Vertex AI
Fully managed ML tools allow you to build, deploy and scale machine-learning (ML) models quickly, for any use case.
Vertex AI Workbench is natively integrated with BigQuery Dataproc and Spark. You can use BigQuery to create and execute machine-learning models in BigQuery by using standard SQL queries and spreadsheets or you can export datasets directly from BigQuery into Vertex AI Workbench to run your models there. Vertex Data Labeling can be used to create highly accurate labels for data collection.
Vertex AI Agent Builder empowers developers to design and deploy advanced generative AI applications for enterprise use. It supports both no-code and code-driven development, enabling users to create AI agents through natural language prompts or by integrating with frameworks like LangChain and LlamaIndex.
Learn more
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.
Learn more
Dataocean AI
DataOcean AI stands out as a premier provider of meticulously labeled training data and extensive AI data solutions, featuring an impressive array of over 1,600 pre-made datasets along with countless tailored datasets specifically designed for machine learning and artificial intelligence applications. Their diverse offerings encompass various modalities, including speech, text, images, audio, video, and multimodal data, effectively catering to tasks such as automatic speech recognition (ASR), text-to-speech (TTS), natural language processing (NLP), optical character recognition (OCR), computer vision, content moderation, machine translation, lexicon development, autonomous driving, and fine-tuning of large language models (LLMs). By integrating AI-driven methodologies with human-in-the-loop (HITL) processes through their innovative DOTS platform, DataOcean AI provides a suite of over 200 data-processing algorithms and numerous labeling tools to facilitate automation, assisted labeling, data collection, cleaning, annotation, training, and model evaluation. With nearly two decades of industry experience and a presence in over 70 countries, DataOcean AI is committed to upholding rigorous standards of quality, security, and compliance, effectively serving more than 1,000 enterprises and academic institutions across the globe. Their ongoing commitment to excellence and innovation continues to shape the future of AI data solutions.
Learn more
OCI Data Labeling
OCI Data Labeling is a powerful tool designed for developers and data scientists to create precisely labeled datasets essential for training AI and machine learning models. This service accommodates various formats, including documents (such as PDF and TIFF), images (like JPEG and PNG), and text, enabling users to upload unprocessed data, apply various annotations—such as classification labels, object-detection bounding boxes, or key-value pairs—and then export the annotated results in line-delimited JSON format, which facilitates smooth integration into model-training processes. It also provides customizable templates tailored for different annotation types, intuitive user interfaces, and public APIs for efficient dataset creation and management. Additionally, the service ensures seamless interoperability with other data and AI services, allowing for the direct feeding of annotated data into custom vision or language models, as well as Oracle's AI offerings. Users can leverage OCI Data Labeling to generate datasets, create records, annotate them, and subsequently utilize the exported snapshots for effective model development, ensuring a streamlined workflow from data labeling to AI model training. Consequently, the service enhances the overall productivity of teams focusing on AI initiatives.
Learn more
