Technical Architecture
We help you make the technical decisions that are expensive to undo: how to split the application, where the data lives, which cloud services to rely on, and how to evolve the system you already run. Each choice is written down with its alternatives and consequences, so your team can understand it and challenge it later.
You need this if…
- Every new feature touches large parts of the code and breaks something somewhere else.
- You’re considering a full rewrite and want a less risky way to evolve what you have.
- Performance degrades as you grow, and you can’t tell where the real bottleneck is.
- Your team keeps debating monolith, microservices, or serverless without reaching a decision.
The problem
Early architecture choices influence the cost of every later change. Poor service boundaries or data models can make new features harder to implement as the system grows.
Who it's for
CTOs and founders facing a major rewrite, limits on scaling, a platform decision, or a migration that requires careful planning.
What you get
Documented architecture with explicit trade-offs, including the data model, service boundaries, platform foundations, and an implementation plan organized into stages.
What we deliver
Current-state assessment
A map of your system as it actually works: data flows, dependencies between modules, coupling points, and fragile areas. It gives the whole team a shared starting point before any decision.
Architecture decision records
One short document per significant decision: the context, the options considered, the choice made, and what it implies, downsides included. Later on, your team still knows why the system is built this way.
Target architecture
The intended split into modules or services, the data model, and the hosting foundation, shown in plain diagrams. Detailed enough for your developers to use as a day-to-day reference.
Staged migration plan
A sequence of steps that can ship independently, each with its own success criterion and rollback path. The system can stay in production throughout, which avoids a single high-risk cutover.
How we work
Read the real system
We read the code and production metrics, then talk with the team. The real blockers are often somewhere other than where everyone expects.
Write down constraints
Team size, expected load, budget, and security requirements shape the architecture far more than current trends do. We write them down before comparing any options.
Compare and decide
We weigh two or three options by cost and reversibility, then draft the ADR with you. Choices that are hard to undo get the most scrutiny.
Migrate incrementally
A routing layer in front of the existing system lets us move one feature at a time. The old code stays in place until the new path has proven itself.
Frequently asked questions
Should we move to microservices?
Rarely at first. For a small team, a monolith with clear internal modules is usually simpler to evolve and cheaper to run. Pulling out a service makes sense when one part of the system has very different load patterns, or when several teams keep getting in each other’s way in the same codebase.
Should we rewrite the application from scratch?
A full rewrite is tempting but risky: for a long time, the old system keeps changing while the new one tries to catch up. We usually favor a gradual migration, one feature at a time. A rewrite is sometimes justified, for example when the technology is no longer maintained or the code is too tangled to split.
Do we need to design for massive scale right now?
It depends on your growth outlook, but usually not. The database is often the first limit you hit, and good indexing, caching, or read replicas tend to push that limit a long way. We start by measuring real load to find the actual bottleneck. What matters most is keeping decisions reversible so you can scale when the need is real.
Our other services
Custom Software Development
Production software with tested code, documented architecture, monitoring, and a handover your team can use.
Artificial Intelligence & Machine Learning
From feature stores to deployed models and evaluation. ML systems designed for operation in production.
Research & Development
Use focused prototypes and measurements to assess technical feasibility before committing to development.
Automation & Integration
Connect existing systems and automate the manual transfers between them.
Technical Consulting
Technical advice on architecture, hiring, and technical due diligence decisions with lasting implications.
Not sure which service applies?
Many projects involve more than one service. Describe the problem, and we’ll outline a technical approach.