ScrapeGraphAI

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ScrapeGraphAI is a groundbreaking Python library that integrates Large Language Models (LLMs) with graph-based workflows to streamline web scraping. It automates the process of extracting data from websites and different file formats, adjusting to modifications in website structures without the need for manual updates. This tool is ideal for developers, researchers, businesses, and content creators in search of efficient, flexible web scraping solutions. Users may opt for ScrapeGraphAI due to its ease of use, adaptability, efficiency, and versatility in managing complex data extraction tasks across various sources and formats.

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Inari is an AI-driven platform designed for customer feedback management, enabling teams to automate the processes of feedback analysis, generating insights, and managing backlogs. It consolidates both unstructured and structured customer feedback into a single hub, offering an efficient workflow for handling the data. The tool automatically assesses customer sentiment and highlights key requests, issues, praise, and insights obtained from user interviews. Inari also uncovers product insights, visualizes trends in real-time, and allows users to directly associate customers with requests, questions, behaviors, and other insights. Moreover, Inari can send insights, summaries, and backlog requests directly to applications like Slack, JIRA, and Linear.
Freemium
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Briefy, an AI-driven tool, swiftly condenses long texts, audio, and video content into clear, well-organized summaries with a single click. It is currently under development and will be released shortly.
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Fiddler AI is a platform focused on AI Observability and Security, assisting organizations in overseeing, analyzing, clarifying, and enhancing their machine learning models and AI applications. It provides real-time monitoring, explainable AI features, and tools to identify issues such as data drift, performance decline, and bias. Organizations may leverage Fiddler AI to ensure model transparency, tackle potential issues before deployment, enhance customer experience, comply with AI governance standards, and derive actionable insights into model behavior. This all-encompassing solution is especially beneficial for data science, MLOps, engineering, and security teams aiming to establish trust, safety, and security in their AI implementations.