More and more products, languages, markets - with algorithms
Advances in the field of artificial intelligence (AI) are driving the development of new tools extremely forward. However, the growing variety of tools also presents customers with the difficult choice of the right AI system, for example the best machine translation engine for their use case.
Depending on the individual use-case, single or combined methods from different Deep Learning disciplines can be applied.
Some examples for the use of AI in the language environment:
- Machine Translation (MT)
- Automated text classification
- Automated text generation
- Named Entity Recognition (NER)
Artificial intelligence often is a black box even for experienced users. But don’t worry! We help you chose the right AI tools and ensure their efficient application in your processes.
With our expertise, you control the data flood
How to organize these ever growing data volumes and provide them with added value? With algorithms of course!
AI processes require a well-maintained database, which we create as part of our language data preparation process. This way you can get an overview of suitable AI systems for your application!
blc supports you in the analysis of AI use case scenarios, training of AI engines, testing of cloud-based tools for text generation and text classification and many other AI-related topics!
Info about Machine Translation Types
Open Use Cases
We help you to use the right AI tool right
Determining requirements and collecting data
- Defining the ideal deployment scenario for the use of AI tools
- Determining and prioritizing data quality and safety requirements
- Analyzing and cleaning up data for training
Selecting and training systems
- Extracting text and terminology for engine training
- Training engines from different providers for comparison
- Evaluating results and selecting the best AI tool for your use case
Optimizing & integrating AI tools
- Calibrating and optimizing AI tools, like MT engines
- Future-proofing the integration of AI tools into the system landscape
- Training of employees and preparation of guidelines
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