Question: I'm looking for a platform that helps me build and evaluate high-performing AI models using high-quality training data.

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SuperAnnotate

For training and testing high-performing AI models with high-quality training data, SuperAnnotate is a great option. It's an end-to-end platform for training, testing, and deploying LLM, CV, and NLP models with high-quality data. The platform pulls data from local and cloud storage, offers a customizable interface, and comes with advanced tools for creating datasets, testing models, and deploying to multiple environments. With a global marketplace of vetted annotation teams and robust data security controls, SuperAnnotate can accelerate AI development while ensuring quality and accuracy.

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Appen

Another top option is Appen, which offers high-quality, diverse data for foundation models and enterprise-ready AI applications. With human feedback and collaboration built in, Appen's platform supports a wide range of data types, including text, images, audio and video. It offers customizable workflows, built-in quality control, and flexible deployment options, making it a trusted option for gathering, curating and fine-tuning data for traditional machine learning and generative AI applications.

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Dataloop

Dataloop is an all-in-one AI development platform that combines data curation, model management, pipeline orchestration, and human feedback to accelerate AI application development. It includes automated preprocessing and embeddings for similarity detection, supports a wide range of unstructured data types, and offers strong security controls. Dataloop is designed to improve collaboration, speed up development, and ensure high quality and security, and offers a lot of value with its suite of tools and integrations.

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HoneyHive

For those who need to evaluate and test AI, HoneyHive is a mission-critical platform for testing, observing and evaluating GenAI applications. It includes automated CI testing, production pipeline monitoring, dataset curation, and human feedback collection. With support for more than 100 models and integration with popular GPU clouds, HoneyHive is great for teams that need to debug, evaluate user feedback and optimize their AI models quickly.

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Deepchecks

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Humanloop

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Clarifai

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Gretel Navigator

Generates realistic tabular data from scratch, edits, and augments existing datasets, improving data quality and security for AI training and testing.

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Openlayer

Build and deploy high-quality AI models with robust testing, evaluation, and observability tools, ensuring reliable performance and trustworthiness in production.

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Scale

Provides high-quality, cost-effective training data for AI models, improving performance and reliability across various industries and applications.

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Klu

Streamline generative AI application development with collaborative prompt engineering, rapid iteration, and built-in analytics for optimized model fine-tuning.

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Dataiku

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Airtrain AI

Experiment with 27+ large language models, fine-tune on your data, and compare results without coding, reducing costs by up to 90%.

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Braintrust

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ThirdAI

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V7

Automates machine learning development tasks, including image and video labeling, to accelerate product delivery and reduce labeling costs by up to 80%.

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Google AI

Unlock AI-driven innovation with a suite of models, tools, and resources that enable responsible and inclusive development, creation, and automation.

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Athina

Experiment, measure, and optimize AI applications with real-time performance tracking, cost monitoring, and customizable alerts for confident deployment.

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LLMStack

Build sophisticated AI applications by chaining multiple large language models, importing diverse data types, and leveraging no-code development.

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Stability AI

Democratize access to powerful AI models across various formats, including images, videos, audio, and language, with flexible membership options.