Optimize internal processes or amaze your clients with AI-based products. Leap into a whole new world of possibilities and use AI to boost your business’ performance, enhance your team’s efficiency and build AI-powered software with the potential to win the market.
No matter what type of AI you need — generative AI, machine learning, predictive analysis or other — we’ve got you covered! With a highly-skilled team and years of experience with AI-powered projects, we’re here to help you build software based on advanced AI models.
AI projects are much like experiments — and in order to get on board with AI adoption, you need to be ready to test ideas, and let some of them fail.
Don’t underestimate the human factor of AI — it’s created to augment your team, so you need to get them ready for being more data-driven and AI-friendly.
Identifying the proper use case is one of the common bottlenecks to successful AI adoption. But worry not, we’ll help you find a solution that addresses your needs best.
Use AI to get valuable insights about your business’ future and make smarter, data-driven decisions.
Use personalized, AI-based recommendations to boost customer engagement, increase sales and more.
Adjust your prices automatically. Use dynamic pricing for higher margins and better conversion rates.
Use AI to assess the value of items, evaluate conversion’s probability or verify credit risk (lead/credit scoring).
Unlock new possibilities with GPT, Midjourney, Stable Diffusion and many more Gen AI models.
Your options are not limited to those above! Whatever your right AI use case is, we’ll help you find it.
An AI-based platform recommends the right courses to support employees’ development at one of the world’s biggest financial institutions.See the study
After the full rollout of the AI-based system, our client ended up with more than 10x return on their investment.See the study
In less than one month, we validated the idea of using AI to improve sales rates in a British telecom company — with over 91% success probability!See the study
An AI-based platform recommends the right courses to support employees’ development at one of the world’s biggest financial institutions.
After the full rollout of the AI-based system, our client ended up with more than 10x return on their investment.
In less than one month, we validated the idea of using AI to improve sales rates in a British telecom company — with over 91% success probability!
The key to successful AI adoption is the right approach — and we’ve got all it takes to support you fully from Day 1.
First: a no obligation consultation to understand your needs & answer questions. Next: a tech call to dig to the core of your project and choose the best starting point for it.
During tailored workshops we help you determine potential AI use cases for your business or polish the ideas you already have & we set the road map to test and validate them.
After the workshops, you get an extensive report including a detailed action plan, estimates for building PoC & prognosis for your product’s development.
The PoCs’ role is to prove that chosen AI use cases can (or cannot) deliver tangible value to your organization — and to choose those worth moving forward with.
That’s when you meet the team carefully selected for your project & we discuss all the essential points of our collaboration. Then — we get to work!
Here’s where the real fun starts. Our teams are always loyal to the Scrum methodology and iterative approach — it’s crucial in AI projects as they require lots of experiments & flexibility
Artificial intelligence is a significant technological trend that shapes the web development landscape. Over the last few years, AI-powered modules have become one of the most desired features of software platforms and applications. As such, they require an adequate system architecture to work smoothly – which has a strong impact on how these systems are developed.
However, many web and mobile applications are not AI-powered and are not intended to be, at least in the near future. They can still benefit from AI-assisted development, e.g. Quality Assessment & code review.
There are certain factors that impact the final cost of such a project. These include: using off-the-shelf components, team composition, quality of data, project scope, costs of the infrastructure, integration, and maintenance, etc.). That’s why it is so difficult to assess this cost without knowing the details.
In general, the costs of AI projects vary from $10-20K for a simple Proof of Concept, which will help you validate the idea of using AI to solve a specific business problem, to $50-500K for the full implementation. The reliable estimation needs to start with having a closer look at your needs, requirements, and possibilities to assess the solution’s complexity and the work it requires.
There is no fixed team size for AI development projects. Depending on your requirements, the team composition in an AI project may vary. Also, note that the AI development team may not need to be limited to data scientists and a scrum master. If you need your AI models to integrate with a system you already use, you will need a software engineer(s). If you need to build new dashboards, interfaces, or whole apps to allow for easy use of the model, you will also need designers.
If you want to build an AI-powered web application, you need to start with designing the architecture that will make it possible to integrate various AI models.
To make it “future proof”, we suggest you not focus solely on the models that you’re starting with. Don’t focus only on the temporary needs. Instead, try to identify all the places that have the potential to be AI-powered in the future – regardless of the data you have right now or your current business processes, needs, and priorities. Thanks to that, you will be able to plan the whole architecture of that new system in a way that will make it possible to integrate other artificial intelligence models in the future.
Artificial intelligence changes web development in many ways. On the one hand, it is transforming how web apps are developed. AI-powered tools for developers can automate some tasks (therefore reducing the development time), improve the code quality, or even suggest optimizations in design based on users’ behavior. On the other hand, it requires web apps and systems to be written in a certain way that enables integration with artificial intelligence models. For sure, it is an important trend that will have a significant impact on web development.
Machine learning uses various types of algorithms: neural networks, linear regression, logistic regression, clustering, decision trees, random forests, etc. The choice of a specific algorithm should be adjusted to your project. Often, it is necessary to test a few algorithms to find the one that is most suitable for the specific use case.