Suppliers United States SuperAnnotate

	SuperAnnotate The complete solution for your computer vision products
HQ Location	United States
Year Founded	2018
Company Type	Private
Revenue	< $10m
Employees	51 - 200
Website	Open website

SuperAnnotate

The complete solution for your computer vision products

HQ Location

United States

Year Founded

2018

Company Type

Private

Revenue

< $10m

Employees

51 - 200

Website

Open website

Company Description	SuperAnnotate is a comprehensive solution where you have the flexibility to perform a variety of tasks all in one place. Our advanced and intuitive image, text, and video annotation services support projects of all sizes across various industries, from autonomous vehicles and medical imaging to security and surveillance. Read More
Contents

Company Description

SuperAnnotate is a comprehensive solution where you have the flexibility to perform a variety of tasks all in one place.

Our advanced and intuitive image, text, and video annotation services support projects of all sizes across various industries, from autonomous vehicles and medical imaging to security and surveillance.

SuperAnnotate’s Technology Stack maps SuperAnnotate’s participation in the IoT technology stack.

Application Layer
Functional Applications

Cloud Layer
Platform as a Service

Infrastructure as a Service

Edge Layer
Automation & Control

Processors & Edge Intelligence

Actuators

Sensors

Devices Layer
Robots

Drones

Wearables

Supporting Technologies
Analytics & Modeling

Application Infrastructure & Middleware

Cybersecurity & Privacy

Networks & Connectivity

Technological Capability

None

Minor

Moderate

Strong

Number of Podcasts1

EP 139 - How to efficiently convert raw data into high-value training data for Al - Tigran Pe trosyan, Co-Founder & CEO, SuperAnnotate

Friday, Jul 29, 2022

Data annotation is the hidden champion of machine learning. It is the process of tagging image, video, text, and other data in order to prepare it for training a model. The quality of your data annotation makes the difference between insight and noise.

In this week’s episode, we interview Tigran Petrosyan, co-founder & CEO of SuperAnnotate. We discuss how to manage and scale your annotation workflow, quickly spot quality issues in your data, and seamlessly integrate new data sets into your existing pipeline. We also explore how specialized agencies and AI are collaborating to accurately tag the high volume of data that AI training requires.

Key questions:

How to manage the key steps of the annotation process - annotate, manage, automate, curate, and integrate?
How can you deliver ML projects faster without compromising on quality?
How should you balance the efforts of internal teams, freelancers, and automated tagging to achieve the right cost structure and performance?

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Overview

SuperAnnotate

IoT Snapshot

Technology Stack

Podcasts