Data Mid-End - MindFlow

Data Mid-End Solution

Help AI companies quickly set up a data mid end for operable applications

New Ways of Data Management

Business systems in the form of chimney architecture can easily lead to problems such as data islands, data isolation, data inconsistency, and so on, resulting in waste of enterprise data utilization.

MindFlow data Mid-End solution enables data to form a benign closed-loop network between the platform and business system by building an integrated data mid end within the enterprise, laying a solid foundation for enterprise data service and sharing, and helping to release more value from the data.

Data Mid-End Solution

With the digital intelligence platform as the core, build the infrastructure to support large-scale intelligent services, and use the systematic platform products to solve the various needs of users for the generic underlying infrastructure of AI, so that enterprises can continuously turn their business into algorithm models, so as to achieve the purpose of reuse, combinatorial innovation and large-scale construction of intelligent services and business empowerment

Application Case

Data Mid-End is the central support for the digitized transformation of enterprises, and it is also the endogenous force to promote the construction of industry information and the intellectualized transformation of enterprises. Its management capabilities of managing data life cycle are suitable for many applications under the digitized economic transformation.

Data Mid-End of a Cloud Service Enterprise

Project Background

The cloud service enterprise is a strategic cloud brand created by a leading global provider of information and communication technology (ICT) solutions, dedicated to providing leading public cloud services, big data and artificial intelligence services, as well as scenario-based solutions for global customers.

Its one-stop AI development platform provides the entire process of AI development services, assisting users to quickly create and deploy models, manage full-cycle AI workflows, meet the needs of different levels of development, and render AI development and use more accessible. To better meet the needs of the AI development platform in the aspect of data processing, the cloud service enterprise is looking for a stable, efficient and privately deployed one-stop data mid-end solution provider.

Program Content

In the overall workflow system of AI development platform, MindFlow data Mid-End is embedded into the overall workflow framework through privatization deployment, which implements data collection, management, labeling, training, and data lifecycle management in the model application layer.

The unstructured data capture capabilities of REAP platform, visual computing capabilities of SEED platform, and audio parsing capabilities can efficiently convert unstructured data into structural data for training related AI algorithm models.

1.Raw Requirements

2.Requirement Analysis

3.Data Management

（SEED、REAP）

4.Training Management

（BAKE）

5.Model Management

6.Deployment Online

7.Result Output

Effectively fill in the missing functions of the AI development platform, help users to quickly create and deploy models, manage the full cycle AI workflow, meet the needs of different development levels, and achieve smooth, stable and reliable operation of the system.

Why Choose Us

'Understand the data, understand your needs better'

A Better Service System

Integrated end-to-end solutions to various issues of enterprise data asset management without difficulty.