Research-as-a-Service

We will research an AI solution for your organisation

Apply sustainable AI

Creating an effective solution that includes AI is a complex and challenging process. There are several key components to any use of artificial intelligence. The business problem, the data, the algorithms, the integrations, the computational complexity – each of these factors have a significant impact on the final quality of the solution. During our collaboration, we will walk you through the entire range of research work: from the analysis of possible scenarios and available data to the design of algorithms to the creation of demonstration applications.

What can we do for you?

AI offers a broad variety of possible solutions and applications. However, the key is to approach the problem individually and tailor the solution to your needs.

Video analysis

Intelligent analysis of image and video data, detection, and recognition of events and objects

Anomaly detection

Detection of abnormal situations based on various types of data

Process optimisation

Optimisation and automation of key processes in the organisation

Forecasting

Forecasting, demand estimation, predictive maintenance

Digital products based on artificial intelligence and created and applied in a sustainable manner enable new technologies to be used to realise ESG goals.

Types of project

AI Adoption Strategy
Feasibility Study
Proof-of-Concept

AI Adoption Strategy

AI adoption strategy will enable you to recognise the potential to improve your organisation using artificial intelligence solutions. A cross-cutting assessment of your processes and available data will create a coherent action plan and identify the most beneficial scenarios for using AI.

For whom?

AI Adoption Strategy is a service dedicated to organisations that:

What will you get?

A report with summarised use cases

A cross-cutting analysis of the organisation’s processes in terms of using AI to optimise them. Analysis of different work scenarios and types of algorithms.

Analysis of data sources and their usability

Review and evaluation of data sources that can be used to create AI algorithms. Preliminary analysis of the usability of different types of data.

Prepared plan for next steps

Recommended action plan describing the next steps in developing an AI-based solution.

The successful application of machine learning solutions in an organisation comes with many risks. The creation of an AI Adoption Strategy plan helps to prevent their occurrence.

Let's discuss your needs

Feasibility Study

Feasibility Study allows you to assess the potential for using AI to solve a specified business problem. Its execution will determine the validity and opportunity for further work towards building a full-scale solution. We will analyse both the data and possible strategies.
As a result, it will become clear whether applying machine learning to a specific problem is likely to be successful. In addition, you will be provided with information on how to do this as efficiently and effectively as possible, using what kind of data and what further steps will lead to a satisfactory solution.

Duration - 2-4 weeks
Cross-cutting analysis of a business scenario for the use of AI
Examination of the possibility, validity, and profitability of applying AI to a given problem
Preparation of the foundations for the creation of a working solution

For whom?

Feasibility Study is a service dedicated to organisations that:

What will you get?

The final report

A report providing an analysis of possible approaches and scenarios for the use of AI in a specific problem.

Code of analysis

Source code of all data analysis and algorithmic work carried out.

Recommendations and action plan

Recommendations and action plan for further phases of the solution work.

Feasibility Study makes it possible to clearly define the tasks to be performed by AI in a given problem, the required data, the boundary conditions, or the type of algorithms to be used.

Let's discuss your needs

Proof-of-Concept

Proof-of-Concept is the most advanced and labour-intensive variant of our Research-as-a-Service proposal. It is an integral part of building AI-based products and solutions. Its purpose is to test whether a given AI application has practical potential and a chance of effective, long-term performance. During the PoC work, machine learning experiments will be carried out to prepare a solution suitable for usability testing. The work will result in AI algorithms integrated with a test application tailored to address the given problem.

Duration 1-3 months
Preparation of baseline versions of the algorithms
Verification of key hypotheses
Preparation of an application to test the solution
Can be extended to include data acquisition process

For whom?

Proof-of-Concept is a service dedicated to organisations that:

have a plan for an AI-based solution
want to test how AI affects a particular business process
need to test a specific problem approach in practice
want to further develop the solution and move towards a working AI model
are looking for sustainable AI, used in a responsible way

What will you get?

An application that enables practical testing

Test how the solution performs in the hands of users and how it integrates with other systems in the organisation.

A basic AI model

Algorithms trained using acquired data. Performance quality evaluation for the most common cases.

A roadmap for further actions

Knowledge of the strengths and weaknesses of the AI solution. Clarified work guidelines for a production implementation

Proof-of-Concept is a crucial part of the effective and responsible use of AI, the first practical step to creating a functional solution.

Let's discuss your needs

Jak przebiega proces?

Research-as-a-Service składa się z 3 wariantów usługi, które układają się w pełny proces adopcji AI. Jednak współpraca może obejmować jeden lub wiele wariantów, dla różnych problemów biznesowych, w zależności od potrzeb organizacji.

How we develop software and AI

Sustainable AI is a priority for us

Our work focuses on modern technologies, and we keep a responsible approach to the process of applying AI and creating solutions. In every business case, the purpose of using AI is meaningful for us. We understand the importance of data and how it affects the potential of the algorithms we create. We believe that AI can be ethical and can support the goals of responsible development.