Rebuild software faster with AI
Want to replace existing software or turn a proven workflow into your own product? Our Human-Agentic Teams combine senior product and technical expertise with AI agents. This helps us rebuild and improve software significantly faster.
We use the existing product as a starting point, identify what you really need and build a maintainable successor. With careful attention to users, integrations and the transition.
Trusted by digital innovators
When is rebuilding the right move?
An ageing platform can slow down change and make maintenance expensive. Rebuilding creates room to rethink the technology, user experience and essential workflows.
An existing product on the market can also inspire your own solution. We first explore which users you want to serve and how your product should be better or different. A working example makes many things tangible, but does not prove demand from your target audience.
Sometimes targeted software modernisation is a better choice than rebuilding everything. We compare both routes before you invest.
Why human-agentic rebuilding is faster
AI agents accelerate delivery
An existing product provides concrete screens, processes and exceptions to work with. Using agreed specifications, agents can draft code, tests and documentation faster.
- Turn familiar screens and workflows into working functionality
- Prepare repeatable development tasks and test scenarios
- Incorporate feedback in short iterations
Senior specialists guide and validate
People decide what we build, make architectural choices and oversee the agreed quality requirements. We tailor engineering and QA involvement to the complexity and risks of your product.
- Clarify scope, exceptions and acceptance criteria
- Assess integrations, security and migration
- Validate working features with your team and users
Learn more about our Human-Agentic Teams.
How we rebuild your software
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Define the scope
We explore users, screens, business rules and integrations. Together, we decide what to keep, improve or remove. You get a clearly scoped first phase with acceptance criteria and an informed estimate.
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Build and test in short iterations
AI agents and specialists work from one backlog. We start with a representative workflow and validate it with your team. This makes progress, quality and remaining complexity visible before we expand.
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Make a controlled transition
We prepare data migration, integrations, ongoing management and user acceptance. Where needed, we switch in stages, with agreed checks and a rollback plan. We then continue improving the product based on usage and feedback.
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How much faster could your rebuild be?
The biggest gains come from clearly defined, repeatable development work. Familiar user flows and clear acceptance criteria help agents build with focus. Unclear business rules, complex integrations and data migration still need careful attention.
That is why we do not promise a fixed speed multiplier for every project. We start with a representative component and use the result to refine the scope, timeline and investment for the next phase.
- Working software to review sooner
- Less manual work on repeatable tasks
- A realistic plan that includes testing and the transition
Our digital product experience
Stay in control of quality and ownership
Maintainable and transferable
We agree on source code, documentation, access and rights to custom-built software. For existing and open-source components, we identify the relevant licences. You know what you receive and how you can develop it further.
Quality checks matched to the risk
An internal tool needs a different approach from a business-critical or regulated platform. We agree upfront on the technical validation, security checks, tests and human expertise required. AI-generated code is not proof of quality in itself.
Software rebuilding: your questions answered
Is rebuilding always better than modernising?
No. If the existing architecture is still suitable, gradual modernisation may involve less risk and disruption. Rebuilding becomes more attractive when the technology or product design consistently prevents the changes you need. We compare the options in terms of user value, maintenance, integrations and the transition.
How does AI help rebuild existing software?
AI agents can turn agreed functionality into code, tests and documentation, and incorporate feedback quickly. An existing product helps make the intended behaviour concrete. Our specialists set the direction and the checks required. Hidden business rules and exceptions still need investigation.
What does it cost and how long does it take?
That depends on the features you choose, the quality of the existing documentation, integrations, data and requirements for going live. We first define a manageable scope and test a representative workflow. This gives us a better basis for estimating the investment and timeline for the next phase.
Does every feature need to be rebuilt?
No. We identify which features users need and which can be removed or simplified. This avoids automatically carrying old complexity into the new product. Where appropriate, we deliver a small but useful part first and expand it with a clear purpose.
How do you reduce risks during the transition?
We include data migration, integrations, permissions and user acceptance in the plan. Before going live, we test against agreed criteria. Where needed, old and new systems run alongside each other temporarily, with an agreed fallback if a check fails.
Can you rebuild software from another provider?
We can develop your own solution for similar user needs. First, we discuss which materials you are entitled to use and which rights and agreements apply. We do not copy source code, branding or protected material without permission. The goal is your own product with clear value for your users.
Discuss your software rebuild
What would you like to replace or improve?
Tell us which product you want to rebuild, who it is for and what is holding you back. A demo, screenshots or an overview of the main workflows helps make the conversation concrete.
Together, we explore the initial scope, the role of AI agents and specialists, and what a reliable transition requires.