AI Agents

Powering the world's leading AI teams

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Tractable new logo
Voxel Logo
CedarsSuniai
Iterative Health
Stanford Medicine logo
Flock safety logo
Philips Logo - coloured

Workflows

Set up streamlined data workflows to enable faster and more accurate data labeling

Build multi-step workflows that unite AI models, labeling teams, and reviewers to produce high-quality labeled data. Maintain visibility of annotation progress across multiple teams.

No-code workflow builder to set up data workflows

Add desired stages to your labeling workflow. Select from annotate, review, consensus, webhooks, and various routers to configure your workflows.

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Custom pathways with advanced routers

Use Encord SDK to set up workflows

Use Encord Agents to automatically pre-label data

Integrate with Claude-3, GPT-4o and more foundational models directly within Encord's Label Editor to pre-label data in bulk and speed up annotators' workflows.

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Use Agents within the Label Editor to accelerate labeling and prepare accurately labeled data even faster.

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Trigger any Agent on your data to automatically pre-classify data to speed up annotators' efforts.

Customize data workflows with Encord Agents

Integrate SOTA models or your own models directly into your data workflows to automate any data action such as reviews, pre-labeling, data classification, filtering and more.

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Models

Use Encord Agents to integrate any SOTA Foundational Model into your data workflow

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GPT-4o

Open AI’s new flagship model which can reason and generate content across audio, vision, and text in real time. For data pipelines, it can analyze unstructured data and generate contextual labels, enrich metadata, or automate multimodal annotation tasks.

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DINOv

A self-supervised computer vision model that uses the Vision Transformer (ViT) architecture to perform image and pixel-level visual tasks such as image classification, video understanding, and depth estimation.

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Gemini Pro and Flash 1.5

Models developed by Google that can process text, images, audio and video. Use the model to reason across different modalities to generate text, answer questions and analyze various data.

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Claude3-Opus

AI model from Anthropic that is designed to handle complex tasks, such as research, analysis, and task automation. It can process and analyze images, including charts, graphs, technical diagrams, and optical character recognition (OCR).

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Open AI Whisper

Automatic speech recognition (ASR) model developed by OpenAI. It can accurately transcribe speech into text across multiple languages and dialects, even in noisy environments. Whisper is trained on a massive dataset of diverse audio clips.

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LLaMa 3.2

More accurate and coherent than LLaMa 3.1, Meta's updated model 3.2 introduces vision-based models, allowing it to process and generate text based on images. This is a major advancement, enabling new applications like image captioning and image-based question answering. LLaMa 3.2 is also multilingual and performs well in text based tasks.

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LLaVa

A multimodal foundation model that excels at tasks involving both text and images. It has been trained on a large dataset of paired text and image data, allowing it to understand the relationship between language and visual content.

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BERT

Bidirectional Encoder Representations from Transformers, understands context, widely used in NLP tasks.

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T5

Text-to-Text Transfer Transformer, translates, summarizes, and generates text.

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GPT-4o

Open AI’s new flagship model which can reason and generate content across audio, vision, and text in real time. For data pipelines, it can analyze unstructured data and generate contextual labels, enrich metadata, or automate multimodal annotation tasks.

avatar
DINOv

A self-supervised computer vision model that uses the Vision Transformer (ViT) architecture to perform image and pixel-level visual tasks such as image classification, video understanding, and depth estimation.

avatar
Gemini Pro and Flash 1.5

Models developed by Google that can process text, images, audio and video. Use the model to reason across different modalities to generate text, answer questions and analyze various data.

avatar
Claude3-Opus

AI model from Anthropic that is designed to handle complex tasks, such as research, analysis, and task automation. It can process and analyze images, including charts, graphs, technical diagrams, and optical character recognition (OCR).

avatar
Open AI Whisper

Automatic speech recognition (ASR) model developed by OpenAI. It can accurately transcribe speech into text across multiple languages and dialects, even in noisy environments. Whisper is trained on a massive dataset of diverse audio clips.

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LLaMa 3.2

More accurate and coherent than LLaMa 3.1, Meta's updated model 3.2 introduces vision-based models, allowing it to process and generate text based on images. This is a major advancement, enabling new applications like image captioning and image-based question answering. LLaMa 3.2 is also multilingual and performs well in text based tasks.

avatar
LLaVa

A multimodal foundation model that excels at tasks involving both text and images. It has been trained on a large dataset of paired text and image data, allowing it to understand the relationship between language and visual content.

avatar
BERT

Bidirectional Encoder Representations from Transformers, understands context, widely used in NLP tasks.

avatar
T5

Text-to-Text Transfer Transformer, translates, summarizes, and generates text.

Agents

Create Agents to accelerate your data annotation workflows

Automate any action to be taken on your data, from data filtering and sorting to more efficient and robust quality control.

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Automatically filter data before labeling
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Smart routing for optimizing annotation resources
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Minimize the burden on human reviewers

Leverage Encord Agents to customize your data workflows

To learn how to automate any part of your data workflow, discuss your use case with our ML team and find out how to achieve the most efficient data workflow.

Why Encord?

Join the thousands of teams deploying production-ready AI applications with best-in-class data curation, labeling, and model evaluation tooling with Encord.

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20% increase in mAP with intelligent data curation

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60% increase in labeling speed by simplifying data pipelines

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83% reduction in false positive rates with specialized data management.