Make the most of data – use artificial intelligence

We can help develop use-case-optimized ChatGPT-like solutions which take information security notice. We also have expertise in, e.g., using machine learning in production environments.

Case: Data secure ChatAI application

Since the previous decade, research into artificial intelligence has been experiencing a new boom, and many practical artificial intelligence applications have become part of our everyday lives. The most visible advances to the general public, like ChatGPT, have been made with natural language processing (NLP), large language models (LLM), and massive computing power and data.

ChatGPT can make work significantly more efficient, and companies have a lot of underutilized data. However, ChatGPT takes the data entered by the user outside of Europe, which is problematic from a GDPR point of view. You also have to be careful with ChatGPT regarding confidential information.

We have developed a ChatAI solution that seeks answers to user questions from the customer company’s data. The solution also runs in the customer’s Azure environment and considers which data can be used in the responses of different user groups.

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Machine learning is no longer a black box but a powerful tool whose conclusions can be traced and verified.

With versatile machine learning libraries

Most of today’s AI applications are based on machine learning (ML). As the name suggests, the machine, i.e., the software, is taught with data. Based on that, the machine learns to conclude independently from similar data content.

Advanced artificial intelligence libraries and cloud services available to everyone simplify the use of artificial intelligence. Instead of requiring to develop the artificial intelligence itself, existing artificial intelligence solutions can now be utilized as part of the software development.

A case: Highlighting important information in the mass of documents

Important information can often be lost amidst the avalanche of documents. A person can’t go through such a large number of documents.

We taught the FinBERT language comprehension model to identify suggested actions in maintenance and inspection reports and implemented an interface to find, browse and highlight them in the documents.

We minimize the risk of AI projects for our customers by, e.g., proving the achievable results at the very beginning of the project.

Proof of Concept gives insight into decision-making

Organizations accumulate large amounts of data every day. By identifying processes in which a person makes conclusions based on a large amount of data, you can find a suitable use case for machine learning.

We can prove the results achievable with machine learning and the level of accuracy with the customer’s data with a fast and lightweight Proof of Concept project.

Suitable use cases for machine learning are, e.g., highlighting important information from a mass of documents and detecting errors in the manufacturing process.

AI guide

What is artificial intelligence, what does machine learning mean, and what can it achieve?

Check out our guide →

Integration needs?

Please, contact Juhani, who works in our sales.

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