Besides being top-notch specialists in machine learning we have a team of expert business consultants ready to support you in achieving your business goals and help to develop the final AI solution that matches your stakeholders’ expectations.
SEND US A REQUESTFrom validating ideas on the business side to creating a strategy that is based on them. Making sure everything is ready from the data side from quality, quantity, engineering and scalability.
We set up all the necessary MLOps infrastructure for initial pilots and scale successful pilots. Of course, we develop the actual AI models producing the desired output and the supporting applications to exploit the output of those models.
One of the key values provided by machine learning is processing unstructured data like speech and text to extract facts and insights, removing the reliance on inaccurate keyword searches and sluggish processing of audio recordings.
AI-based natural language processing (NLP) solutions allow machines to perform these tasks at a speed that is unmatched by humans. This allows us to classify entire documents, divide them into sections by topic, understand the user’s intent in a conversation, or extract pieces of information from long texts.
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Here at Dynalytix, we develop computer vision applications focused on deriving meaningful information from visual inputs like images and videos at a scale and speed impossible for humans.
Our experience in this domain allows us to provide our partners with solutions tailored to their specific datasets, scale and performance needs.
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AI-powered recommendation engines can make recommendations based on tens of thousands of data points. This means highly relevant results for the end-user. This area of machine learning is especially relevant for the aviation, retail, banking and telecom industries where it’s used for.
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With MLOps we use a set of techniques that aim to deploy and maintain ML models in production reliably and efficiently.
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We worked closely with the VNG team, to identify key areas where AI could bring the most value and evaluated the business data needed to train relevant machine learning models. We also helped provide an additional framework for data collection and strategy to use AI solutions.
We build an AI web-based and mobile-app solution based on computer vision and natural language processing models. The goal strategy is to use AI solutions to help policymakers be more data-driven, cost-effective and efficient in investigating subversive or criminal behaviors of businesses in the main cities of the Netherlands.
Working closely with your company, we will identify the key areas where AI can bring the most value. This involves meetings with all stakeholders and developing a roadmap for action together.
We will evaluate if you have the business data needed to train relevant machine learning models. If required, we identify additional frameworks for data collection in your company.
Based on our meetings and data analysis, we’ll share with you the possible AI use cases for your company. We will work hand-in-hand to agree on the desired outcome.
We will build and apply various machine learning models to your business data, to find the best solution. As a result, we will develop algorithms that accomplish the desired goal.
We integrate the machine learning model with an API or front-end product, making it user-friendly and accessible to the end-user.
Any system might require time to time maintenance, and we are happy to support our customers with that.
Discovering the right process to be enhanced with AI may be an unusual task for business people.
People should come to us when they have a business problem where they intuitively feel that the solution could be hidden in data and that it can not be solved by writing a couple of simple rules. If this is the case, AI might be the solution.
To actually define an AI use case, business leaders will need the help of an AI team, who judge if and how to proceed with the problem enhancement; the problem owner who knows the most about the issue; and technical specialists who understand how the problem described by the problem owner can be interacted with in the technical world.
Data collection is most often on the client side as it is connected to the peculiar business problem to be solved we help as much as we can, especially if it is a data source we have worked with before.
Labeling can be on the client side if very specific knowledge is required for labeling or it can be outsourced to a labeling company or us. Hybrid solutions are also available, and in all cases, we provide proper labeling training and guidelines tailored to the computer vision task.
If you imagine the process made up of iterations of the cycle: data collection, labeling, model development + training, testing & evaluation and deployment into the final solution, usually the first 2 steps take 20-50% of the time (the smaller the project / standard problem, the higher the percentage) while the split between the latter 3 is really dependent of the novelty of the problem being solved, the required performance level and the complexity of deployment. The AI project range is from 5 months to multi-year collaborations.
During the project evaluation, we provide a feasibility assessment, and for problems in which we have experience, we can provide a more precise prediction and discuss the forecasted minimum level of performance.
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