Most AI projects die somewhere between the demo and daily use. Before any production code, we validate your idea on your own data and give you a clear go or no-go. If it's worth building, we take it all the way to daily use.
Decide which AI project to fund first, and which to leave alone. Rate each idea against what your data and team can actually support. Walk out with a shortlist of pilots, or a clear "not yet" and the reason why.
See more about AI Strategy WorkshopsFind out what stands between your AI pilot and production before you build. Check data, ownership, security, and compliance up front, and put the access rules and audit trail in place before launch.
Make your data available to your people and ready for your AI. Bring your source systems together in your own cloud, at a fraction of the old infrastructure cost, on a platform your own team runs day to day.
Answer questions around the clock from your own knowledge and systems. Capture leads, take repetitive requests off your team, and keep every answer up to date without a developer.
See more about AI Agents & AssistantsBuild the AI product your customers will pay for, or add AI to the platform you already sell. Work with one team for design, data, models, backend, and frontend that stays on your roadmap after launch.
We'll score one idea with you and say so if the answer is "not yet". No deck, no pitch, one page of findings.
Contact usIndustries
Every industry has its own data, rules, and deadlines. The questions we help answer don't change: what's worth building, what's in the way, and how to make it stick.
Enrollment, retention, and student support run on data most universities can't get to in time. That's where we come in: AI for admissions, advising, and reporting, built on the university's own data.
DLabs.AI started with an app for people living with diabetes. Health has stayed with us since: patient assistants, clinical analytics, and the compliance groundwork regulated data requires.
Every store, product, and promotion leaves a trail of data. Our work turns it into demand forecasts, stock plans, and a clear view of what to automate first.
Education companies compete on how well their products teach and assess. We build the AI inside those products: adaptive learning, faster assessment, content that's easier to produce.
We start from the problem, not the sector. If there's a process worth automating or a product worth building, contact us.
Tell us the AI idea you'd start with, a new product or a process you run today. We'll check it against your own data and give you a straight answer: build it, prepare something first, or leave it alone.
DLabs.AI began with a personal problem. Shemmy, our CEO, has lived with type 1 diabetes since he was ten, and the company's first product was an app that helps people manage the disease with their own data. It set the pattern for everything since: start with the problem, not the technology, and judge the result by whether people use it.
Today we're a team of AI engineers and data scientists who help organizations get real use out of the data they already collect. We put candor before enthusiasm: if an idea isn't worth building, or a simpler solution would do, you'll hear it from us first.
How we work
If at any point we conclude that an idea isn't worth taking further, we say so before you spend more on it.
We look at your processes and ideas together and score which ones are ready for AI and which are not. You get concrete answers on where to start and which initiative will bring the most value. If you already know what to build, we move straight to validation.
Before any production code, we verify that the foundations are in place (data, ownership, security, compliance) and test the idea on a sample of your own data. You get a working prototype, an architecture, a budget, and a clear go or no-go.
We build and integrate the system, with your people involved as much as you want: your engineers can review every pull request, or we deliver it ready to run. A fixed price when the scope is clear, time and materials when it still needs discovery, and a weekly status either way.
A small group of your users works with the system on real data, and we measure the results against the success criteria agreed up front. You see how it performs before it reaches everyone.
We launch, train your people, and keep measuring whether the system is used. You end up with AI in daily use and a team of your own that can run it.
Our culture of learning and continuous improvement resonates deeply with the approach of the DLabs.AI team. We truly appreciate the extensive learning opportunities they provided. Even when initial challenges seemed daunting, their support helped us overcome these obstacles and successfully achieve nearly all our significant goals.
Hitesh Pachpor
Hello Chef
We were impressed by the DLabs team and their high level of professionalism, expertise, and consideration. They took the time to listen to and understand our company's needs and issues. Throughout the process, we felt more like one team. It was very easy to communicate and work together.
Maciej Szewczyk
Taxando GmbH
Throughout the project, we have found the DLabs.AI team focussed, knowledgeable and responsive. We are delighted with the progress we have made on this project to date, and look forward to seeing our new product develop further over the coming months.
Matt Criticos
Boldly
The DLabs.AI team works really hard to ensure a high level of quality of our product. Step by step, they’re removing all roadblocks. They’re flexible and respond quickly to changing demands. And they understand the importance of data quality and analytics, which is the heart of our product.
Michał Myczkowski
Marketing Analytica
The DLabs.AI team is very experienced and they’re masters of machine learning algorithms. Their team does an excellent job of dedicating enough time and focus on each step of the process, which helps when delivering great products. We’d gladly work with them again!
Marcin Śliwa
NMG
DLabs.AI maintained open lines of communication and met project deadlines. Professional and collaborative, the team provided excellent feedback and useful insights. Customers can expect a partner that is both technically proficient and dedicated to delivering results.
Daniel Kajak
Sentione
They exhibit great knowledge about machine learning.
Kamil Starski
UnamoX
Bring the AI idea you have in mind, whether it's been stuck since the demo or hasn't started yet. We'll tell you, on your data, what it takes to make it real.