Best AI tools for< Graph Network Inference >

Sardine is an AI-powered platform for fraud prevention and compliance. It offers a comprehensive suite of products to help banks, retailers, and fintechs detect fraud patterns, prevent money laundering, and stop sophisticated scams. Sardine combines deep device intelligence, behavior biometrics, and identity signals to provide a precise risk score for every customer interaction. The platform also features machine learning models, a rules engine, network graph analysis, anomaly detection, and generative AI capabilities to fight modern threats. Sardine helps reduce fraud rates, decrease false positives, and streamline risk operations with its fully integrated solutions.

Maven is a social media platform that focuses on connecting people based on shared interests rather than followers or likes. It offers a social media detox by providing a network without borders where users can have meaningful conversations and discover relevant content. Maven incorporates AI technology to help users untangle their thoughts, connect with like-minded individuals, and explore trending interests. The platform aims to create a community-driven space for users to engage in thoughtful discussions and expand their interests.

Metabob is an AI-powered code review tool that helps developers detect, explain, and fix coding problems. It utilizes proprietary graph neural networks to detect problems and LLMs to explain and resolve them, combining the best of both worlds. Metabob's AI is trained on millions of bug fixes performed by experienced developers, enabling it to detect complex problems that span across codebases and automatically generate fixes for them. It integrates with popular code hosting platforms such as GitHub, Bitbucket, Gitlab, and VS Code, and supports various programming languages including Python, Javascript, Typescript, Java, C++, and C.

Kumo is an AI-powered platform that helps businesses personalize customer experiences, acquire new customers, understand customer behavior, improve planning and monitoring, resolve data inconsistencies, fight fraud and abuse, detect money laundering, and empower data scientists with advanced techniques. It offers cutting-edge solutions for various AI and machine learning tasks, such as predictive modeling, anomaly detection, entity resolution, and graph embeddings. Kumo's capabilities are designed to enhance customer interactions, optimize marketing campaigns, and provide valuable insights for businesses across different industries.

InfraNodus is a text network visualization tool that helps users generate insights from any discourse by representing it as a network. It uses AI-powered algorithms to identify structural gaps in the text and suggest ways to bridge them. InfraNodus can be used for a variety of purposes, including research, creative writing, marketing, and SEO.

DealGraph is an AI-powered platform that helps users explore business networks by leveraging hidden relationships among organizations. By analyzing unstructured texts and images, DealGraph provides Relationship Intelligence, allowing users to gain instant knowledge of connections their prospects, customers, or competitors have with other organizations. The platform offers Relationship Alerts to notify users of new relationships, enabling them to uncover crucial insights and opportunities without the need for extensive research. DealGraph also features a Relationship Graph that visualizes organization networks through interactive graphs, answering key questions about market dynamics, customer relationships, industry trends, and supply chain structures. It caters to various users, including sales teams for prospecting, investors for company research, and corporate development teams for market overviews.

Ekko is an AI-enabled Web3 application that serves as an events Oracle, providing real-time alerts, reports, and insights for Web3 users. It addresses critical problems faced by users in managing, analyzing, and automating interactions with onchain and offchain events. Ekko offers a user-friendly interface for creating custom alerts, notifications, and automation workflows without the need for coding skills. It facilitates seamless integration of data sources and interoperability between blockchain networks, reducing the burden on developers and increasing efficiency.

The website is an AI tool designed to generate a knowledge graph based on input text. It uses advanced algorithms and machine learning capabilities to streamline operations, deliver personalized experiences, and unlock new possibilities. Users can input text related to various topics, and the tool processes the information to create a structured knowledge graph.

Quanty is an AI-driven financial knowledge graph application that provides market insights on crypto and stocks news through advanced algorithms and knowledge graphs. It offers a GraphQL API for deep market understanding, smart data classification, current market insights, entity and relationship extraction, and dynamic GraphQL access. Users can access a wide range of financial news, insights, and analytics seamlessly through Quanty's robust GraphQL API.

UPTO3 is a decentralized event knowledge graph protocol that aims to provide consensus verification for Web3 events by turning them into NFTs. Users can mint and verify events on the platform, with rewards based on the outcomes. The platform promotes transparency, open data access, and unbiased analysis through economic incentives. UPTO3 will be built on Blast(L2) and offers features such as event minting as NFTs, decentralized verification tasks, and gas rewards for validators. The project launch is scheduled to coincide with Blast's mainnet launch in February, following the testnet launch in January.

Derwen is an open-source integration platform for production machine learning in enterprise, specializing in natural language processing, graph technologies, and decision support. It offers expertise in developing knowledge graph applications and domain-specific authoring. Derwen collaborates closely with Hugging Face and provides strong data privacy guarantees, low carbon footprint, and no cloud vendor involvement. The platform aims to empower AI engineers and domain experts with quality, time-to-value, and ownership since 2017.

VIVA is an AI-powered creative visual design platform that aims to bring every moment to life. It provides users with tools and features to create visually appealing designs effortlessly. With VIVA, users can unleash their creativity and design stunning visuals for various purposes such as social media posts, presentations, and marketing materials. The platform leverages artificial intelligence to streamline the design process and help users achieve professional-looking results without the need for advanced design skills.

ChartFast is an AI Data Analyzer tool that automates data visualization and analysis tasks, powered by GPT-4 technology. It allows users to generate precise and sleek graphs in seconds, process vast amounts of data, and provide interactive data queries and quick exports. With features like specialized internal libraries for complex graph generation, customizable visualization code, and instant data export, ChartFast aims to streamline data work and enhance data analysis efficiency.

Capital Companion is an AI-powered trading and investing platform designed to provide users with a competitive edge in the markets. The platform offers a range of features including 24/7 AI assistant support, intelligent trading recommendations, risk analysis tools, real-time stock analytics, market sentiment analysis, and pattern recognition for technical analysis. By leveraging artificial intelligence, Capital Companion aims to help traders make well-informed decisions and protect their investments in a dynamic market environment.

Floneum is a versatile AI-powered tool designed for language-related tasks. It allows users to build workflows using large language models through a user-friendly drag-and-drop interface. Additionally, Floneum supports the secure extension of functionalities with WebAssembly plugins, enabling users to write plugins in various languages like Rust, C, Java, or Go. With 41 built-in plugins, Floneum offers a range of features to enhance text processing, search engine operations, file handling, Python script execution, browser automation, and more.

Zelma is an AI-powered research assistant that enables users to find, graph, and understand U.S. school testing data using plain English queries. It allows users to search student test data by school district, demographics, grade, and more, and presents the results with graphs, tables, and descriptions. Zelma aims to make education data accessible and understandable for everyone.

Factori is a data intelligence platform designed for an AI-first world, offering a wide range of products and datasets to empower businesses with advanced data insights. It enables users to uncover movement trends, reach customers effectively, drive data-driven insights, personalize experiences, and target the right consumers with unique segments. Factori is trusted by global businesses for all their data requirements, providing high-quality data to improve predictive and causal models.

NOLEJ is an AI-powered platform that helps instructional designers and teachers rapidly generate interactive eLearning material. It can automatically generate interactive content from existing learning materials, such as textbooks, videos, and online media resources. NOLEJ also offers a variety of interactive formats, including interactive videos, flashcards, glossaries, crosswords, drag-and-drop activities, find-the-word puzzles, and interactive books.

Goover is a personalized AI research agent that streamlines the process of acquiring knowledge by providing self-driving experiences. It offers users the ability to dive deeper into various topics through curated briefings, reports, and insights. Goover utilizes advanced AI technology to deliver tailored answers, identify key information, and facilitate meaningful discussions. Users can access knowledge anytime, anywhere through the mobile app, ensuring they stay informed and engaged with their passions. With Goover, users can track specific topics, receive automatic updates, and explore diverse perspectives effortlessly.

Math Sniper is an AI-powered application designed to provide precise math solutions, exam preparation assistance, and exploration of mathematical concepts. The app offers step-by-step solutions to math challenges at all levels, connects users with math tutors for personalized help, and covers a wide range of subjects beyond mathematics, such as biology, chemistry, physics, history, economics, and language tasks. With features like Snap & Ask for instant answers, step-by-step explanations, and a user-friendly interface, Math Sniper aims to enhance users' understanding of complex concepts and facilitate learning in various disciplines.

The Intel® AI Reference Models repository contains links to pre-trained models, sample scripts, best practices, and tutorials for popular open-source machine learning models optimized by Intel to run on Intel® Xeon® Scalable processors and Intel® Data Center GPUs. The purpose is to quickly replicate complete software environments showcasing the AI capabilities of Intel platforms. It includes optimizations for popular deep learning frameworks like TensorFlow and PyTorch, with additional plugins/extensions for improved performance. The repository is licensed under Apache License Version 2.0.

Welcome to the ultimate hub for on-device Large Language Models (LLMs)! This repository is your go-to resource for all things related to LLMs designed for on-device deployment. Whether you're a seasoned researcher, an innovative developer, or an enthusiastic learner, this comprehensive collection of cutting-edge knowledge is your gateway to understanding, leveraging, and contributing to the exciting world of on-device LLMs.

Paper-Reading-ConvAI is a repository that contains a list of papers, datasets, and resources related to Conversational AI, mainly encompassing dialogue systems and natural language generation. This repository is constantly updating.

A comprehensive repository focusing on 'Model Merging in LLMs, MLLMs, and Beyond', providing an exhaustive overview of model merging methods, theories, applications, and future research directions. The repository covers various advanced methods, applications in foundation models, different machine learning subfields, and tasks like pre-merging methods, architecture transformation, weight alignment, basic merging methods, and more.

Awesome-Graph-LLM is a curated collection of research papers exploring the intersection of graph-based techniques with Large Language Models (LLMs). The repository aims to bridge the gap between LLMs and graph structures prevalent in real-world applications by providing a comprehensive list of papers covering various aspects of graph reasoning, node classification, graph classification/regression, knowledge graphs, multimodal models, applications, and tools. It serves as a valuable resource for researchers and practitioners interested in leveraging LLMs for graph-related tasks.

Analyze the following text from a github repository (name and readme text at end) . Then, generate a JSON object with the following keys and provide the corresponding information for each key, in lowercase letters: 'description' (detailed description of the repo, must be less than 400 words，Ensure that no line breaks and quotation marks.),'for_jobs' (List 5 jobs suitable for this tool,in lowercase letters), 'ai_keywords' (keywords of the tool,user may use those keyword to find the tool,in lowercase letters), 'for_tasks' (list of 5 specific tasks user can use this tool to do,in lowercase letters), 'answer' (in english languages)

Awesome-Segment-Anything is a powerful tool for segmenting and extracting information from various types of data. It provides a user-friendly interface to easily define segmentation rules and apply them to text, images, and other data formats. The tool supports both supervised and unsupervised segmentation methods, allowing users to customize the segmentation process based on their specific needs. With its versatile functionality and intuitive design, Awesome-Segment-Anything is ideal for data analysts, researchers, content creators, and anyone looking to efficiently extract valuable insights from complex datasets.

Zep is a long-term memory service for AI Assistant apps. With Zep, you can provide AI assistants with the ability to recall past conversations, no matter how distant, while also reducing hallucinations, latency, and cost. Zep persists and recalls chat histories, and automatically generates summaries and other artifacts from these chat histories. It also embeds messages and summaries, enabling you to search Zep for relevant context from past conversations. Zep does all of this asyncronously, ensuring these operations don't impact your user's chat experience. Data is persisted to database, allowing you to scale out when growth demands. Zep also provides a simple, easy to use abstraction for document vector search called Document Collections. This is designed to complement Zep's core memory features, but is not designed to be a general purpose vector database. Zep allows you to be more intentional about constructing your prompt: 1. automatically adding a few recent messages, with the number customized for your app; 2. a summary of recent conversations prior to the messages above; 3. and/or contextually relevant summaries or messages surfaced from the entire chat session. 4. and/or relevant Business data from Zep Document Collections.

EZKL is a library and command-line tool for doing inference for deep learning models and other computational graphs in a zk-snark (ZKML). It enables the following workflow: 1. Define a computational graph, for instance a neural network (but really any arbitrary set of operations), as you would normally in pytorch or tensorflow. 2. Export the final graph of operations as an .onnx file and some sample inputs to a .json file. 3. Point ezkl to the .onnx and .json files to generate a ZK-SNARK circuit with which you can prove statements such as: > "I ran this publicly available neural network on some private data and it produced this output" > "I ran my private neural network on some public data and it produced this output" > "I correctly ran this publicly available neural network on some public data and it produced this output" In the backend we use the collaboratively-developed Halo2 as a proof system. The generated proofs can then be verified with much less computational resources, including on-chain (with the Ethereum Virtual Machine), in a browser, or on a device.

LLM-Viewer is a tool for visualizing Language and Learning Models (LLMs) and analyzing performance on different hardware platforms. It enables network-wise analysis, considering factors such as peak memory consumption and total inference time cost. With LLM-Viewer, users can gain valuable insights into LLM inference and performance optimization. The tool can be used in a web browser or as a command line interface (CLI) for easy configuration and visualization. The ongoing project aims to enhance features like showing tensor shapes, expanding hardware platform compatibility, and supporting more LLMs with manual model graph configuration.

GOLEM is an open-source AI framework focused on optimization and learning of structured graph-based models using meta-heuristic methods. It emphasizes the potential of meta-heuristics in complex problem spaces where gradient-based methods are not suitable, and the importance of structured models in various problem domains. The framework offers features like structured model optimization, metaheuristic methods, multi-objective optimization, constrained optimization, extensibility, interpretability, and reproducibility. It can be applied to optimization problems represented as directed graphs with defined fitness functions. GOLEM has applications in areas like AutoML, Bayesian network structure search, differential equation discovery, geometric design, and neural architecture search. The project structure includes packages for core functionalities, adapters, graph representation, optimizers, genetic algorithms, utilities, serialization, visualization, examples, and testing. Contributions are welcome, and the project is supported by ITMO University's Research Center Strong Artificial Intelligence in Industry.

Detailed technical diagram and graph assistant

Propagation Analysis over Graphs

I craft PowerShell scripts for Microsoft Graph.

Converts graph triples to clear text, no assumptions.

Specialist in creating diagrams and graphs based on user requests

Japanese patent data graph generator with user engagement

Meet Tech Guru, your go-to AI for data engineering, coding expertise, and graph databases. Combining humor, reliability, and approachability to simplify tech with a personal touch.

Expert in generating and debugging Neo4j code, with explanations on graph database principles.

Maps PM skills to competencies, plots on radar graph.

Diagram creation: flowcharts, mindmaps, UML, chart, PlotUML, workflow, sequence, ERD, database & architecture visualization for code, presentations and documentation. [New] Add a logo or any image to graph diagrams. Easy Download & Edit

Expert in Micro Economics, interprets graphs, explains concepts, avoids direct exam answers.

Educational guide for understanding algebra principles and equations.

IntegriPal: Your friendly integral calculus guide!

Creates schedules, charts, or graphs based on user inputs.

Expert in schema.org, guiding precise use of 'additionalType'.

Provide a hand-drawing or screenshot of your desired plot along with the data and I'll make the plot.

Obsidian wine log assistant with code block outputs

💎 The worlds greatest data analysis tool 💎

Ask: "What graphs can you create from MY pee times data file (.xlsx)?" Show to your Urologist.

Crafts Powerpoint PPT presentations with visuals and graphs