Why Sarolta
Engineering judgment, kept close to your product.
Most software problems grow in the gap between what people mean and what eventually gets built. Sarolta closes that gap through direct collaboration and engineering work you can inspect.
The difference
We do not treat the product as a handoff.
You know the people, the workflows, and the outcome that matters. We bring the technical depth: review, design, build, testing, security, release work, and practical operating knowledge.
Together, that means the next version is not merely impressive in a demo. It is clearer, more dependable, and easier to own.
Professional engineering capability
The depth to make the next version dependable.
We build and improve applications across the product, data, infrastructure, security, and quality work that a real release requires.
Applications
Product and application engineering
SaaS, web applications, Windows and Linux desktop software, mobile apps, internal tools, and workflow systems.
AI systems
AI built into real products
Model integration, retrieval and knowledge workflows, AI-assisted automation, validation, safety controls, and human review.
Data
Databases that support the work
Data modelling, SQL, performance, migrations, integrations, reporting, and the data care appropriate to the product.
Platform
Cloud and server infrastructure
Cloud services, Linux systems, deployment, CI/CD, backups, observability, recovery, and operating guidance.
Security
Security designed into delivery
Authentication, roles and permissions, secrets handling, secure integrations, hardening, and risk-based review.
Quality
Quality that can be demonstrated
Test-first work, code review, QA/QC, performance checks, release readiness, and evidence for the decisions that matter.
AI CHANGES THE ECONOMICS
You hire our development service.
You do not buy or learn another platform.
We bring the system, engineers, and discipline.
You stay focused on outcomes.
We work with your tools, your environment,
and your team.
No. Automation expands the work our engineers can compare, test, inspect, and prove. Engineers remain responsible for judgment and delivery.
No. The build profile sets the right proof depth for the project, from one focused question through operational release readiness.
It means the agreed specification passed its stated testing, completed Late Discovery, and was accepted through ARA/UAT in the stated environment.
We preserve work that earns its place and recommend replacement only when the evidence shows it is the safer route.
Yes. You receive the agreed software, requirements, specification, evidence, known limits, and handoff material.
Modern tools, human responsibility
Our engineers take responsibility for the result.
AI supports analysis, implementation, testing, and review. Our engineers remain accountable for the technical decisions, the checks, and the software we deliver. We work with you to agree what success means and provide evidence that the result meets that agreement.
AI-assisted delivery, engineer-owned
Generated code is a starting point. Evidence is the standard.
We use AI-native workflows to analyse, test, implement, review, remediate, and keep evidence. Automation carries repeatable work; experienced developers own the judgment.
Model providers
OpenAI
Anthropic
Gemini
Mistral AI
DeepSeek
Kimi
GLM / Z.ai
Qwen
MiniMax
DoubaoCoding tools and model access
OpenCode
OpenRouterReview and assurance
CodeRabbit
Greptile
SonarQube
Snyk
Semgrep
PlaywrightWe choose models and assurance tools for the task, target environment, and risk—then keep one rigorous, human-led process around them.
01 / Understand
Clarify the job
We establish what must work, who depends on it, and what could go wrong.
02 / Define
Make it testable
Required behaviour, boundaries, and acceptance checks are made clear before the build moves.
03 / Build
Use AI with intent
AI accelerates research and implementation while engineers direct the design and scope.
04 / Check
Test and inspect
Automated checks, focused QA, and engineering review examine the work against the real need.
05 / Remediate
Fix what is found
Deficiencies are addressed and the relevant checks are run again, not waved through.
06 / Release
Leave proof behind
You receive a clear record of the build, testing, decisions, and next operating steps.
Zero-trust, evidence-based delivery
We do not accept plausible code as proven software.
Readable output is not enough. We look for evidence that behaviour, security, performance, and release decisions are appropriate for the actual product. The exact checks follow the audience, risk, and delivery context.
01 / Required behaviour
A clear description of what needs to happen.
We translate product intent into work that can be discussed, reviewed, and checked without turning it into an unreadable bureaucracy.
02 / Tests and QA
Checks for the functionality people depend on.
Automated tests where they help, plus human QA and quality control for critical journeys, failures, integrations, and user experience.
03 / Reviewable evidence
Findings and decisions that stay visible.
Builds, test results, review findings, and release guidance create a practical record during delivery and after handover.
Quality without late surprises
Thoroughness is how we protect time and budget.
Quality has to be planned, not inspected in at the end. Clear boundaries, checks tied to real behaviour, and early review keep risk visible while there is still time to act. That is the practical discipline we bring to delivering high-quality work on time and within budget.
Start with a practical conversation
Bring what you have.
We will help you identify what is worth keeping, what needs attention, and the most practical route forward.