Services / AI Solutions
We start by testing whether AI can handle the task on your own data. Then we build a product people actually want to use.
What do you actually build?
We build AI assistants that answer from your company's data, and agents that carry out tasks on their own. You get a working product at the end.
Could you build one for us?
Yes. We start with the Starter stage: we test on your data whether it works, before you commit to an interface or a wider plan.
And who owns it afterwards?
You do. At the end we hand over the whole solution with its documentation, so you can keep developing it with us or with any other team, whenever you like.
AI assistant – it can be imperfect. For anything specific, book a call.
Your team re-keys data out of documents, emails and forms all day. We hand that to an agent and keep a human on the exceptions.
The answer is somewhere in documents, notes or old tickets. An AI assistant searches your materials, finds it and points to the source.
A model that invents details is worse than no model. We base every answer on your data, and when the answer isn't there, the assistant declines.
Ordinary search fails the moment someone phrases a question differently. We build search that understands what people mean, so your team finds things faster.
Generic widgets feel foreign and get ignored. We build the assistant into your product so it looks and works like part of it.
Impressive in a slide deck, unusable at real volume. Before anyone commits, we check on your data that the solution works well and pays off.
Documents, tickets, records or a catalogue the work already runs on.
Feasibility tested on your own data before a roadmap gets signed.
Not a widget in the corner: an assistant with your data, tone and permissions.
The solution belongs to you, and you can switch AI models whenever you like.
This is a real assistant we built and run in production on this site – same stack we'd ship for you. Ask it anything about doubleucode.
Try asking
Grounded in
AI assistant – it can be imperfect. For anything specific, book a call.
A live AI model with safeguards: it declines off-topic and unsafe questions and answers only from what we've published.
Practical AI connected to your data, your workflows and your product – not a generic chatbot bolted on the side.
AI assistants that answer questions and help users get their work done. They feel like part of your product, not a bolted-on widget.
Assistants that answer from your documents and knowledge base, so your team finds information faster and can trust what it gets.
AI agents that take over repetitive tasks in the tools you already use, giving your team time for work that needs a person.
The models and tools we use to ship reliable, production-grade AI.
Shipped patterns
Move Maya to the Pro workspace
workspace.moveDone – Maya is on Pro, seat count updated to 43.
An in-app assistant that answers questions from product data and carries out users' requests.
Read the case studyShipped patterns
Overnight queue · 214 tickets
A support assistant that resolves common tickets from the knowledge base and escalates the rest to a human.
Read the case studyShipped patterns
Which contracts auto-renew in Q3?
Search that understands what people mean and answers from a company's internal documents. It shows the source and respects each user's permissions.
Read the case studyShipped patterns
Something warm for a rainy commute
A conversational shopping assistant that understands intent and recommends products from the live catalogue.
Read the case studyShipped patterns
invoice-4821.pdf
An agent that extracts, validates and routes data from incoming documents – cutting manual processing time.
Read the case studyOur users used to open a ticket just to find a setting. Now they ask inside the app and get an answer with a link to the exact page – and we can finally see what they were asking for all along.
SaaS & Product
In-app copilot grounded in product data
The assistant takes the repetitive half of the queue and hands us the rest with the context already gathered. Nobody waits until the morning for a first reply any more.
Customer Support
Support agent with human handoff
Invoices and delivery notes used to sit in an inbox until someone typed them in. They're read, checked and routed the same day now, and we only look at what the agent flags.
Operations
Document processing agent
01
You tell us the use case; we say whether AI is the right tool for it.
02
We go through your data, your constraints and the risk worth validating first.
03
You pick the stage, we agree the scope, and the build starts.
We split an AI project into three stages. Each answers one question: will the technology work, will it pay off, and will people use it.
We look at your data, agree what success means and pick the stage worth starting with.
Depending on the stage, we build a feasibility test, a prototype or an MVP ready for launch.
We hand over the complete solution with documentation. It's all yours, and you can keep developing it without us too.
Best for
Can AI actually do this? We test it in a working app on your real data.
What you get
Best for
Will investors and the board fund this? We show them the solution proven in Starter as a working prototype.
What you get
Best for
Will users stick around? A production-ready MVP with the infrastructure to support your first real users.
What you get
Not sure which stage fits? In a no-commitment technical assessment we'll help you pick the one to start with.
doubleucode · Free consultation · Call: +48 667 083 196
Got a question about your own use case? Send it straight to us:
Ask about your AI projectYes. Everything we build for you is handed over with documentation. The solution is yours, and you can keep developing it with us or with another team.
We work with leading AI models, including those from OpenAI, Anthropic and Google, and with proven web technologies. We choose the model to fit the task and the budget, and compare the options on your data before you decide. We'll go through the details in a free consultation.
We start by checking that the solution works on your data, and only then build further. That way you invest in a project that makes sense and get working software at every stage.
Yes. Each stage builds on the work done before it, so you never pay for the same thing twice. You decide on the next step once you've seen the results of the previous one.
You get the complete solution and can continue with your own team or with us. We can also take care of its maintenance and further development.
