We work primarily with scale-ups and enterprises – companies with 50 to 500 employees that have a working product or an existing engineering organization and need a partner who combines technical depth with product thinking. Most of our clients are based outside Poland: in Germany, the United Kingdom, Norway, Switzerland, and the United States. We serve as a nearshore development partner, embedded in our clients' workflows and time zones. Our clients include global organizations such as BlaBlaCar, BOSCH, TUI Musement, Sonnen, Maxeon Solar Technologies, Corel, Decathlon, UNDP, Leaseweb, and PRISMA. We have also worked with growth-stage companies across fintech, energy, healthcare, logistics, and e-commerce – from early MVP to platforms serving millions of users.

We choose technology to suit the product, the business goals, and the stage of development – not the other way around. Our stack covers three areas: Web development: Java, JavaScript, TypeScript, Python, PHP, Node.js, React, Angular, Vue.js, Django, Symfony, .NET Mobile development: iOS, Android, React Native, Xamarin, Windows/UWP AI & automation: Python, TypeScript, JavaScript, OpenAI, LangChain, LlamaIndex, LLM integration, RAG (Retrieval-Augmented Generation), machine learning, fine-tuning On infrastructure we work with AWS, Firebase, Kubernetes, Terraform, and Docker. We do not limit engagements to a single stack – teams are assembled around what the project requires.

Yes. We work with enterprises on digital transformation engagements — from legacy system modernization and cloud migration to building new internal platforms and integrating AI into engineering processes. We operate as a long-term technology partner, not a one-off vendor. Our engagements typically begin with a technical audit and a scoped roadmap, then move into execution in Agile iterations.

Yes. Our DevOps & Infrastructure practice covers CI/CD pipeline design, AWS migrations, Kubernetes and Terraform configuration, and cloud-native architecture. We work both on new greenfield systems and on lift-and-shift migrations of legacy applications. For SaaS products hitting infrastructure ceilings — rising AWS costs, unstable deployments, no automation – we conduct an infrastructure audit and redesign the architecture for 10x current load, delivered in stages without downtime.

Yes. We build minimum viable products for teams that need to validate a business idea before committing to full-scale development. A typical MVP engagement at Boldare runs 8 to 16 weeks with a team of 3 to 5 people, and ends with a working product, user testing results, and a concrete recommendation on what to build next. We work across Europe and have delivered MVPs for clients in the US, DACH region, and the UK.

Yes. Boldare is an AI-native software development company – meaning AI is not a feature we offer, but the way we work. It is embedded in how our engineers think about problems, structure code, and deliver software from the first day of a project. In practice this means AI is present across the full SDLC: generating and reviewing code, writing and maintaining tests, supporting refactoring in large legacy systems, producing documentation alongside changes, and accelerating migrations that would otherwise take weeks. Our engineers work with AI tooling – including Claude Code, GitHub Copilot, and custom LLM-based pipelines – directly inside production codebases, across Java and JVM-based backends, PHP and Symfony systems, Python services, and TypeScript/Node.js environments, including systems with 10+ years of accumulated complexity. Being AI-native also means we have made the mistakes early, built the guardrails, and developed the engineering judgment for when to use AI and when not to. We know what breaks in large codebases, how to manage context in long-running sessions, and how to maintain quality and predictability when AI is driving significant portions of the output.

Yes. We design and build products where AI is a core component – not a feature added at the end. This includes LLM integrations via API, RAG (Retrieval-Augmented Generation) architectures, agentic AI pipelines, and MCP server development. We have built multi-agent systems where AI handles code review, documentation, and test generation in parallel on the same codebase.

Yes. We work with systems that have 5 to 15 years of accumulated complexity – monolithic applications, undocumented codebases, outdated frameworks. We begin with an audit: what is worth keeping, what needs refactoring, and what requires replacement. We then plan the migration in stages that do not stop the business. We have completed a Symfony 4.4 to 7.4 migration in half the time it would have taken without AI tooling. We also work with Java, .NET, and PHP legacy systems of similar scale.

Yes – this is our most common engagement model. We embed alongside your internal engineers rather than replacing them, working inside the same repositories, sprint ceremonies, and delivery cycles. Knowledge transfer happens through real work, not handover documentation. This model works for team augmentation, specialized skill gaps, and situations where you need extra capacity without the overhead of traditional outsourcing.

We treat design and engineering as a single process, not sequential phases. Our design teams work embedded with engineers from the first day of a project, covering product discovery workshops, UX research, interface design, and design systems. We have experience designing for complex enterprise contexts — operational dashboards, B2B platforms, internal tools for field technicians and data analysts. For products with AI components, we design human-AI interaction patterns that give users a sense of control without hiding the model's limitations.