REAL-TIME DATA PROCESSINGNDA

Deterministic real-time backend for continuous data streams

Anonymised case study

Due to a non-disclosure agreement, we can't share the client name or project name. What you read here is the description of a real delivered project — anonymised.

Background

A European IoT company processed real-time sensor data. The platform initially grew quickly, but the processing logic had been built ad-hoc: every new customer got customisations, and the async pipelines became complexly intertwined. Their support team was firefighting weekly, and they were losing customer trust over inexplicable data discrepancies.

Problem → Solution

Problem

Async updates created inconsistent data states with unpredictable production behaviour.

Solution

A rule-based, deterministic processing engine with strict validation — predictable output for every input.

Approach

We re-architected the entire processing logic as a rule-based, event-driven system. The key insight: every input must have a deterministic output, regardless of processing order. The migration was gradual — old and new pipelines ran side-by-side for validation, and we only switched traffic when the new system matched or exceeded the old in correctness.

Outcome

4×

Traffic on the same infrastructure

Data inconsistencies since launch

~50%

Support escalations cut (month 1)

Data inconsistencies are gone; the system handles continuous load stably.

Operations

LIVE

24/7 production operations, Firebase infra management, deployment automation and incident response.

Selected work

We take what we build seriously.

EU TAX COMPLIANCE

EU compliance platform for companies operating in Hungary

The team can now independently extend complex tax rules without putting the whole system at risk.

MULTI-TENANT PLATFORM

Multi-tenant web application with strict tenant isolation

New tenant onboarding takes minutes, and the codebase can be extended without risk.

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