Our Favourite AI Tools
Welcome to our curated list of favourite AI tools. This resource highlights a variety of products—from model providers and application frameworks to low-code solutions, observability platforms, evaluation tools, and developer utilities—that empower teams to build, deploy, and maintain advanced AI solutions. Each section provides a brief overview of the tool along with relevant links for further exploration and quick-start resources.
For foundational AI model providers specializing in language, vision, or multimodal models.
Founded in 2021 by former OpenAI executives Dario and Daniela Amodei, Anthropic is an AI safety and research company based in San Francisco. The company focuses on developing reliable and interpretable AI systems with a strong emphasis on safety and ethical considerations. Their interdisciplinary team includes experts in machine learning, physics, policy, and product development, all collaborating to create beneficial AI technologies.
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One of Anthropic's flagship products is Claude, a large language model designed to assist with various tasks, including coding and complex problem-solving. Claude incorporates "Constitutional AI," a framework developed to align AI systems with human values—ensuring outputs are helpful, harmless, and honest.
Learn more on Wikipedia
In recent developments, Anthropic is finalizing a $3.5 billion funding round, which would value the company at $61.5 billion. This investment underscores the growing confidence in Anthropic's approach to ethical AI development.
Read the Reuters report
Getting Started with Anthropic:
Platforms that enable building AI-powered applications or workflows.
LangChain is an open-source framework designed to facilitate the development of applications powered by large language models (LLMs). It provides developers with tools and abstractions necessary for building context-aware, reasoning applications that effectively leverage company data and APIs.
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The framework streamlines every stage of the LLM application lifecycle—from prototyping to deployment. Its flexible architecture supports customization, allowing developers to tailor applications to specific use cases and data sources.
Read the Documentation
Developers can also access extensive guides, tutorials, and community support through LangChain's GitHub repository, making it a versatile resource for creating intelligent systems.
Visit LangChain on GitHub
Getting Started with LangChain:
Tools that make AI more accessible to non-technical users through simplified interfaces.
LangFlow is a low-code platform designed to democratize AI development by enabling users to create AI agents and workflows without extensive programming knowledge. Its visual interface allows for seamless integration of various APIs, models, and databases, streamlining the process of building AI-powered applications.
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The platform provides a range of pre-built components and templates that facilitate rapid prototyping and deployment. This empowers users to develop tailored applications across various industries while reducing development time and costs.
Getting Started with LangFlow:
Zapier is a widely used automation platform that connects different applications and services, enabling users to create automated workflows—known as "Zaps"—without any coding. It integrates with numerous AI models and tools, allowing for the seamless inclusion of AI functionalities into everyday workflows.
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By supporting a vast ecosystem of applications, Zapier makes it easy to set up triggers and actions between apps. This ensures consistency in automated tasks and reduces the potential for human error, ultimately enhancing productivity and efficiency.
Getting Started with Zapier:
Solutions that help evaluate, track, debug, and optimize AI systems in production.
Comet is a comprehensive platform offering tools for tracking, debugging, and optimizing machine learning models throughout their lifecycle. With features such as experiment tracking, model monitoring, and data visualization, it provides data scientists and engineers deep insights into model performance.
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The platform also offers real-time monitoring and alerting, which ensures that AI systems operate as intended by promptly identifying and resolving issues. Its collaborative features allow teams to share experiments, insights, and reports, fostering a culture of transparency and continuous improvement.
Getting Started with Comet:
Opik is a monitoring and debugging platform from Comet, designed to provide comprehensive insights into AI systems. Effective monitoring tools should offer real-time visibility, anomaly detection, and seamless integration with existing workflows—Opik delivers on all these fronts.
With Opik, you can log, view, and evaluate your LLM (Large Language Model) traces during both development and production. The platform, combined with LLM-as-a-Judge evaluators, helps you identify and resolve issues in your LLM applications efficiently.
Getting Started with Opik:
Products designed to streamline the AI development lifecycle, from prototyping to debugging and performance tuning.
Vercel v0 is an experimental, AI-enhanced version of Vercel's deployment platform, tailored specifically for developers working on AI-driven applications. It integrates state-of-the-art performance tuning and debugging tools into the development workflow, allowing developers to deploy applications with optimal speed and efficiency.
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This tool focuses on automating parts of the deployment process and providing real-time performance insights, which can help reduce development time and minimize manual tuning. With its seamless integration into existing development environments, Vercel v0 supports rapid prototyping and iterative improvement for AI applications.
Additionally, Vercel v0 offers detailed analytics and logs that enable developers to quickly identify and resolve performance bottlenecks, ensuring that AI-powered applications run smoothly in production. Its innovative approach makes it a valuable asset for teams looking to optimize their deployment lifecycle.
Getting Started with Vercel v0:
Replit Agents are AI-powered assistants integrated into the Replit online coding environment, designed to streamline the entire development lifecycle. These agents assist developers by automating routine coding tasks, suggesting improvements, and even debugging code in real time—all directly within the IDE.
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By leveraging machine learning, Replit Agents analyze code and provide contextual recommendations, helping to reduce development time and improve code quality. They are especially useful for rapid prototyping, where quick iterations and debugging are essential for success.
Replit Agents also support collaborative coding by offering insights and suggestions that can be shared across teams, making them an invaluable tool for modern software development workflows that require both efficiency and accuracy.
Getting Started with Replit Agents:
NotebookLM is an AI-powered research and note-taking assistant developed by Google Labs. Designed to help users make sense of complex information, it grounds its responses in the sources you upload, such as documents, PDFs, and Google Slides, providing citations and relevant quotes for accuracy. Learn about NotebookLM on the Google AI Blog
One of its latest features, Audio Overview, transforms text-based sources into engaging, AI-generated discussions. With just one click, two virtual hosts summarize your material, make insightful connections, and present the content in a conversational format. The audio can even be downloaded, allowing users to listen on the go.
Getting Started with NotebookLM: