Enter the platform here

LEARNING

IMPACT

INDICATOR

TECHNOLOGY

making sense of big data

See the big picture behind the big data

who we are?

WHat it is?

A big data platform to work with indicators, to conceal the big data complexity behind compact indicators. You can create and set up any type of indicator; list, model or learning indicators, via machine learning and neural network technology.

LEIMINTE is currently extended to cope also with real-time data series. Data can be uploaded via file uploads or APIs (suitable for real time data)

How?

Your data is organized in projects; you can then

set up indicators and use your project data to calculate and report upon them; the indicators can be calculated based on lists or models that you will set up
run flexible machine learning training and classifications on your data, mapping them on classes/ labels you will define
combine both above, i.e., calculate your indicator values based on your lists or models, and run machine learning training/ classifications on the indicators

LEIMINTE is based on the TensorFlow open-source neural network technology. It provides a user interface to TensorFlow, allowing you to organize your work with your data.

See Solutions below for practical examples.

SOLUTIONS

Standard compliance

Providing data support for standard compliance (a model indicator based project) EUROPEAID PROJECT

Data management for CSR (Corporate Social Responsibility), EMAS (Environmental Management and Audit Scheme), and HCMI (Hotel Carbon Measurement Initiative)

Company segmentation

Company segmentation with regard to the innovation potential for public funding authorities (a ML classification based project) HORIZON PROJECT

See video

Risk assessment

Venture capital innovation funding risk classification (a ML classification based project) PRIVATE CLIENT

See video

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NEWS & events

Entreprise Standard Documentation Support

A model for sustainable tourism in Central Asia: Building Capacities, Creating Awareness, Introducing technology; a EuropeAid project

LEIMINTE is currently deployed in 360 tourism enterprises in Central Asia countries to support their documentation for CSR (Corporate Social Responsibility), EMAS (Environmental Management and Audit Scheme), and HCMI (Hotel Carbon Measurement Initiative).

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PRICING

Please contact us for a quote. We need

a concise description of the intended use case,
the size and kind of data (e.g real time)
the number of users
the models that will be used and the indicators that will be created
whether machine learning based training and classifications will be required

Enter the platform here

​LEARNING

IMPACT

INDICATOR

TECHNOLOGY

making sense of big data

See the big picture behind the big data

who we are?

WHat it is?

​

A big data platform to work with indicators, to conceal the big data complexity behind compact indicators. You can create and set up any type of indicator; list, model or learning indicators, via machine learning and neural network technology.

​

LEIMINTE is currently extended to cope also with real-time data series. Data can be uploaded via file uploads or APIs (suitable for real time data)

How?

Your data is organized in projects; you can then

​

set up indicators and use your project data to calculate and report upon them; the indicators can be calculated based on lists or models that you will set up

run flexible machine learning training and classifications on your data, mapping them on classes/ labels you will define

combine both above, i.e., calculate your indicator values based on your lists or models, and run machine learning training/ classifications on the indicators

​

LEIMINTE is based on the TensorFlow open-source neural network technology. It provides a user interface to TensorFlow, allowing you to organize your work with your data.

​

See Solutions below for practical examples.

SOLUTIONS

NEWS & events

PRICING

Please contact us for a quote. We need

a concise description of the intended use case,

the size and kind of data (e.g real time)

the number of users

the models that will be used and the indicators that will be created

whether machine learning based training and classifications will be required

Contact

LEARNING