We take ownership of backend systems that are already in production — and not behaving as expected.
At some point, you stop trusting what the system tells you.
Integrations break.
Data drifts.
Billing becomes unpredictable.
We step in, stabilize the system, and make it reliable again.
What We Fix
Most systems don't fail loudly.
They slowly become inconsistent.
We work in that space.
Typical situations we handle:
- Integrations that "mostly work" but fail in edge cases
- Data inconsistencies across services or systems
- Billing and subscription flows behaving unpredictably
- Webhooks, queues, and async processes that are hard to reason about
- Systems that no one fully understands anymore
If your system feels unreliable — we can take it from there.
How We Work
We work in two phases.
We start with a focused diagnostic of your system in production.
In the first days, we:
- map how your system actually behaves in production
- identify where data becomes inconsistent or breaks
- trace critical flows (billing, integrations, async processes)
At the end of this phase, you get:
- a written summary of the system's current behavior
- a list of issues with severity and impact
- a clear explanation of why these issues occur
- a prioritized stabilization plan
In some cases, the diagnostic alone is enough to resolve the issue internally.
We take ownership of fixing the system — starting with the most critical points.
This typically includes:
- fixing broken or unreliable integrations
- restoring data consistency across systems
- stabilizing billing and subscription flows
- making async processes predictable and observable
- introducing invariants and checks to prevent issues from recurring
We stay involved until critical flows are stable and the team has clear visibility into system behavior.
Engagement is structured as a focused collaboration — not ad-hoc tasks.
Selected Work
A CRM integration quietly exposed other customers' invoices
In a production e-commerce system with active users and real billing data.
No crashes. No errors.
Just valid-looking — but wrong — data.
Root cause: hidden dependency on CRM filtering logic.
Fix: enforced customer-level validation and removed trust in external filtering.
→ eliminated data leak risk
→ made system behavior predictable
Filters returned empty results where products existed
In a production e-commerce system with a growing catalog.
No crashes.
Just inconsistent results.
Root cause: the catalog structure had evolved from a simple tree into a graph — while the platform still treated it as hierarchical.
Fix: restructured category-attribute ownership, reduced cross-category logic, and restored a predictable structure.
→ made filtering consistent across all categories
→ restored trust in catalog behavior
Who We Work With
We work with teams where the system already exists — and matters.
Typical clients:
- SaaS companies with active users and real data
- Agencies delivering complex backend-driven projects
- CTOs and consultants who need reliable execution
Not idea-stage startups.
Not one-off tasks.
We work where things are already in motion.
Team
Aleksandrs Ralovecs
Backend engineer focused on system behavior, data consistency, and production stability.
LinkedIn →I work directly with clients from diagnosis to stabilization.
Supported by a small team of engineers when the scope requires it.
Contact
If your system feels unstable —
or you're starting to lose confidence in how it behaves —
Let's take a look.