01Start with the business challenge

Bring us the problem. We build the software that solves it.

Slow systems, manual work, outdated software or a product that has to launch fast: we turn business problems into custom software, AI and automation, from discovery and UX design to engineering and long-term support.

  • AI-native, human-accountable delivery
  • 4.9/5 average rating on Clutch, GoodFirms and DesignRush
  • Building digital products since 2015
Doctro’s App product screenDoctro’s App product screen
ProblemNeed a new product live fast?
Result2 weeksto a beta MVP with core functionality
Products we have built and evolved
GlovoNimblaProdeologyMotorKLezzooGOeurekaSuperCarersQueen Car

Start with the business challenge

What are you trying to build or improve?

Pick the problem closest to yours. Each one shows the signs, how we solve it, proof and the smallest useful first step.

Success stories

Business challenges translated into working digital products.

Explore all 19 case studies →

AI at the core

AI-native, so you get results faster.

AI is part of how we design, build and test, with experienced people accountable for every decision.

Delivery approach

A Visible Path from Decision to Working Software.

A shared view of scope, evidence, dependencies and acceptance criteria keeps the next decision visible throughout delivery.

01

Frame the Decision

Clarify the workflow, users, constraints and evidence needed for the next decision.

02

Design the Path

Make scope, experience, architecture, integrations and acceptance criteria visible.

03

Build in Increments

Deliver reviewable software with automated checks, regular feedback and transparent progress.

04

Launch and Operate

Plan monitoring, support ownership, rollback and the next product decision before release.

Work with the Team You Already Have

We can own a defined workstream or collaborate with internal product, design and engineering teams.

Keep Product Knowledge Transferable

Architecture, source code, documentation and operating knowledge are structured for client ownership under the agreed contract.

Control Delivery Risk

Scope, dependencies, acceptance criteria, testing and release controls remain visible throughout delivery.

Ways to start

Start small. Decide with evidence.

A focused first step that ends with something you can evaluate, before you commit to a larger build.

Engagement & pricing →
01

Technical assessment

Best when: You have an existing product, codebase or legacy system.

  • Codebase and architecture review
  • Risks, technical debt and integration map
  • Modernization or extension plan
Software Modernization →
02

Product discovery

Best when: You have a business problem and need a responsible build decision.

  • Problem statement and workflow map
  • First-release scope with acceptance criteria
  • Architecture direction and delivery plan
What discovery delivers →
03

Feasibility prototype

Best when: A key technical or AI question must be answered before the MVP.

  • A focused prototype of the riskiest part
  • Evidence against agreed acceptance criteria
  • A go, change or stop recommendation
AI Product Development →

Not sure which one fits? Answer four questions and get a suggested starting point.

Find your starting point →

Insights

Decisions behind better digital products.

All insights →

FAQ · Reduce delivery risk

Start with the decision your business needs to make.

All answers →
How much does it cost to work with OpenGeeksLab?

Every project is scoped individually. We estimate by capability and uncertainty, not by counting screens, and stage the budget so each step ends with something you can evaluate. See Engagement & pricing for what influences cost.

How long does it take to build a product?

It depends on scope, integrations and the evidence you need before release. On past projects, a four-person team delivered a beta telemedicine MVP in two weeks, and a five-person team delivered a marketplace web product in six months and its mobile app in four.

What technologies do you work with?

Our case studies include React, Next.js, Angular, React Native, Swift, Kotlin, Node.js, NestJS, Java, PHP, MongoDB, MySQL, Redis, Elasticsearch and AWS. We choose the stack that fits the product, risk and operating reality.

Can you handle AI projects as well as traditional software?

Yes. We build AI assistants, retrieval and agent workflows, and add AI to existing products, alongside web, mobile, SaaS and modernization work.

Do we have to begin with discovery?

No. A focused discovery is useful when requirements, feasibility or risks need clarification. A well-defined project or established product workstream can move directly into delivery planning.

Can you work with an existing product or internal team?

Yes. The engagement can start with a codebase and architecture review, a defined product workstream, modernization, integration or additional engineering capacity alongside your team.

Can AI be added to existing software?

Often, yes, but the useful starting point is the workflow and available data. We assess feasibility, integration, privacy, evaluation, cost and fallback before recommending an AI implementation.

Who owns the software and source code?

The engagement is structured so the client can own and operate the delivered product, source code and project knowledge under the agreed contract.

Start with the business need

Let's Discuss What Your Business Needs to Build.

Tell us about your product, existing software or operational challenge. We'll help identify a practical next step.

Dmytro Dvurechenskyi
Dmytro DvurechenskyiChief Executive Officer, Stockholm

Four-question project planner

Find a Useful Starting Point.

Your answers stay in this browser until you add the brief to the enquiry form.

Question 1 of 4
What needs to change?