Best Retrieval-Augmented Generation (RAG) Software for Microsoft Excel

Swirl effortlessly integrates with your enterprise applications, offering real-time data access. It enables secure retrieval-augmented generation from your corporate data without storing any information, while functioning effectively within your firewall. Additionally, Swirl can easily link to your proprietary language models. With Swirl Search, your organization gains an innovative solution that delivers rapid access to all necessary information across various data sources. The platform features multiple connectors designed for popular applications and services, allowing for a seamless connection. There’s no need for data migration, as Swirl harmonizes with your existing systems to maintain data security and uphold privacy standards. Tailored specifically for enterprises, Swirl recognizes that transferring data solely for search and AI integration can be costly and inefficient. By offering a federated and unified search experience, Swirl provides a superior alternative for businesses looking to optimize their data utilization. This approach not only enhances productivity but also streamlines the search process across diverse data environments.

FastGPT is a versatile, open-source AI knowledge base platform that streamlines data processing, model invocation, and retrieval-augmented generation, as well as visual AI workflows, empowering users to create sophisticated large language model applications with ease. Users can develop specialized AI assistants by training models using imported documents or Q&A pairs, accommodating a variety of formats such as Word, PDF, Excel, Markdown, and links from the web. Additionally, the platform automates essential data preprocessing tasks, including text refinement, vectorization, and QA segmentation, which significantly boosts overall efficiency. FastGPT features a user-friendly visual drag-and-drop interface that supports AI workflow orchestration, making it simpler to construct intricate workflows that might incorporate actions like database queries and inventory checks. Furthermore, it provides seamless API integration, allowing users to connect their existing GPT applications with popular platforms such as Discord, Slack, and Telegram, all while using OpenAI-aligned APIs. This comprehensive approach not only enhances user experience but also broadens the potential applications of AI technology in various domains.

Supervity offers a suite of AI-powered agents that enable businesses to automate operations and enhance productivity. With capabilities like Agentic Chat and Agentic Voice, Supervity enables businesses to simulate human-like conversations, automate outbound phone calls, and support real-time co-browsing. These agents are designed for seamless integration into enterprise systems, enabling employees to work faster and independently. Whether you're in finance, HR, IT, or customer experience, Supervity’s AI agents can help automate repetitive tasks, improve decision-making, and drive digital adoption.

Entry Point AI serves as a cutting-edge platform for optimizing both proprietary and open-source language models. It allows users to manage prompts, fine-tune models, and evaluate their performance all from a single interface. Once you hit the ceiling of what prompt engineering can achieve, transitioning to model fine-tuning becomes essential, and our platform simplifies this process. Rather than instructing a model on how to act, fine-tuning teaches it desired behaviors. This process works in tandem with prompt engineering and retrieval-augmented generation (RAG), enabling users to fully harness the capabilities of AI models. Through fine-tuning, you can enhance the quality of your prompts significantly. Consider it an advanced version of few-shot learning where key examples are integrated directly into the model. For more straightforward tasks, you have the option to train a lighter model that can match or exceed the performance of a more complex one, leading to reduced latency and cost. Additionally, you can configure your model to avoid certain responses for safety reasons, which helps safeguard your brand and ensures proper formatting. By incorporating examples into your dataset, you can also address edge cases and guide the behavior of the model, ensuring it meets your specific requirements effectively. This comprehensive approach ensures that you not only optimize performance but also maintain control over the model's responses.