MInD Platform logo

MInD Platform

by Machine Intelligence · Since 2019
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Active1+ countriesCloud
Quick facts
VendorMachine Intelligence
Year launched2019
StatusActive
LocationHoránygyöngye utca 102/b., Szigetmonostor, Pest 2015, HU
Countries served1+
Languages24
Integrations1+
Free tierN/A
Free trialN/A
Contact salesYES

About MInD Platform

MInD Platform is a software from Machine Intelligence that enables the potential of AI in industrial processes. It combines machine vision, data analysis, and various services to help unify complex factory measurement processes. The platform includes the MInD Editor, Database service, Brain service, Manager service, and Report service, providing capabilities for efficient problem-solving and process management. With MInD, users can use AI to improve their workflow and improve decision-making based on data-driven insights. This platform is designed to support industrial organizations looking to integrate advanced technologies into their operations. Key capabilities: MInD Editor Database service Brain service Manager service Report service Best for: industrial companies that need to harness AI for process improvement.

The MInD Platform, developed by Machine Intelligence, is a cutting-edge deep learning and artificial intelligence platform designed to streamline the deployment of machine learning models in enterprise environments. At its core, MInD (Machine Intelligence & Deep learning) provides a full-stack solution for model development, training, optimization, and deployment. Its primary focus is on facilitating AI workflows at scale—especially in industries such as healthcare, manufacturing, finance, and logistics—by combining powerful computational tools with user-friendly interfaces and scalable infrastructure. Key features include automated model training, real-time inference capabilities, model versioning, collaborative tools for teams, and integrated data visualization dashboards. When it comes to **user interface and ease of use**, the MInD Platform excels with a sleek, intuitive, and modern UI. Designed with both data scientists and business users in mind, the dashboard presents clean navigation menus, contextual tooltips, and drag-and-drop components for model configuration and data preprocessing. Users can quickly switch between different views such as the data explorer, training workspace, and model evaluation section.

Pros & Cons

Pros
  • Enables users without programming or AI knowledge to develop and deploy AI solutions.
  • Offers an end-to-end solution from data collection to maintenance, simplifying AI implementation.
  • Specifically designed for real-time quality monitoring on industrial production lines, directly addressing a critical business need.
  • Supports deployment on-premise, in the cloud, or on edge devices, accommodating diverse infrastructure requirements.
  • Unique in offering dedicated AI solutions for the complex challenges of the space industry.
Cons
  • While easy to use, the "no programming" aspect might limit deep understanding or customization for highly specialized use cases.
  • Users might become highly dependent on the MInD platform for their AI development and operations.
  • An "end-to-end platform" could imply a non-trivial initial setup and integration process, despite ease of use post-setup.
  • While it mentions cloud and edge deployment, the real-world scalability for extremely large or highly niche industrial operations might need further examination.

Features

Key features

End-to-end AI Development and Deployment

MInD provides a complete platform for developing, deploying, operating, and maintaining AI solutions, from data collection to real-time monitoring on various hardware.

No-Code/Low-Code AI Development

The platform is designed for users without programming or AI knowledge, featuring a "SMART BUILDER" system that suggests automatic solutions.

Real-time Quality Monitoring

MInD excels at generating deep learning models from data and then providing continuous, real-time quality monitoring on production lines.

Hardware Agnostic Deployment (On-premise/Cloud/Edge)

The solutions developed on MInD can be deployed flexibly across computers, cloud infrastructure, or edge devices, and can integrate with various hardware from major manufacturers.

MES Integration

The "Manager" service within MInD maintains a connection with Manufacturing Execution Systems (MES), allowing for seamless data flow and integration into existing factory processes.

Space Industry Solutions

MInD extends its AI capabilities to the space industry with specialized platforms like NEODetect

Additional features

Deployment to Hardware

Enables the deployment of trained AI models to various hardware, including computers, cloud, and edge devices.

Solution Operation and Maintenance

Handles the ongoing operation and maintenance of the deployed AI solutions.

No Programming/AI Knowledge Required

Can be used by individuals without prior programming or artificial intelligence expertise.

SMART BUILDER System

Automatically suggests solutions, simplifying the AI development process.

Manager Service MES Connection

Maintains connectivity with Manufacturing Execution Systems for integrated factory operations.

On-premise or Cloud Deployment

The entire platform can be run locally or in the cloud, offering deployment flexibility.

Deep Learning Model Generation

Capable of creating deep learning models based on measured and saved data.

Real-time Quality Monitoring

Provides continuous monitoring of product quality in real-time.

Machine Intelligence Box (MIB)

A hardware component (though not mandatory) that operates in the field with built-in camera for AI-based decision-making.

Editor

An analysis and AI building tool with a node-based system, featuring annotator and data management capabilities.

Brain

Manages and executes AI pre- and post-processing.

Database

A unit for storing, accessing, and organizing measurement data.

Manager

An application designed to interconnect various services within the MInD platform.

Report

An application that generates documentation summarizing neural network training outcomes.

Image Storage

Stores transmitted images and sends notifications about new images; images can be queried via HTTP.

YAMc (Versatile Client)

Captures data and feeds it to the data monitor system.

Data Monitor

A system for collecting, storing, and visualizing sensor data, metrics, and neural network decisions.

Detector

A subsystem that performs neural network inference on new images in the data stream.

Pricing

Free trial
Free version
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Countries & Languages

1
Countries served
24
Interface languages
13
Billing currencies

Available in

All Countries.

Interface languages

EnglishFrenchGermanSpanishItalianJapaneseChineseKoreanRussianPortugueseDutchPolishTurkishCzechSwedishDanishNorwegianFinnishHungarianSlovenianRomanianGreekThaiIndonesian.

Billing currencies

🇺🇸USD🇪🇺EUR🇬🇧GBP🇯🇵JPY🇦🇺AUD🇨🇦CAD🇨🇭CHF🇨🇳CNY🇸🇪SEK🇮🇳INR🇲🇽MXN🇸🇬SGD🇭🇰HKD

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