Best AI tools for< Refine Data >

Basejump AI is an AI-powered data access tool that allows users to interact with their database using natural language queries. It empowers teams to access data quickly and easily, providing instant insights and eliminating the need to navigate through complex dashboards. With Basejump AI, users can explore data, save relevant information, create custom collections, and refine datapoints to meet their specific requirements. The tool ensures data accuracy by allowing users to compare datapoints side by side. Basejump AI caters to various industries such as healthcare, HR, and software, offering real-time insights and analytics to streamline decision-making processes and optimize workflow efficiency.

Voxel51 is an AI tool that provides open-source computer vision tools for machine learning. It offers solutions for various industries such as agriculture, aviation, driving, healthcare, manufacturing, retail, robotics, and security. Voxel51's main product, FiftyOne, helps users explore, visualize, and curate visual data to improve model performance and accelerate the development of visual AI applications. The platform is trusted by thousands of users and companies, offering both open-source and enterprise-ready solutions to manage and refine data and models for visual AI.

Globose Technology Solutions Pvt Ltd (GTS) is an AI data collection company that provides various datasets such as image datasets, video datasets, text datasets, speech datasets, etc., to train machine learning models. They offer premium data collection services with a human touch, aiming to refine AI vision and propel AI forward. With over 25+ years of experience, they specialize in data management, annotation, and effective data collection techniques for AI/ML. The company focuses on unlocking high-quality data, understanding AI's transformative impact, and ensuring data accuracy as the backbone of reliable AI.

DataChat is a no-code, AI analytics platform that enables business users to ask questions of their data in plain English, empowering them to gain insights quickly and efficiently. The platform allows users to refine questions, reshape data, and adjust insights without any coding required. DataChat ensures transparency in the workflow and maintains data security by performing all computations within the user's data warehouse. With DataChat, users can easily access real-time insights and make data-driven decisions to enhance their business operations.

Grro is an AI-powered platform that provides audience insights for over 550,000 English podcasts. It offers data-driven insights to help podcast creators understand their audience better, identify niche segments, and leverage marketing potential. With weekly updates, Grro helps users refine their content strategy, find partnership opportunities, and analyze viral reach. The platform aims to empower podcasters with valuable information to make informed decisions and enhance their podcasting experience.

Namique is an AI-powered name generator that helps businesses create short, brandable, and memorable names. It utilizes an advanced AI model to generate unique and attention-grabbing names. Namique also offers custom filters to help businesses find the perfect name for their brand. Additionally, Namique provides discounts on domain purchases when a name generated by Namique is used.

CVBee.ai is an AI-powered online CV maker that offers a comprehensive solution for creating, optimizing, and refining professional resumes. The platform utilizes artificial intelligence to generate CVs from users' career background, enhance existing CVs with industry-specific keywords, and provide format and structure suggestions. With features like iterative refinement and keyword optimization, CVBee.ai aims to help job seekers craft job-winning resumes that stand out in Applicant Tracking Systems (ATS) and increase their chances of landing interviews.

Capitol AI is an AI tool designed to help users create persuasive content from data. It is currently in beta phase, where AI-generated content may be incorrect or misleading. The platform offers users the ability to leverage AI technology to generate compelling content based on data inputs. Capitol AI aims to streamline the content creation process and provide users with valuable insights to enhance their communication strategies.

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.

ExcelMaster is an AI-powered Excel formula and VBA assistant that provides human-level expertise. It can generate formulas, fix or explain existing formulas, learn formula skills, and draft and refine VBA scripts. ExcelMaster is the first of its kind product that handles real-world Excel structure and solves complicated formula/VBA assignments. It is far better than other “toy” formula bots, Copilot, and ChatGPT.

CHAPTR is an innovative AI solutions provider that aims to redefine work and fuel human innovation. They offer AI-driven solutions tailored to empower, innovate, and transform work processes. Their products are designed to enhance efficiency, foster creativity, and anticipate change in the modern workforce. CHAPTR's solutions are user-centric, secure, customizable, and backed by the Holtzbrinck Publishing Group. They are committed to relentless innovation and continuous advancement in AI technology.

NeoPrompts is an AI-powered prompt optimization tool designed to help businesses enhance their efficiency by providing tailored prompts for various industries. With a vast library of 25,000 optimized prompts, NeoPrompts ensures clear and precise instructions to achieve accurate results in AI applications. The tool reduces ambiguity, enhances clarity, and offers prompt customization for image and video generation. NeoPrompts aims to be the best copilot for ChatGPT users, offering prompt refinement and boosting productivity by up to 35%. Users can access free trials and advanced features to optimize prompts, chat with ChatGPT-4o, and enroll in courses for enhanced AI capabilities.

Inworld is an AI framework designed for games and media, offering a production-ready framework for building AI agents with client-side logic and local model inference. It provides tools optimized for real-time data ingestion, low latency, and massive scale, enabling developers to create engaging and immersive experiences for users. Inworld allows for building custom AI agent pipelines, refining agent behavior and performance, and seamlessly transitioning from prototyping to production. With support for C++, Python, and game engines, Inworld aims to future-proof AI development by integrating 3rd-party components and foundational models to avoid vendor lock-in.

Pixis is a codeless AI infrastructure designed for growth marketing, offering purpose-built AI solutions to scale demand generation. The platform leverages transparent AI infrastructure to optimize campaign results across platforms, with features such as targeting AI, creative AI, and performance AI. Pixis helps reduce customer acquisition cost, generate creative assets quickly, refine audience targeting, and deliver contextual communication in real-time. The platform also provides an AI savings calculator to estimate the returns from leveraging its codeless AI infrastructure for marketing. With success stories showcasing significant improvements in various marketing metrics, Pixis aims to empower businesses to unlock the capabilities of AI for enhanced performance and results.

Preps is an AI-powered mock interview simulation platform designed to help users prepare for technical interviews. It offers realistic interview scenarios that mimic real-world technical interviews conducted at top tech companies. Users can practice with AI interviewers in real-time, receive personalized feedback, and improve their interview skills. With Preps, users can simulate various interview scenarios, practice unexpected questions, and refine their answers to increase their chances of success in technical interviews.

Dropshipping Copilot is an AI-assisted tool for dropshippers and e-commerce enthusiasts. It offers data-driven insights, top product searches, and supplier sourcing to help users grow their sales and profits efficiently. With over 231,487 users, Dropshipping Copilot provides access to over 200 million trending products and 300,000 suppliers from AliExpress. Its AI-assisted product selection feature provides instant matches based on keywords, helping users expand their creative selection and improve accuracy with each pick. The tool also offers AI-powered image enhancement, title optimization, and Shopify sync for seamless product listing and inventory management. Dropshipping Copilot provides market intelligence, including trend detection, competitive analysis, and strategic insights, to help users refine their approach and gain an edge in the market. It also offers cost efficiency, profit growth, and informed supplier selection to help users maximize their margins. The tool's workflow automation features, such as auto-listing, bulk pricing, and real-time sync, streamline operations and save time. Dropshipping Copilot is designed to help users uncover new products, elevate their listings, equip themselves with data-driven insights, boost their margins, and streamline their workflow.

Blobr AI is an AI-powered ads expert tool designed to help users maximize their advertising budget on Google Ads. The tool connects to users' ads 24/7, leveraging top SEA practices to provide actionable recommendations for bidding strategy, keyword optimization, targeting adjustments, and CPC reduction. By automating deep analysis at scale, Blobr AI allows users to focus on strategy while the AI handles data optimization, leading to constant growth and improved ROI.

LLM Quality Beefer-Upper is an AI tool designed to enhance the quality and productivity of LLM responses by automating critique, reflection, and improvement. Users can generate multi-agent prompt drafts, choose from different quality levels, and upload knowledge text for processing. The application aims to maximize output quality by utilizing the best available LLM models in the market.

Amazon Q in QuickSight is a generative BI assistant that makes it easy to build and consume insights. With Amazon Q, BI users can build, discover, and share actionable insights and narratives in seconds using intuitive natural language experiences. Analysts can quickly build visuals and calculations and refine visuals using natural language. Business users can self-serve data and insights using natural language. Amazon Q is built with security and privacy in mind. It can understand and respect your existing governance identities, roles, and permissions and use this information to personalize its interactions. If a user doesn't have permission to access certain data without Amazon Q, they can't access it using Amazon Q either. Amazon Q in QuickSight is designed to meet the most stringent enterprise requirements from day one—none of your data or Amazon Q inputs and outputs are used to improve underlying models of Amazon Q for anyone but you.

Cover Letter AI is an AI-powered tool that helps job seekers write professional and personalized cover letters in any language in just minutes. The tool uses modern large language models to generate cover letters that are tailored to the specific job and company that the user is applying to. Cover Letter AI is easy to use and requires no prior writing experience. Users simply need to upload their CV and fill out a few basic details about the job they are applying for. Cover Letter AI will then generate multiple versions of the cover letter, which the user can then edit and refine until they are satisfied with the final result.

ProX is a lm-based data refinement framework that automates the process of cleaning and improving data used in pre-training large language models. It offers better performance, domain flexibility, efficiency, and cost-effectiveness compared to traditional methods. The framework has been shown to improve model performance by over 2% and boost accuracy by up to 20% in tasks like math. ProX is designed to refine data at scale without the need for manual adjustments, making it a valuable tool for data preprocessing in natural language processing tasks.

Data-Juicer is a one-stop data processing system to make data higher-quality, juicier, and more digestible for LLMs. It is a systematic & reusable library of 80+ core OPs, 20+ reusable config recipes, and 20+ feature-rich dedicated toolkits, designed to function independently of specific LLM datasets and processing pipelines. Data-Juicer allows detailed data analyses with an automated report generation feature for a deeper understanding of your dataset. Coupled with multi-dimension automatic evaluation capabilities, it supports a timely feedback loop at multiple stages in the LLM development process. Data-Juicer offers tens of pre-built data processing recipes for pre-training, fine-tuning, en, zh, and more scenarios. It provides a speedy data processing pipeline requiring less memory and CPU usage, optimized for maximum productivity. Data-Juicer is flexible & extensible, accommodating most types of data formats and allowing flexible combinations of OPs. It is designed for simplicity, with comprehensive documentation, easy start guides and demo configs, and intuitive configuration with simple adding/removing OPs from existing configs.

Dataformer is a robust framework for creating high-quality synthetic datasets for AI, offering speed, reliability, and scalability. It empowers engineers to rapidly generate diverse datasets grounded in proven research methodologies, enabling them to prioritize data excellence and achieve superior standards for AI models. Dataformer integrates with multiple LLM providers using one unified API, allowing parallel async API calls and caching responses to minimize redundant calls and reduce operational expenses. Leveraging state-of-the-art research papers, Dataformer enables users to generate synthetic data with adaptability, scalability, and resilience, shifting their focus from infrastructure concerns to refining data and enhancing models.

LLM-PowerHouse is a comprehensive and curated guide designed to empower developers, researchers, and enthusiasts to harness the true capabilities of Large Language Models (LLMs) and build intelligent applications that push the boundaries of natural language understanding. This GitHub repository provides in-depth articles, codebase mastery, LLM PlayLab, and resources for cost analysis and network visualization. It covers various aspects of LLMs, including NLP, models, training, evaluation metrics, open LLMs, and more. The repository also includes a collection of code examples and tutorials to help users build and deploy LLM-based applications.

LLM Datasets is a repository containing high-quality datasets, tools, and concepts for LLM fine-tuning. It provides datasets with characteristics like accuracy, diversity, and complexity to train large language models for various tasks. The repository includes datasets for general-purpose, math & logic, code, conversation & role-play, and agent & function calling domains. It also offers guidance on creating high-quality datasets through data deduplication, data quality assessment, data exploration, and data generation techniques.

STILL is an open-source project exploring slow-thinking reasoning systems, focusing on o1-like reasoning systems. The project has released technical reports on enhancing LLM reasoning with reward-guided tree search algorithms and implementing slow-thinking reasoning systems using an imitate, explore, and self-improve framework. The project aims to replicate the capabilities of industry-level reasoning systems by fine-tuning reasoning models with long-form thought data and iteratively refining training datasets.

The LLM course is divided into three parts: 1. 🧩 **LLM Fundamentals** covers essential knowledge about mathematics, Python, and neural networks. 2. 🧑‍🔬 **The LLM Scientist** focuses on building the best possible LLMs using the latest techniques. 3. 👷 **The LLM Engineer** focuses on creating LLM-based applications and deploying them. For an interactive version of this course, I created two **LLM assistants** that will answer questions and test your knowledge in a personalized way: * 🤗 **HuggingChat Assistant**: Free version using Mixtral-8x7B. * 🤖 **ChatGPT Assistant**: Requires a premium account. ## 📝 Notebooks A list of notebooks and articles related to large language models. ### Tools | Notebook | Description | Notebook | |----------|-------------|----------| | 🧐 LLM AutoEval | Automatically evaluate your LLMs using RunPod |  | | 🥱 LazyMergekit | Easily merge models using MergeKit in one click. |  | | 🦎 LazyAxolotl | Fine-tune models in the cloud using Axolotl in one click. |  | | ⚡ AutoQuant | Quantize LLMs in GGUF, GPTQ, EXL2, AWQ, and HQQ formats in one click. |  | | 🌳 Model Family Tree | Visualize the family tree of merged models. |  | | 🚀 ZeroSpace | Automatically create a Gradio chat interface using a free ZeroGPU. |  |

DB-GPT is a personal database administrator that can solve database problems by reading documents, using various tools, and writing analysis reports. It is currently undergoing an upgrade. **Features:** * **Online Demo:** * Import documents into the knowledge base * Utilize the knowledge base for well-founded Q&A and diagnosis analysis of abnormal alarms * Send feedbacks to refine the intermediate diagnosis results * Edit the diagnosis result * Browse all historical diagnosis results, used metrics, and detailed diagnosis processes * **Language Support:** * English (default) * Chinese (add "language: zh" in config.yaml) * **New Frontend:** * Knowledgebase + Chat Q&A + Diagnosis + Report Replay * **Extreme Speed Version for localized llms:** * 4-bit quantized LLM (reducing inference time by 1/3) * vllm for fast inference (qwen) * Tiny LLM * **Multi-path extraction of document knowledge:** * Vector database (ChromaDB) * RESTful Search Engine (Elasticsearch) * **Expert prompt generation using document knowledge** * **Upgrade the LLM-based diagnosis mechanism:** * Task Dispatching -> Concurrent Diagnosis -> Cross Review -> Report Generation * Synchronous Concurrency Mechanism during LLM inference * **Support monitoring and optimization tools in multiple levels:** * Monitoring metrics (Prometheus) * Flame graph in code level * Diagnosis knowledge retrieval (dbmind) * Logical query transformations (Calcite) * Index optimization algorithms (for PostgreSQL) * Physical operator hints (for PostgreSQL) * Backup and Point-in-time Recovery (Pigsty) * **Continuously updated papers and experimental reports** This project is constantly evolving with new features. Don't forget to star ⭐ and watch 👀 to stay up to date.

This repository contains the code and dataset for LDB, a novel debugging framework that enables Large Language Models (LLMs) to refine their generated programs by tracking the values of intermediate variables throughout the runtime execution. LDB segments programs into basic blocks, allowing LLMs to concentrate on simpler code units, verify correctness block by block, and pinpoint errors efficiently. The tool provides APIs for debugging and generating code with debugging messages, mimicking how human developers debug programs.

Open Data QnA is a Python library that allows users to interact with their PostgreSQL or BigQuery databases in a conversational manner, without needing to write SQL queries. The library leverages Large Language Models (LLMs) to bridge the gap between human language and database queries, enabling users to ask questions in natural language and receive informative responses. It offers features such as conversational querying with multiturn support, table grouping, multi schema/dataset support, SQL generation, query refinement, natural language responses, visualizations, and extensibility. The library is built on a modular design and supports various components like Database Connectors, Vector Stores, and Agents for SQL generation, validation, debugging, descriptions, embeddings, responses, and visualizations.

This repository is a curated collection of data science and AI concepts and IQs, covering topics from foundational mathematics to cutting-edge generative AI concepts. It aims to support learners and professionals preparing for various data science roles by providing detailed explanations and notebooks for each concept.

HuatuoGPT-o1 is a medical language model designed for advanced medical reasoning. It can identify mistakes, explore alternative strategies, and refine answers. The model leverages verifiable medical problems and a specialized medical verifier to guide complex reasoning trajectories and enhance reasoning through reinforcement learning. The repository provides access to models, data, and code for HuatuoGPT-o1, allowing users to deploy the model for medical reasoning tasks.

Taranis AI is an advanced Open-Source Intelligence (OSINT) tool that leverages Artificial Intelligence to revolutionize information gathering and situational analysis. It navigates through diverse data sources like websites to collect unstructured news articles, utilizing Natural Language Processing and Artificial Intelligence to enhance content quality. Analysts then refine these AI-augmented articles into structured reports that serve as the foundation for deliverables such as PDF files, which are ultimately published.

A collection of papers related to knowledge distillation of large language models (LLMs). The repository focuses on techniques to transfer advanced capabilities from proprietary LLMs to smaller models, compress open-source LLMs, and refine their performance. It covers various aspects of knowledge distillation, including algorithms, skill distillation, verticalization distillation in fields like law, medical & healthcare, finance, science, and miscellaneous domains. The repository provides a comprehensive overview of the research in the area of knowledge distillation of LLMs.

LLM Consortium is a plugin for the `llm` package that implements a model consortium system with iterative refinement and response synthesis. It orchestrates multiple learned language models to collaboratively solve complex problems through structured dialogue, evaluation, and arbitration. The tool supports multi-model orchestration, iterative refinement, advanced arbitration, database logging, configurable parameters, hundreds of models, and the ability to save and load consortium configurations.

LLM101n is a course focused on building a Storyteller AI Large Language Model (LLM) from scratch in Python, C, and CUDA. The course covers various topics such as language modeling, machine learning, attention mechanisms, tokenization, optimization, device usage, precision training, distributed optimization, datasets, inference, finetuning, deployment, and multimodal applications. Participants will gain a deep understanding of AI, LLMs, and deep learning through hands-on projects and practical examples.

This repository contains the Python source code for FINMEM, a Performance-Enhanced Large Language Model Trading Agent with Layered Memory and Character Design. It introduces FinMem, a novel LLM-based agent framework devised for financial decision-making, encompassing three core modules: Profiling, Memory with layered processing, and Decision-making. FinMem's memory module aligns closely with the cognitive structure of human traders, offering robust interpretability and real-time tuning. The framework enables the agent to self-evolve its professional knowledge, react agilely to new investment cues, and continuously refine trading decisions in the volatile financial environment. It presents a cutting-edge LLM agent framework for automated trading, boosting cumulative investment returns.

Crawl4AI is a powerful and free web crawling service that extracts valuable data from websites and provides LLM-friendly output formats. It supports crawling multiple URLs simultaneously, replaces media tags with ALT, and is completely free to use and open-source. Users can integrate Crawl4AI into Python projects as a library or run it as a standalone local server. The tool allows users to crawl and extract data from specified URLs using different providers and models, with options to include raw HTML content, force fresh crawls, and extract meaningful text blocks. Configuration settings can be adjusted in the `crawler/config.py` file to customize providers, API keys, chunk processing, and word thresholds. Contributions to Crawl4AI are welcome from the open-source community to enhance its value for AI enthusiasts and developers.

MemFree is an open-source hybrid AI search engine that allows users to simultaneously search their personal knowledge base (bookmarks, notes, documents, etc.) and the Internet. It features a self-hosted super fast serverless vector database, local embedding and rerank service, one-click Chrome bookmarks index, and full code open source. Users can contribute by opening issues for bugs or making pull requests for new features or improvements.

CyberScraper 2077 is an advanced web scraping tool powered by AI, designed to extract data from websites with precision and style. It offers a user-friendly interface, supports multiple data export formats, operates in stealth mode to avoid detection, and promises lightning-fast scraping. The tool respects ethical scraping practices, including robots.txt and site policies. With upcoming features like proxy support and page navigation, CyberScraper 2077 is a futuristic solution for data extraction in the digital realm.

Specializes in creating, refining, and testing data analysis prompts based on user queries.

I refine complex knowledge into granular, integrated solutions.

Craft and refine GPTs. Join our Reddit community: https://www.reddit.com/r/GPTreview/

Assists with creating, refining, and understanding neural networks.

Expert in refining custom GPT model instructions.

Refines search queries with specific terms and includes Google links

I'm an acronym finder, ranking possibilities and refining with context. I can also suggest acronyms given a term or phrase.

Refines code in multiple languages.

Refines GPT instruction sets for optimal performance

Optimized with advanced search operators for refined results. Specializing in finding and linking top custom GPTs from builders around the world. Version 0.3.0

I help refine product enhancements. Logic - Essential Details - Business Value

I refine AI art prompts for Stable Diffusion model.

Refine your startup strategy with Startup Business Validator: Dive into SWOT, Business Model Canvas, PESTEL, and more for comprehensive insights. Got just an idea? We'll craft the details for you.

I refine journals while keeping your unique voice.

I refine fantasy character details for accurate art.

I refine academic writing, list edits in a table, and provide the final paragraph.

Helps write and refine medical SCI papers with accuracy and research guidance.

Write prompt like a professional! I refine user prompts for optimal ChatGPT responses. Type "Start" to begin.

I refine resumes and prep interviews.

I refine explanations.