E5 Text EmbeddingsMicrosoft
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Related Products
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About
AfterQuery is an applied research platform designed to create high-quality training data for frontier artificial intelligence models by capturing how real experts think, reason, and solve problems in professional contexts. It focuses on transforming real-world work into structured datasets that go beyond simple outputs, encoding decision-making processes, tradeoffs, and contextual reasoning that traditional internet-sourced data cannot provide. It works directly with domain experts to generate supervised fine-tuning data, including prompt–response pairs and detailed reasoning traces, as well as reinforcement learning datasets with expert-designed prompts and grading frameworks that convert subjective judgment into scalable reward signals. It also builds custom agent environments across APIs and tools, enabling models to be trained and evaluated in realistic workflows, and captures computer-use trajectories that demonstrate how humans interact with software step by step.
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About
E5 Text Embeddings, developed by Microsoft, are advanced models designed to convert textual data into meaningful vector representations, enhancing tasks like semantic search and information retrieval. These models are trained using weakly-supervised contrastive learning on a vast dataset of over one billion text pairs, enabling them to capture intricate semantic relationships across multiple languages. The E5 family includes models of varying sizes—small, base, and large—offering a balance between computational efficiency and embedding quality. Additionally, multilingual versions of these models have been fine-tuned to support diverse languages, ensuring broad applicability in global contexts. Comprehensive evaluations demonstrate that E5 models achieve performance on par with state-of-the-art, English-only models of similar sizes.
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Audience
AI researchers, developers, and enterprises building advanced models who need high-quality, expert-driven training data to improve reasoning and real-world task performance
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Audience
E5 Text Embeddings are designed for AI researchers, machine learning engineers, and developers seeking high-quality text representations for applications like semantic search, information retrieval, and multilingual NLP tasks
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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API
Offers API
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API
Offers API
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Screenshots and Videos |
Screenshots and VideosNo images available
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Pricing
No information available.
Free Version
Free Trial
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Pricing
Free
Free Version
Free Trial
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Reviews/
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Reviews/
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Company InformationAfterQuery
Founded: 2025
United States
www.afterquery.com
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Company InformationMicrosoft
Founded: 1975
United States
github.com/microsoft/unilm/tree/master/e5
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Categories |
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Integrations
Model Context Protocol (MCP)
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