Headerbild zu Operationalisierung von Data Science (MLOps)

Operationalization of Data Science (MLOps)

Maximize the benefits of AI by integrating AI processes with business processes and ensure data quality and traceability of the AI process.
Contact us now

Key challenges that MLOps overcome

Trust in data and the process behind it is key to the successful use of Artificial Intelligence. However, this poses numerous challenges for companies:

Assessment

Unambiguous assessment of the origin and correctness of the data for the decision

Requirements

Duration and effort for the operational deployment of a new algorithm must be lean

Rating

Evaluation of the technical correctness of the algorithm

Quality

Embedding AI in the business process requires quality: documented, monitored, traceable

Are you facing similar challenges?

AI platforms help you provide documented, traceable information and implement MLOps. Generate intelligent AI processes from trusted data and embed them into business processes to make informed decisions. We support you in this!

Request a non-binding exchange

Advantages of an AI platform:

MLOps' challenges in handling data and the process behind it can be overcome with an AI platform:

  • Operationalization of AI processes

    Using Artificial Intelligence to gain insights from data is already a great advantage. This advantage can be multiplied a hundredfold if the AI process is embedded in the actual operational process and can thus constantly deliver its added value. This in turn requires the AI process to operationalize itself: AI must be available as a service, via REST API, as a batch job.

  • Provisioning and monitoring of services

    The provision of AI services in the required form must be agile, performant and traceable. The same requirements apply as for all other business-critical processes.

  • Long-term technical and business monitoring (BIAS) of AI models.

    AI processes are subject to a constant learning and aging process, as the underlying business process is also evolving. A progression in the operational process must be countered with an evolution of the AI process and this must be automated as much as possible. Likewise, potentially undesirable influences ("BIAS") must be detected and documented.

  • Data cataloging/governance

    Central cataloging of data enables faster and more agile development of AI processes. When the origin and meaning of data is documented, AI can make the right predictions more safely and reliably.

  • Data Virtualization

    Making data available to the AI process can be a challenge. Data virtualization can help by making data available to the AI process not physically, but virtually, fully documented and protected.

In our projects, we analyze the individual requirements based on the customer's situation. Then, on the basis of technical and business requirements, we suggest the appropriate architecture to achieve the goals and implement it if necessary.

In the AI platform, thanks to "AutoAI", a model equal in quality and grade was created with a few clicks and a usable, monitored AI process was created in a few minutes. Using OpenScale, this process is now monitored by AI for quality, drift and BIAS.

Marc Bastien Software Architect TIMETOACT

Cloud Pak for Data as AI platform

Experience from previous customer situations have shown that the "Cloud Pak for Data" solution offered by IBM comprehensively supports the AI process incl. MLOps in all aspects. Graphically, the solution and the process look like this:

Grafik zu Cloud Pak for Data als KI-Plattform

Practical example with our customers


Marc Bastien, Software Architect at TIMETOACT, will show you how IBM Cloud Pak for Data and structured application of Data Science identifies and exploits untapped potential in processes using project examples from our customers. 

textandvideo.cookieNotEnabled.text

Our Services:

The breadth and simultaneous depth in covering all analytical issues is TIMETOACT's strength. Experience from decades of consulting and close cooperation with the leading technology providers benefits every project. TIMETOACT has always been at the forefront of adapting new, modern solutions from the technology leaders.

Proof-of-Value Workshops

Determination of data situation and use cases as feasibility study incl. proposal of target architecture for AI project

Introduction & Implementation

Identify open challenges in existing or new AI projects and the potential benefits of adopting an AI platform.

Selection & Implementation

Support in the selection and implementation of an AI platform

Support

Support for the introduction of AI and AI platforms

Contact us now!

We would be happy to advise you in a non-binding conversation and show you how you can benefit from MLOps. Just leave your contact details and we will get back to you as soon as possible.

* required

We use the information you send to us only to contact you in context of your request. For this purpose, we store your data in our CRM for up to 6 months. You can find all further information in our Privacy Policy.

Please solve captcha!

captcha image
Navigationsbild zu Data Science
Service

Data Science, Artificial Intelligence and Machine Learning

For some time, Data Science has been considered the supreme discipline in the recognition of valuable information in large amounts of data. It promises to extract hidden, valuable information from data of any structure.

Navigationsbild zu Data Science
Service

AI & Data Science

We offer comprehensive solutions in the fields of data science, machine learning and AI that are tailored to your specific challenges and goals.
Teaserbild zu Data Integration Service und Consulting
Service

Data Integration, ETL and Data Virtualization

While the term "ETL" (Extract - Transform - Load / or ELT) usually described the classic batch-driven process, today the term "Data Integration" extends to all methods of integration: whether batch, real-time, inside or outside a database, or between any systems.
Articifial Intelligence & Data Science
Service

Artificial Intelligence & Data Science

Data Science is all about extracting valuable information from structured and unstructured data.

Headerbild zu Data Governance Consulting
Service

Data Governance

Data Governance describes all processes that aim to ensure the traceability, quality and protection of data. The need for documentation and traceability increases exponentially as more and more data from different sources is used for decision-making and as a result of the technical possibilities of integration in Data Warehouses or Data Lakes.

Data Science & Advanced Analytics
Kompetenz 9/3/20

Data Science, AI & Advanced Analytics

Data Science & Advanced Analytics includes a wide range of tools that can examine business processes, help drive change and improvement.
Blog 10/31/23

5 Inconvenient Questions when hiring an AI company

This article discusses five questions you should ask when buying an AI. These questions are inconvenient for providers of AI products, but they are necessary to ensure that you are getting the best product for your needs. The article also discusses the importance of testing the AI system on your own data to see how it performs.
Blog 4/16/24

The Intersection of AI and Voice Manipulation

The advent of Artificial Intelligence (AI) in text-to-speech (TTS) technologies has revolutionized the way we interact with written content. Natural Readers, standing at the forefront of this innovation, offers a comprehensive suite of features designed to cater to a broad spectrum of needs, from personal leisure to educational support and commercial use. As we delve into the capabilities of Natural Readers, it's crucial to explore both the advantages it brings to the table and the ethical considerations surrounding voice manipulation in TTS technologies.
Blog 6/27/23

Boosting speed of scikit-learn regression algorithms

The purpose of this blog post is to investigate the performance and prediction speed behavior of popular regression algorithms, i.e. models that predict numerical values based on a set of input variables.
Blog 12/7/22

State of Fast Feedback in Data Science Projects

DSML projects can be quite different from the software projects: a lot of R&D in a rapidly evolving landscape, working with data, distributions and probabilities instead of code. However, there is one thing in common: iterative development process matters a lot.
Headerbild zu IBM Watson Knowledge Studio
Technologie

IBM Watson Knowledge Studio

In IBM Watson Knowledge Studio, you train an Artificial Intelligence (AI) on specialist terms of your company or specialist area ("domain knowledge"). In this way, you lay the foundation for automated text processing of extensive, subject-related documents.

Headerbild Data Insights
Service

Data Insights

With Data Insights, we help you step by step with the appropriate architecture to use new technologies and develop a data-driven corporate culture
Headerbild Talend Data Integration
Technologie

Talend Data Integration

Talend Data Integration offers a highly scalable architecture for almost any application and any data source - with well over 900 connectors from cloud solutions like Salesforce to classic on-premises systems.
Headerbild IBM Cloud Pak for Data
Technologie

IBM Cloud Pak for Data

The Cloud Pak for Data acts as a central, modular platform for analytical use cases. It integrates functions for the physical and virtual integration of data into a central data pool - a data lake or a data warehouse, a comprehensive data catalogue and numerous possibilities for (AI) analysis up to the operational use of the same.
Kompetenz

Artificial Intelligence & Data Strategy

Every company collects and manages vast amounts of data, e.g. from production processes or business transactions.
Unternehmen

About us

Professional consulting in the use of Cloud Computing solutions for companies and organizations
Headerbild zu IBM Decision Optimization
Technologie

Decision Optimization

Mathematical algorithms enable fast and efficient improvement of partially contradictory specifications. As an integral part of the IBM Data Science platform "Cloud Pak for Data" or "IBM Watson Studio", decision optimisation has been decisively expanded and embedded in the Data Science process.

Referenz 4/22/21

Flexibility in the data evaluation of a theme park

With the support of TIMETOACT, an theme park in Germany has been using TM1 for many years in different areas of the company to carry out reporting, analysis and planning processes easily and flexibly.
Produkt

Cloud Machine Learning

Instead of writing code that describes the action to be performed by the computer, your code provides an algorithm that adapts itself. Learn faster and better with Machine Learning!
News 8/6/21

Intelligent Document Processing now even more efficient!

For these reasons, we are constantly improving our performance in the field of Intelligent Document Processing and now have a strong partner at our side in the form of the experts from PLANET artificial intelligence GmbH in Rostock.

Bleiben Sie mit dem TIMETOACT GROUP Newsletter auf dem Laufenden!