Data and AI

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Responsible

Cost-conscious

Outcome-focused

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Use Cases

How can data and AI applications be effectively integrated into your business processes? We've compiled a selection of use cases that highlight the potential of data and AI across various industries and scenarios – from data-driven decision-making in agriculture to regulatory compliance in financial services, and efficient data exchange between departments.

Automation in Agriculture

A platform that applies AI to satellite images to monitor field variability, predict yields, and plan field operations.

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Medical Technology

The traditional approach to diagnosing heart disease involves a visit to a clinic or hospital for an electrocardiogram (ECG), which can be time consuming, costly and inconvenient for continuous monitoring. A portable and easy-to-use personal ECG device with AI technology can be a worthwhile alternative.

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Enhancing Agricultural Yield with Precision Farming

Agriculture can benefit greatly from Machine Learning by using data to make decisions about planting, maintenance, and harvesting, to optimize yields and reduce waste.

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Predictive Maintenance in Manufacturing

Predictive maintenance in manufacturing uses Machine Learning to predict when a machine is likely to fail, enabling just-in-time maintenance to prevent downtime without unnecessary inspections.

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Regulatory Compliance for Financial Services

In financial services, Data Mesh helps streamline regulatory compliance. Each data product can have its own customized policies and controls, simplifying compliance with strict standards. This localized approach improves the auditability and transparency of compliance efforts.

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Global Enterprises

In multi-divisional global enterprises, Data Mesh enables individual business units to take ownership of their data as a product, improving data quality and accessibility. A global interoperability layer ensures seamless collaboration and insight across the enterprise.

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Personalized Customer Experiences and Supply Chain Management in the Beauty industry

Decentralizing data management puts domain-specific teams in charge, enabling rapid personalization and operational efficiency to meet customer demands.

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Predicitve Maintenance in Manufacturing

Equipment failure in manufacturing can lead to costly downtime and maintenance. A Data and Machine Learning Platform offers the infrastructure to implement predictive maintenance by leveraging data analytics and machine learning.

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Interdepartmental Data Sharing

In interdepartmental data sharing, Data Contracts provide a shared data framework that facilitates effective communication and builds trust between departments. The result is a streamlined integration that enhances data quality throughout the organization, yielding long-term benefits.

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Third-Party Data Exchanges

In the context of exchanging data with third parties, Data Contracts play a critical role in ensuring security and compliance. They establish protocols for data management that promote responsible practices and alignment with legal and quality standards. This, in turn, diminishes risk for organizations and their external associates.

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Machine Learning Models

In the business context of machine learning, Data Contracts are vital protectors of model performance. They establish concise criteria for data quality, volume, timing, and structure. Their purpose is to guarantee that machine learning models always obtain the appropriate data for superior performance, despite changing data environments.

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Our Services

AI Products

We design and develop products that leverage artificial intelligence (AI) technologies to automate and improve various aspects of business operations, technology, and consumer services.

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Data and ML Engineering

Our software and data engineers design, develop, and deploy machine learning models into production systems.

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Data Mesh

Introducing Data Mesh requires organizational, technical, and cultural change. We offer consulting, assistance and tools to enable your leaders and engineers to take ownership and build trustworthy data products.

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Platform Engineering

We help you to develop, construct, and refine the foundational infrastructure that supports and drives data and AI solutions.

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Knowledge Transfer

Our data and AI experts love to share their technical knowledge and practical experience with you.

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40 %

Consultants using AI finished 12.2% more tasks on average, completed tasks 25.1% more quickly, produced 40% higher quality results.

2025

By the end of 2025, 55% of manufacturing companies and 71% of information industry companies in Germany are expected to use generative AI for commercial purposes.

39 %

AI can enhance efficiency and profitability in the manufacturing sector. It's forecasted to increase the share of profit by 39%​.

Why INNOQ?

For more than 20 years, our employees have been consulting SMEs and corporations and successfully realizing all kinds of IT systems. Our expertise is backed by many years of practical experience – in software architecture and development, digital platforms and infrastructures, and digital product development. For us, technology has no self-purpose, but is the basis of solving real problems.

Before we give advice, we listen

Before we convince you, we convince ourselves

The result: Technology that moves everyone forward

190 employees

300+ customers

Since 1999

Dr. Larysa Visengeriyeva
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We’d love to assist you in your digitalization efforts from start to finish. Please do not hesitate to contact us.

Successful projects

In-depth trainings

In cooperation with our partner

Data Mesh: Fundamentals

For software architects and developers.
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AI Products with Domain-driven Design

Using Domain-driven Design, Event Storming, and ML Canvas to design AI Products.
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Get to know our primers

Data Mesh Architecture

Data Mesh is a sociotechnical approach that enables development teams to autonomously carry out data analysis. In this primer we explain Data Mesh from the engineering perspective.
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MLOps (in German)

In this primer, we explain the fundamentals and principles of MLOps with the goal of conveying MLOps processes from an engineering perspective.
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28
Sep
2023

Architecting MLOps. Von der AI Strategie zur MLOps-Plattform

data2day / 10:15 – 11:00

28
Sep
2023

Architecting MLOps. Von der AI Strategie zur MLOps-Plattform

data2day / 10:15 – 11:00