Find and compare the best Artificial Intelligence software for Firecrawl in 2024
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Use the comparison tool below to compare the top Artificial Intelligence software for Firecrawl on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.
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Google Cloud Platform
Google
Free ($300 in free credits) 55,132 RatingsGoogle Cloud is an online service that lets you create everything from simple websites to complex apps for businesses of any size. Customers who are new to the system will receive $300 in credits for testing, deploying, and running workloads. Customers can use up to 25+ products free of charge. Use Google's core data analytics and machine learning. All enterprises can use it. It is secure and fully featured. Use big data to build better products and find answers faster. You can grow from prototypes to production and even to planet-scale without worrying about reliability, capacity or performance. Virtual machines with proven performance/price advantages, to a fully-managed app development platform. High performance, scalable, resilient object storage and databases. Google's private fibre network offers the latest software-defined networking solutions. Fully managed data warehousing and data exploration, Hadoop/Spark and messaging. -
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OpenAI's mission, which is to ensure artificial general intelligence (AGI), benefits all people. This refers to highly autonomous systems that outperform humans in most economically valuable work. While we will try to build safe and useful AGI, we will also consider our mission accomplished if others are able to do the same. Our API can be used to perform any language task, including summarization, sentiment analysis and content generation. You can specify your task in English or use a few examples. Our constantly improving AI technology is available to you with a simple integration. These sample completions will show you how to integrate with the API.
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Claude is an artificial intelligence language model that can generate text with human-like processing. Anthropic is an AI safety company and research firm that focuses on building reliable, interpretable and steerable AI systems. While large, general systems can provide significant benefits, they can also be unpredictable, unreliable and opaque. Our goal is to make progress in these areas. We are currently focusing on research to achieve these goals. However, we see many opportunities for our work in the future to create value both commercially and for the public good.
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Hugging Face
Hugging Face
$9 per monthAutoTrain is a new way to automatically evaluate, deploy and train state-of-the art Machine Learning models. AutoTrain, seamlessly integrated into the Hugging Face ecosystem, is an automated way to develop and deploy state of-the-art Machine Learning model. Your account is protected from all data, including your training data. All data transfers are encrypted. Today's options include text classification, text scoring and entity recognition. Files in CSV, TSV, or JSON can be hosted anywhere. After training is completed, we delete all training data. Hugging Face also has an AI-generated content detection tool. -
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Flowise
Flowise
FreeFlowise is open source and will always be free to use for commercial and private purposes. Build LLMs apps easily with Flowise, an open source UI visual tool to build your customized LLM flow using LangchainJS, written in Node Typescript/Javascript. Open source MIT License, see your LLM applications running live, and manage component integrations. GitHub Q&A using conversational retrieval QA chains. Language translation using LLM chains with a chat model and chat prompt template. Conversational agent for chat model that uses chat-specific prompts. -
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Composio
Composio
$49 per monthComposio is a platform for integration that enhances AI agents and Large Language Models by providing seamless connections with over 150 tools. It supports a variety of agentic frameworks, LLM providers and function calling for efficient task completion. Composio provides a wide range of tools including GitHub and Salesforce, file management and code execution environments. This allows AI agents to perform a variety of actions and subscribe to different triggers. The platform offers managed authentication that allows users to manage authentication processes for users and agents through a central dashboard. Composio's core features include a developer first integration approach, built in authentication management, and an expanding catalog with over 90 ready to connect tools. It also includes a 30% reliability increase through simplified JSON structure and improved error handling. -
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Dify
Dify
Your team can develop AI applications using models such as GPT-4, and operate them visually. You can deploy your application within 5 minutes, whether it is for internal team use or an external release. Using documents/webpages/Notion content as the context for AI, automatically complete text preprocessing, vectorization and segmentation. No need to learn embedding methods anymore. This will save you weeks of development. Dify offers a smooth user experience for model access and context embedding. It also provides cost control, data annotation, and cost control. You can easily create AI apps for internal team use, or product development. Start with a prompt but go beyond its limitations. Dify offers rich functionality in many scenarios. -
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LLaMA
Meta
LLaMA (Large Language Model meta AI) is a state of the art foundational large language model that was created to aid researchers in this subfield. LLaMA allows researchers to use smaller, more efficient models to study these models. This furtherdemocratizes access to this rapidly-changing field. Because it takes far less computing power and resources than large language models, such as LLaMA, to test new approaches, validate other's work, and explore new uses, training smaller foundation models like LLaMA can be a desirable option. Foundation models are trained on large amounts of unlabeled data. This makes them perfect for fine-tuning for many tasks. We make LLaMA available in several sizes (7B-13B, 33B and 65B parameters), and also share a LLaMA card that explains how the model was built in line with our Responsible AI practices.
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