Top Data Science – AI with results
We empower people and businesses with innovative and reliable AI solutions
AI solutions for more autonomous world
Top Data Science solutions focus on understanding the actual customer business problem and how it can benefit from automation. We use the most optimal AI approaches for each customer problem and the developed solution. We ensure our solutions are built to be production-ready, to ensure fast and continuous return on investment for our customers.
Industrial AI and Process Optimization
Optimal AI solutions through co-creation
Top Data Science co-creation model brings together customers’ domain knowledge and our AI know-how to build up innovative, robust and scalable solutions.
Top Data Science
We provide leading-edge AI solutions and services from world-class multi-industry enterprises to focused service companies and public sector organizations.
Top Data Science is a Morpho Group company. Established in 2004, Morpho Inc. is a global leader in image processing and imaging AI solutions, with headquarters in Tokyo, Japan and listed on Tokyo Stock Exchange.
We innovate and deliver
We innovate together with our customers and partners how AI technology should be utilized in an optimal way. We keep our promises and deliver on time with high quality.
We solve meaningful problems
We have passion to solve your meaningful problem. Top Data Science AI solutions have been successfully deployed across different industries internationally.
We empower people and businesses with AI
Our success is measured through our customers’ success. Sharing our deep AI know-how and identified best practices are in the core of our co-creation model.
The powerful function of Artificial Intelligence (AI) , including Machine Learning (ML) and Deep Learning (DL), is the ability to describe and learn from data, to predict what will happen and then to recommend right actions. Therefore, AI has been creating competitive advantage for companies in a broad range of industries. The combination of comprehensive strategies with best practices, state of the art tools and world-class expertises is the key for companies to be successful with AI.
Top Data Science helps companies in the full cycle of AI projects from data annotation, models experiment & development, to deployment and operation across platforms of choice. With us, our client can easily do experiments, robustly develop production-level solutions, or reliably and cost-effectively scale up and operate AI solutions in their daily work.
Artificial Intelligence (AI) , Machine Learning (ML) and Deep Learning (DL)
The powerful function of Artificial intelligence (AI) , including machine learning (ML) and deep learning (DL), is the ability to describe and learn from data, to predict what will happen and then to recommend right actions. Therefore, AI has been creating competitive advantage for companies in a broad range of industries. The combination of comprehensive strategies with best practices, state of the art tools and world-class expertises is the key for companies to be successful with AI. Top Data Science helps companies in the full cycle of AI projects from data annotation, models experiment & development, to deployment and operation across platforms of choice. With us, our client can easily do experiments, robustly develop production-level solutions, or reliably and cost-effectively scale up and operate AI solutions in their daily work.
News, Blog, Case Studies, Events.
Top Data Science and Stora Enso Collaboration to boost AI-based Automation AI-based computer...
Interview with Eero Mäki-Lohiluoma, Quality Assurance Manager and Qualified Person at Orion...
Like in many years before, in 2021 Top Data Science offered multiple internship opportunities for...
Learn more about AI solutions and key success factors
What do you mean by "AI with results"? Could you give some examples?
Artificial Intelligence has vast potential to provide value and benefits for society, organizations and businesses as well as individuals in their daily activities. Still, how to achieve these benefits and results is not trivial. Also the results should be thought multidimensionally, both what is the long-term goal in utilizing AI and what results should be achieved along the path that will take an organization towards the goal.
The final goal in utilizing AI technologies relates many times to improved productivity, cost savings through efficiency gains, better quality, improved safety and even well-being at work as repetitive work tasks can be replaced and supported by automation. We have developed a deep and versatile know-how to select the right data and AI approach as well as technologies and algorithms to achieve significant measurable benefits in the above mentioned value points. We have a true passion to help our customers to achieve those results that they are setting for their AI and digitalization journey.
While the overall objective is in most cases a quantifiable business or other benefit, it is very important to set the right kind of ambitious and realistic objectives that enable achieving the long-term goal. We have established an effective and flexible customer co-creation model that has proven to provide high-value results all the way from proof-of-concepts and prototypes to production-grade AI solution deployments. By setting these mid-term targets and achieving results along the way, you are able to build up trust within the project core group as well as towards the interest groups following the progress. During this process we always openly share our AI understanding with our customers so that in every step they are more knowledgeable to set the goals for the next automation phase. It is amazing how quickly many of our customers’ development team members have picked up the AI development philosophy and are then ready to move their organization to the next level.
When is a company ready to utilize AI? Competences needed?
This is a great question. Certainly there are some lines of business and activities that will not gain direct benefits out of AI, but you could even state that most of the industries are benefiting and will benefit from these technologies.
One good and simple starting point on how to approach this is to think that is there a routine task that either the company and/or an individual person would benefit by automation. Automation many times comes hand-in-hand with digitalization of a process or activity, which is one of the building blocks also for AI-based automation. Through digitalization the data foundation of an activity gets established and that opens up opportunities to utilize different AI and machine learning technologies from video and image based computer vision to sensor based optimization as well as text based Natural Language Processing (NLP).
The question related to competence is very relevant. Still the AI technology and service market has evolved in such a huge scale during the past 5 years that access to knowledge is easy and the amount of tools and services available is beyond the need of a single organization that is about to start an AI journey.
A good approach is to gather some initial understanding of AI-utilization examples that somehow are of interest to your own business or activity, and then engage with peer companies or AI expert companies to get help, ideas and guidance. The entry barrier to start is nowadays very low, the market and its actors are ready to support companies interested in AI from the first initial discussion all the way to utilizing the latest and greatest technologies in production level solutions.
How can a company provide AI solutions both to industrial and healthcare sectors?
It is true that each industry and customer domain requires understanding the specifics of that activity in focus. Still AI and machine learning technologies are extremely flexible when it comes adapting them to different use cases. That is also a big reason why the leading high-tech companies are investing so heavily on their AI platforms.
As an example Computer Vision and Imaging AI technologies share the same key capabilities that enable detecting, classifying and segmenting issues and objects whether they relate to industrial high-precision tasks or a demanding healthcare related topic. Key to success here is to collaborate closely with customers’ domain experts and to understand what are the specific AI competences that relate to each industry domain the company is serving.
We have been fortunate to work already for years in multiple industry domains with some of the leading companies and innovators in their sector. That has enabled us to establish a competence and technology foundation to serve efficiently our customers and developed robust and reliable AI solutions.
What is co-creation in practice?
We call our customer collaboration model co-creation. We feel that it communicates well what the collaboration utilizing AI technologies is all about, at least in our case. It is innovating together with customers and partners how things, whether they are process optimization, quality assurance or serving customers, can be done in a new and smarter way. This co-creation is what we do every day, and when it comes with quantifiable results, it is truly exciting and motivating.
The “co-” part in the term is essential. We always combine our deep and extensive AI know-how with our customers’ domain knowledge. This requires both methodology competence and experience so that we are fast in picking up the specific needs of each customer’s line of business. This collaboration includes many times formulating or validating the business case and use cases, and most of the time verifying the automation and AI objectives e.g. what the organization wants to achieve through our collaboration.
A big part of co-creation at its best relates to enabling continuous, scalable and extendable benefits through utilizing AI solutions. By solving one or two business problems with good results creates a foundation to start to think how AI based automation could be further developed to cover more process areas and work tasks. The effectiveness of the co-creation improves continuously as both parties learn from each other. When AI solution scaling is done successfully the value achieved can be staggering.