Best AI tools for< Augment Data >

PandasAI is an open-source AI tool designed for conversational data analysis. It allows users to ask questions in natural language to their enterprise data and receive real-time data insights. The tool is integrated with various data sources and offers enhanced analytics, actionable insights, detailed reports, and visual data representation. PandasAI aims to democratize data analysis for better decision-making, offering enterprise solutions for stable and scalable internal data analysis. Users can also fine-tune models, ingest universal data, structure data automatically, augment datasets, extract data from websites, and forecast trends using AI.

syntheticAIdata is a platform that provides synthetic data for training vision AI models. Synthetic data is generated artificially, and it can be used to augment existing real-world datasets or to create new datasets from scratch. syntheticAIdata's platform is easy to use, and it can be integrated with leading cloud platforms. The company's mission is to make synthetic data accessible to everyone, and to help businesses overcome the challenges of acquiring high-quality data for training their vision AI models.

QuData is an AI and ML solutions provider that helps businesses enhance their value through AI/ML implementation, product design, QA, and consultancy services. They offer a range of services including ChatGPT integration, speech synthesis, speech recognition, image analysis, text analysis, predictive analytics, big data analysis, innovative research, and DevOps solutions. QuData has extensive experience in machine learning and artificial intelligence, enabling them to create high-quality solutions for specific industries, helping customers save development costs and achieve their business goals.

Tome is an AI assistant for sales, designed to enhance sales teams' productivity and efficiency. It offers a new way to research accounts, providing a 360° view of every account, personalized outreach capabilities, and meeting preparation assistance. Tome is used by over 10,000 teams and is engineered to be a second brain for sales professionals, trained on value frameworks and sales data to gather strategic initiatives and understand customers in the Ideal Customer Profile (ICP). It leverages public web and internal data sources to extract valuable insights for sales teams.

The Human-Centred Artificial Intelligence Lab (Holzinger Group) is a research group focused on developing AI solutions that are explainable, trustworthy, and aligned with human values, ethical principles, and legal requirements. The lab works on projects related to machine learning, digital pathology, interactive machine learning, and more. Their mission is to combine human and computer intelligence to address pressing problems in various domains such as forestry, health informatics, and cyber-physical systems. The lab emphasizes the importance of explainable AI, human-in-the-loop interactions, and the synergy between human and machine intelligence.

Prompt Engineering is a discipline focused on developing and optimizing prompts to efficiently utilize language models (LMs) for various applications and research topics. It involves skills to understand the capabilities and limitations of large language models, improving their performance on tasks like question answering and arithmetic reasoning. Prompt engineering is essential for designing robust prompting techniques that interact with LLMs and other tools, enhancing safety and building new capabilities by augmenting LLMs with domain knowledge and external tools.

Giotto.ai is a Swiss-based company focused on building Artificial General Intelligence by combining Modern Machine Learning with Topological and Algebraic methods. They offer AI Strategy Consulting, AI Application Development, AI Model Integrations, AI R&D Services, and on-demand AI & Tech Talent Solutions. The company provides services to various industries such as Insurance, Finance, Logistics, Healthcare, Education, Retail, Manufacturing, and Defence. Giotto.ai aims to automate complex processes with a high level of robustness and explainability, driving innovation in the technological space.

NextGenAI is an AI application focused on the financial services industry. It aims to challenge the current perception of AI and its role in banking and financial institutions. The platform explores innovative ways to augment human intelligence and propel the financial sector into the next generation of AI. Through a combination of keynotes, panels, demos, and workshops, NextGenAI facilitates discussions on AI regulations, industry best practices, and collaboration opportunities.

Veritone is a leading provider of artificial intelligence (AI) solutions for businesses. Its flagship product, aiWARE, is an enterprise AI platform that provides access to hundreds of cognitive engines through one common software infrastructure. Veritone's AI solutions are used by businesses in a variety of industries, including media and entertainment, recruitment, government, legal and compliance, and sports. Veritone's mission is to augment the human workforce by transforming use-case concepts into tangible, industry-leading applications and solutions.

SparkCognition Government Systems (SGS) is a full-spectrum artificial intelligence company dedicated to government and national defense missions. The company leverages AI technologies such as machine learning, natural language processing, and computer vision to enhance mission readiness, battle management, logistics, security, and manufacturing optimization. SparkCognition Government Systems focuses on delivering targeted AI solutions to amplify asset readiness, augment human intelligence, and accelerate decision-making processes for government organizations.

Botsy is an AI chatbot builder designed for WhatsApp, enabling users to create conversational AI chatbots without the need for coding. It allows for natural conversations, brand customization, audience management, user data analysis, and knowledge augmentation. Botsy offers usage-based pricing with discounts for larger message bundles, along with hands-on training and tech support for customers. The platform aims to leverage AI for social impact by providing personalized AI services to communities in need.

Prefit.AI is a generative AI search engine that enables users to quickly generate new content based on a variety of inputs. It can explore and analyze complex data in new ways, discover new trends and patterns, and summarize content, outline multiple solution paths, brainstorm ideas, and create detailed documentation from research notes. Prefit.AI can also respond naturally to human conversation and serve as a tool for customer service and personalization of customer workflows. It can augment employee workflows and act as efficient assistants for everyone in your organization.

Frame is an Intelligent Company Workspace solution that serves as the control center for AI workforce, offering a suite of AI-powered tools and AI employees to scale businesses. It provides features like building custom AI employees, cross-app search, cross-app linking, Chrome extension, and real-time data awareness. Frame empowers users to manage product development, hire employees, manage sales pipelines, raise venture capital, collaborate remotely, centralize company knowledge, and augment teams with AI employees. The application is loved by users from forward-thinking companies and offers a delightful suite of native apps for teamwork, including note-taking, task management, whiteboard, and more. Frame is designed for speed and efficiency, enabling users to switch between apps seamlessly and maintain clean data through auto-enrichment.

Dreamwave is an AI research lab developing new ways to augment human creativity with artificial intelligence. Its products include AI headshots, team headshots, and custom photo studios. AI headshots can be generated in minutes, and team headshots can be generated consistently to scale with growing companies. Custom photo studios allow users to generate new photos of themselves with any scene, outfit, or hair. Dreamwave is committed to empowering human creativity, safe and unbiased representation, and secure and private data.

DataHawk is an eCommerce analytics platform powered by AI that helps users optimize their eCommerce operations from A to Z. It provides competitive intelligence, performance analysis, conversion optimization, sales growth, brand image protection, traffic generation, and more. DataHawk offers automated data collection, composable analytics, AI-powered productivity, integrations, exclusive datasets, and professional services. The platform empowers users with end-to-end visibility, comprehensive marketplace data, flexibility, control over operational data, and expert support. With AI capabilities, DataHawk automates data collection, detects anomalies, generates recommended actions, and augments productivity. The platform enhances revenue, RoAS, and time savings for users, supported by dedicated experts and customer success stories.

Arro is an AI-powered research assistant that helps product teams collect customer insights at scale. It uses automated conversations to conduct user interviews with thousands of customers simultaneously, generating product opportunities that can be directly integrated into the product roadmap. Arro's innovative AI-led methodology combines the depth of user interviews with the speed and scale of surveys, enabling product teams to gain a comprehensive understanding of their customers' needs and preferences.

Augment is a personal AI assistant that helps you remember anything, type less, and read faster. It works inside all the apps you know and love, so you can stay focused on the task at hand. Augment is designed for macOS and is trusted by professionals from all walks of life.

Ideator is an AI-powered tool that helps designers and innovators generate creative ideas. It allows users to input a feature or interaction and then generates different variations of how it could be used, while keeping its main job the same. Ideator is still under development, but it has the potential to be a valuable tool for designers and innovators who are looking for new and creative ways to solve problems.

Swivl is an automation platform designed for self-storage businesses, offering intelligent automation solutions to streamline operations and enhance customer interactions. The platform leverages conversational AI technology to automate conversations with tenants, drive revenue, and augment workforce capabilities. Swivl aims to simplify the rental process, save costs, and increase revenue for self-storage operators while maintaining brand integrity. The platform is trusted by self-storage leaders for its ability to automate customer touchpoints, provide automated customer support and sales assistance, and enhance team productivity. With features like digital assistants, online self-service automation, inventory recommendations, call center deflection, and omni-channel experiences, Swivl is a comprehensive solution for self-storage businesses.

Sana is an AI company transforming how organizations learn and access knowledge. Its AI-first learning platform and knowledge assistant are designed for people teams that want to do learning differently. The platform offers integrations, solutions for employee onboarding, sales enablement, compliance training, leadership development, and external training. The knowledge assistant helps everyone work faster, think bigger, and achieve more. Sana's products are trusted by the world's most pioneering companies.

LangTest is a comprehensive evaluation library for custom LLM and NLP models. It aims to deliver safe and effective language models by providing tools to test model quality, augment training data, and support popular NLP frameworks. LangTest comes with benchmark datasets to challenge and enhance language models, ensuring peak performance in various linguistic tasks. The tool offers more than 60 distinct types of tests with just one line of code, covering aspects like robustness, bias, representation, fairness, and accuracy. It supports testing LLMS for question answering, toxicity, clinical tests, legal support, factuality, sycophancy, and summarization.

Hof is a CLI tool that unifies data models, schemas, code generation, and a task engine. It allows users to augment data, config, and schemas with CUE to improve consistency, generate multiple Yaml and JSON files, explore data or config with a TUI, and run workflows with automatic task dependency inference. The tool uses CUE to power the DX and implementation, providing a language for specifying schemas, configuration, and writing declarative code. Hof offers core features like code generation, data model management, task engine, CUE cmds, creators, modules, TUI, and chat for better, scalable results.

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.

LangCheck is a Python library that provides a suite of metrics and tools for evaluating the quality of text generated by large language models (LLMs). It includes metrics for evaluating text fluency, sentiment, toxicity, factual consistency, and more. LangCheck also provides tools for visualizing metrics, augmenting data, and writing unit tests for LLM applications. With LangCheck, you can quickly and easily assess the quality of LLM-generated text and identify areas for improvement.

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.

Lhotse is a Python library designed to make speech and audio data preparation flexible and accessible. It aims to attract a wider community to speech processing tasks by providing a Python-centric design and an expressive command-line interface. Lhotse offers standard data preparation recipes, PyTorch Dataset classes for speech tasks, and efficient data preparation for model training with audio cuts. It supports data augmentation, feature extraction, and feature-space cut mixing. The tool extends Kaldi's data preparation recipes with seamless PyTorch integration, human-readable text manifests, and convenient Python classes.

DataDreamer is a powerful open-source Python library designed for prompting, synthetic data generation, and training workflows. It is simple, efficient, and research-grade, allowing users to create prompting workflows, generate synthetic datasets, and train models with ease. The library is built for researchers, by researchers, focusing on correctness, best practices, and reproducibility. It offers features like aggressive caching, resumability, support for bleeding-edge techniques, and easy sharing of datasets and models. DataDreamer enables users to run multi-step prompting workflows, generate synthetic datasets for various tasks, and train models by aligning, fine-tuning, instruction-tuning, and distilling them using existing or synthetic data.

Tonic Validate is a framework for the evaluation of LLM outputs, such as Retrieval Augmented Generation (RAG) pipelines. Validate makes it easy to evaluate, track, and monitor your LLM and RAG applications. Validate allows you to evaluate your LLM outputs through the use of our provided metrics which measure everything from answer correctness to LLM hallucination. Additionally, Validate has an optional UI to visualize your evaluation results for easy tracking and monitoring.

Ragas is a framework that helps you evaluate your Retrieval Augmented Generation (RAG) pipelines. RAG denotes a class of LLM applications that use external data to augment the LLM’s context. There are existing tools and frameworks that help you build these pipelines but evaluating it and quantifying your pipeline performance can be hard. This is where Ragas (RAG Assessment) comes in. Ragas provides you with the tools based on the latest research for evaluating LLM-generated text to give you insights about your RAG pipeline. Ragas can be integrated with your CI/CD to provide continuous checks to ensure performance.

This repository is a curated collection of resources for fine-tuning Large Language Models (LLMs) like GPT, BERT, RoBERTa, and their variants. It includes tutorials, papers, tools, frameworks, and best practices to aid researchers, data scientists, and machine learning practitioners in adapting pre-trained models to specific tasks and domains. The resources cover a wide range of topics related to fine-tuning LLMs, providing valuable insights and guidelines to streamline the process and enhance model performance.

Invariant Analyzer is an open-source scanner designed for LLM-based AI agents to find bugs, vulnerabilities, and security threats. It scans agent execution traces to identify issues like looping behavior, data leaks, prompt injections, and unsafe code execution. The tool offers a library of built-in checkers, an expressive policy language, data flow analysis, real-time monitoring, and extensible architecture for custom checkers. It helps developers debug AI agents, scan for security violations, and prevent security issues and data breaches during runtime. The analyzer leverages deep contextual understanding and a purpose-built rule matching engine for security policy enforcement.

The 'llms' repository is a comprehensive guide on Large Language Models (LLMs), covering topics such as language modeling, applications of LLMs, statistical language modeling, neural language models, conditional language models, evaluation methods, transformer-based language models, practical LLMs like GPT and BERT, prompt engineering, fine-tuning LLMs, retrieval augmented generation, AI agents, and LLMs for computer vision. The repository provides detailed explanations, examples, and tools for working with LLMs.

DeepEval is a simple-to-use, open-source LLM evaluation framework specialized for unit testing LLM outputs. It incorporates various metrics such as G-Eval, hallucination, answer relevancy, RAGAS, etc., and runs locally on your machine for evaluation. It provides a wide range of ready-to-use evaluation metrics, allows for creating custom metrics, integrates with any CI/CD environment, and enables benchmarking LLMs on popular benchmarks. DeepEval is designed for evaluating RAG and fine-tuning applications, helping users optimize hyperparameters, prevent prompt drifting, and transition from OpenAI to hosting their own Llama2 with confidence.

The serverless-rag-demo repository showcases a solution for building a Retrieval Augmented Generation (RAG) system using Amazon Opensearch Serverless Vector DB, Amazon Bedrock, Llama2 LLM, and Falcon LLM. The solution leverages generative AI powered by large language models to generate domain-specific text outputs by incorporating external data sources. Users can augment prompts with relevant context from documents within a knowledge library, enabling the creation of AI applications without managing vector database infrastructure. The repository provides detailed instructions on deploying the RAG-based solution, including prerequisites, architecture, and step-by-step deployment process using AWS Cloudshell.

This repository focuses on Retrieval-Augmented Generation (RAG) and Large Language Models (LLMs). It provides code and resources to augment LLMs with real-time data for dynamic, context-aware applications. The content covers topics such as semantic search, fine-tuning embeddings, building RAG chatbots, evaluating LLMs, and using knowledge graphs in RAG. Prerequisites include Python skills, knowledge of machine learning and LLMs, and introductory experience with NLP and AI models.

LLMRec is a PyTorch implementation for the WSDM 2024 paper 'Large Language Models with Graph Augmentation for Recommendation'. It is a novel framework that enhances recommenders by applying LLM-based graph augmentation strategies to recommendation systems. The tool aims to make the most of content within online platforms to augment interaction graphs by reinforcing u-i interactive edges, enhancing item node attributes, and conducting user node profiling from a natural language perspective.

This repository contains the source code and datasets for Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs accepted to ACL 2024. It proposes a framework called Graph Chain-of-thought (Graph-CoT) to enable Language Models to traverse graphs step-by-step for reasoning, interaction, and execution. The motivation is to alleviate hallucination issues in Language Models by augmenting them with structured knowledge sources represented as graphs.

LlamaIndex is a data framework for building LLM applications. It provides tools for ingesting, structuring, and querying data, as well as integrating with LLMs and other tools. LlamaIndex is designed to be easy to use for both beginner and advanced users, and it provides a comprehensive set of features for building LLM applications.

BambooAI is a lightweight library utilizing Large Language Models (LLMs) to provide natural language interaction capabilities, much like a research and data analysis assistant enabling conversation with your data. You can either provide your own data sets, or allow the library to locate and fetch data for you. It supports Internet searches and external API interactions.

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