Build your
Vision Intelligence Assistant

We envision a future where vision-aided digital assistants support individuals through the complexities of work

Vision Intelligence models for Your Business Needs

Operating Procedures

Store your physical procedures in one place to collect knowledge and make training smooth and interactive

Unstructured to structured

Upload any format: video, text, audio. Our platform will turn it into a structured format, readable by anyone

Live Vision Intelligence

Execute and get real-time feedback on correctness and quality along the assembly line

The ultimate way to collect and learn tasks

Our algorithm can learn and store physical procedures in multimodal ways, guiding workers on any task while seeing what is happening

Add a new procedure

Upload just one video. Our algorithm will help you structure the procedure in various formats

Add a new procedure

Upload just one video. Our algorithm will help you structure the procedure in various formats

View Stored Procedures

Workers can visualize stored procedures in multimodal ways, from textual to illustrative

View Stored Procedures

Workers can visualize stored procedures in multimodal ways, from textual to illustrative

Execute Live!

Our Vision Intelligence can guide you through the procedure while seeing what is happening

Execute Live!

Our Vision Intelligence can guide you through the procedure while seeing what is happening

Powered by Research

Compositional Entailment Learning for Hyperbolic Vision-Language Models

HyCoCLIP further captures the intrinsic relationships between objects within an image and the corresponding words in a sentence, pushing the boundaries of vision-language learning.

Learn More

PREGO: Online mistake detection in
PRocedural EGOcentric videos

Promptly identifying procedural errors from egocentric videos in an online setting is highly challenging and valuable for detecting mistakes as soon as they happen.

Learn More

Multimodal motion conditioned diffusion model for skeleton-based video anomaly detection

Novel generative model for video anomaly detection (VAD), which assumes that both normality and abnormality are multimodal.

Learn More

Build your
Vision Intelligence Assistant

Build your
Vision Intelligence Assistant

We envision a future where vision-aided digital assistants support individuals through the complexities of work

We envision a future where vision-aided digital assistants support individuals through the complexities of work

Operating Procedures

Operating Procedures

Operating Procedures

Unstructured to structured

Unstructured to structured

Unstructured to structured

Live Vision Intelligence

Live Vision Intelligence

Live Vision Intelligence

The ultimate way to collect and learn tasks

The ultimate way to collect and learn tasks

Add a new procedure

Add a new procedure

View Stored Procedures

View Stored Procedures

Execute Live!

Execute Live!

Powered by Research

Powered by Research

Compositional Entailment Learning for Hyperbolic Vision-Language Models

Compositional Entailment Learning for Hyperbolic Vision-Language Models

Compositional Entailment Learning for Hyperbolic Vision-Language Models

HyCoCLIP further captures the intrinsic relationships between objects within an image and the corresponding words in a sentence, pushing the boundaries of vision-language learning.

PREGO: Online mistake detection in
PRocedural EGOcentric videos

PREGO: Online mistake detection in
PRocedural EGOcentric videos

PREGO: Online mistake detection in
PRocedural EGOcentric videos

Promptly identifying procedural errors from egocentric videos in an online setting is highly challenging and valuable for detecting mistakes as soon as they happen.

Multimodal motion conditioned diffusion model for skeleton-based video anomaly detection

Multimodal motion conditioned diffusion model for skeleton-based video anomaly detection

Multimodal motion conditioned diffusion model for skeleton-based video anomaly detection

Novel generative model for video anomaly detection (VAD), which assumes that both normality and abnormality are multimodal.

Supported by

Supported by

Operating Procedures

Operating Procedures

Operating Procedures

Unstructured to structured

Unstructured to structured

Unstructured to structured

Live Vision Intelligence

Live Vision Intelligence

Live Vision Intelligence

The ultimate way to collect and learn tasks

The ultimate way to collect and learn tasks

Add a new procedure

Add a new procedure

View Stored Procedures

View Stored Procedures

Execute Live!

Execute Live!

Powered by Research

Powered by Research

Compositional Entailment Learning for Hyperbolic Vision-Language Models

Compositional Entailment Learning for Hyperbolic Vision-Language Models

Compositional Entailment Learning for Hyperbolic Vision-Language Models

HyCoCLIP further captures the intrinsic relationships between objects within an image and the corresponding words in a sentence, pushing the boundaries of vision-language learning.

PREGO: Online mistake detection inPRocedural EGOcentric videos

PREGO: Online mistake detection inPRocedural EGOcentric videos

PREGO: Online mistake detection inPRocedural EGOcentric videos

Promptly identifying procedural errors from egocentric videos in an online setting is highly challenging and valuable for detecting mistakes as soon as they happen.

Multimodal motion conditioned diffusion model for skeleton-based video anomaly detection

Multimodal motion conditioned diffusion model for skeleton-based video anomaly detection

Multimodal motion conditioned diffusion model for skeleton-based video anomaly detection

Novel generative model for video anomaly detection (VAD), which assumes that both normality and abnormality are multimodal.

Supported by

Supported by

PREGO: Online mistake detection in
PRocedural EGOcentric videos

PREGO: Online mistake detection in
PRocedural EGOcentric videos

PREGO: Online mistake detection in
PRocedural EGOcentric videos