Ango Hub
Ango Hub is an all-in-one, quality-oriented data annotation platform that AI teams can use. Ango Hub is available on-premise and in the cloud. It allows AI teams and their data annotation workforces to quickly and efficiently annotate their data without compromising quality.
Ango Hub is the only data annotation platform that focuses on quality. It features features that enhance the quality of your annotations. These include a centralized labeling system, a real time issue system, review workflows and sample label libraries. There is also consensus up to 30 on the same asset.
Ango Hub is versatile as well. It supports all data types that your team might require, including image, audio, text and native PDF. There are nearly twenty different labeling tools that you can use to annotate data. Some of these tools are unique to Ango hub, such as rotated bounding box, unlimited conditional questions, label relations and table-based labels for more complicated labeling tasks.
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Pipedrive
Pipedrive is a powerful CRM and sales pipeline management platform designed to help businesses track and optimize their sales processes. The platform offers automation tools, AI-powered sales insights, and real-time reporting to help businesses close deals faster and more effectively. With customizable workflows, integrations with a wide range of apps, and an intuitive interface, Pipedrive supports sales teams of all sizes in managing leads, automating repetitive tasks, and monitoring performance for smarter, data-driven decisions.
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prompteasy.ai
Now you have the opportunity to fine-tune GPT without any technical expertise required. By customizing AI models to suit your individual requirements, you can enhance their capabilities effortlessly. With Prompteasy.ai, fine-tuning AI models takes just seconds, streamlining the process of creating personalized AI solutions. The best part is that you don't need to possess any knowledge of AI fine-tuning; our sophisticated models handle everything for you. As we launch Prompteasy, we are excited to offer it completely free of charge initially, with plans to introduce pricing options later this year. Our mission is to democratize AI, making it intelligent and accessible to everyone. We firmly believe that the real potential of AI is unlocked through the way we train and manage foundational models, rather than merely utilizing them as they come. You can set aside the hassle of generating extensive datasets; simply upload your relevant materials and engage with our AI using natural language. We will take care of constructing the dataset needed for fine-tuning, allowing you to simply converse with the AI, download the tailored dataset, and enhance GPT at your convenience. This innovative approach empowers users to harness the full capabilities of AI like never before.
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Entry Point AI
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.
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