AI Solutions

If you have already identified a profound deep learning use case in your organisation, but do not have the expertise to develop a prototype or a scalable and production-ready solution, we can help you out. No matter how far you are in the process, we can support you in all stages of development, from data collection to the final implementation of the solution into regular workflows.

Use Cases

The use cases are diverse and cover different areas to ensure that you are ready to assimilate into an AI-prevalent future.
Our individual models work with images, text and data.

Computer Vision

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Image Classification
Classification of images according to its visual content
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Object Detection
Recognition of instances of semantic objects in digital images and videos
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Anomaly Detection
Detection of anomalies & novelties in image datasets

Natural Language Processing

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Document Classification
Assigning categories to entire documents with (un)structured data
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Question Answering
Automatic answering of frequently asked questions
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Entity Recognition
Classification of named entity within unstructured text into categories

Other

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Design Automation
Assistance in the creation and development of technical designs
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Forecasting
Prediction of changes for important business KPIs
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Time Series Analysis
Finding complex patterns in sequential data

Our Solutions

If you have an important problem and sufficient data available, we can develop a tailor-made solution for you - be it prototype or product.

Proof-of-Concept Solution

The prototype solution is dedicated to building your first deep learning solution, while proving both the technical feasibility and business value of your use case.
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Production-Ready Solution

If you want a solution that goes beyond a proof of concept and is directly integrated into your running operation, we can develop suitable cloud or on-premises solutions specifically for you.

Methodology to our Solutions

There are two ways that our above solutions can be implemented

Hybrid Processing

Our Hybrid Processing infrastructure leverages on the best of both human intelligence and deep learning. We automate repetitive tasks and leave the most challenging cases to your team. This is more suited for human-centered workflows.

Full Automation

Contrary to our hybrid approach, the autonomous method allows our models to be fully accountable for your data - without any human interaction. This is more suited for real-time cases.

Learn more

Recent Examples of our Work

For Proof-of-Concept Solution

Our work with Daimler was to prove that computer vision techniques are able to check manually picked kits in logistical areas. Within a short period of time and without much data annotation effort, we successfully trained a classification model that is able to analyze the manual kitting processes efficiently and accurately. The model was able to classify objects of different geometric clusters with a high accuracy rate and detect if they are correct or wrong parts. Only a small handful of geometric clusters with indiscernible differences (e.g. a few millimetres difference in height) caused uncertainty in the model.

For Product-Ready Solution

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Infineon designs and produces chips. Chip verification requires lengthy testing to reach functional coverage. We built an unsupervised novelty detection algorithm that reduced redundancy in simulations. Thereby, we saved Infineon Technologies 2,400,000 hours of computational time, saved an amount in the double-digit millions per chip design and decreased time-to-market by 3 months.

Supercharge your Processes

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