularly updated with new tools and resources to keep up with the latest advancements in the field of artificial intelligence.

Build-your-own-AI-Assistant-Solution-Accelerator is a pre-release and preview solution that helps users create their own AI assistants. It leverages Azure Open AI Service, Azure AI Search, and Microsoft Fabric to identify, summarize, and categorize unstructured information. Users can easily find relevant articles and grants, generate grant applications, and export them as PDF or Word documents. The solution accelerator provides reusable architecture and code snippets for building AI assistants with enterprise data. It is designed for researchers looking to explore flu vaccine studies and grants to accelerate grant proposal submissions.

Open AI is a powerful tool for artificial intelligence research and development. It provides a wide range of machine learning models and algorithms, making it easier for developers to create innovative AI applications. With Open AI, users can explore cutting-edge technologies such as natural language processing, computer vision, and reinforcement learning. The platform offers a user-friendly interface and comprehensive documentation to support users in building and deploying AI solutions. Whether you are a beginner or an experienced AI practitioner, Open AI offers the tools and resources you need to accelerate your AI projects and stay ahead in the rapidly evolving field of artificial intelligence.

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.

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.

SuperAgentX is a lightweight open-source AI framework designed for multi-agent applications with Artificial General Intelligence (AGI) capabilities. It offers goal-oriented multi-agents with retry mechanisms, easy deployment through WebSocket, RESTful API, and IO console interfaces, streamlined architecture with no major dependencies, contextual memory using SQL + Vector databases, flexible LLM configuration supporting various Gen AI models, and extendable handlers for integration with diverse APIs and data sources. It aims to accelerate the development of AGI by providing a powerful platform for building autonomous AI agents capable of executing complex tasks with minimal human intervention.

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.

Awesome-AI-Coding is a curated list of AI coding topics, projects, datasets, LLM models, embedding models, papers, blogs, products, startups, and peer awesome lists related to artificial intelligence in coding. It includes tools for code completion, code generation, code documentation, and code search, as well as AI models and techniques for improving developer productivity. The repository also features information on various AI-powered developer tools, copilots, and related resources in the AI coding domain.

Docling simplifies document processing, parsing diverse formats including advanced PDF understanding, and providing seamless integrations with the general AI ecosystem. It offers features such as parsing multiple document formats, advanced PDF understanding, unified DoclingDocument representation format, various export formats, local execution capabilities, plug-and-play integrations with agentic AI tools, extensive OCR support, and a simple CLI. Coming soon features include metadata extraction, visual language models, chart understanding, and complex chemistry understanding. Docling is installed via pip and works on macOS, Linux, and Windows environments. It provides detailed documentation, examples, integrations with popular frameworks, and support through the discussion section. The codebase is under the MIT license and has been developed by IBM.

Expert in tailored accelerator search for startups.

Accelerate web app development with Material Tailwind GPT's components - 10x faster.

Accelerates the learning of key phrases and cultural norms for travelers in various languages.

The Go-To Coach for Aspiring Digital Entrepreneurs, Innovators, & Startups. Learn More at UnderdogInnovationInc.com.

Niche-focused startup guide, humorous, strategic, simplifying ideas.

Drop in any requirements or any text ; I'll help you create an MVP with insights.

A guide for developing university-focused digital startup accelerator programs.