FinTech · Healthcare & Pharma · eCommerce

We architect quality.

AI-driven validation, QA consulting and intelligent quality operations for teams shipping regulated software. We design the gates that decide what reaches production — and prove they hold.

release / 2026.4.1QUALITY GATES
  • Unit & contract1,284
  • API & integration412
  • Regression · Playwright2,940
  • AI output validationlive
  • Compliance sign-offqueued
3 of 5 gates passed · no blockerspromote to production

Three engagement models

Pick the model. We bring the engineering.

AI-Native Quality Engineering

AI-Driven Validation

We help organizations transform software delivery through intelligent quality engineering.

70%+of AI initiatives fail to deliver sustainable impact

Book an AI validation assessment
  • 01People — Empowered teams with AI skills and mindset
  • 02Processes — AI-native processes designed for speed, quality and adaptability
  • 03Platform — Unified platform enabling visibility, integration and scale
  • 04AI Capabilities — Embedded intelligence across the delivery value chain
  • 05Outcomes — Measurable business impact and continuous improvement

Case studies

Measured on production uptime, not test-case volume.

All case studies

Featured · HealthTech & Pharma

An AQA ecosystem built from scratch, and a 2.5× cheaper environment estate.

Challenge

Manual processes could not keep up with the release cycle, and an expensive, unstable environment architecture made every regression run a gamble.

Execution

A custom Playwright automation ecosystem, AQA integrated into release management with quality gates, and a full audit of development, AQA and QA environments.

Impact

Only stable code reaches production, and environment consolidation plus smarter test scheduling cut development-environment spend by 2.5×.

2.5×

Lower dev-environment cost

Environment consolidation and test-run scheduling

5.0

Clutch rating

4 verified reviews · quality, schedule, cost and NPS all 5.0

“They contact us very quickly with good ideas and possible solutions.”
Executive · HealthTech & Pharma
Verified on Clutch, January 2026

More engagements

FinTech & Financial Services

Investment reporting migration

Migration testing, functional coverage and formal documentation for a global investment company.

6 months · 4 QA engineers · Global

Healthcare & Pharma

Healthcare AI analytics framework

Data quality across the processing pipeline.

12 months · 5 QA engineers · US

Industries

A test is only as good as the domain logic behind it.

FinTech & Financial Services

Payment gateway and transaction-security testing, API integration checks, and validation of automated risk-scoring and financial decision agents.

  • Payment gateway and settlement flows
  • Transaction security and fraud paths
  • Automated risk-scoring agent outputs
  • Third-party API integration contracts
  • PCI-DSS
  • SOC 2
  • GDPR
Explore this industry

Interactive · 60 seconds

QA maturity check

Six questions, scored 1 (not at all) to 5 (fully in place). You get a maturity band and the moves we would make first. No email required.

14out of 30Repeatable

The basics run, but they depend on people remembering. Stabilise environments and triage, then widen coverage without widening maintenance.

What we would do first

  • Reproducible environments and seeded test data
  • Flake tracking with an owner and an SLA
  • Extend API and contract coverage before UI
Get this reviewed by an engineer
Not at allFully in place

Critical user journeys are covered by automated tests that run on every release candidate.

The suite is wired into CI/CD and blocks a merge or a release when it fails.

Environments are reproducible and test data is provisioned without manual setup.

Failures are triaged to a root cause quickly, and flaky tests are tracked rather than ignored.

Non-deterministic features are benchmarked for accuracy, bias, privacy and injection resistance.

Audit evidence for HIPAA, SOC 2, PCI-DSS or FDA is produced by the pipeline, not assembled by hand.

FAQ

Questions technical leaders ask us first.

Everyone says "AI-native" now. What does it actually mean here?

Fair scepticism. For us it means two specific things.

We use AI in the work — test design, requirement analysis, defect clustering, release-readiness scoring — because it does those things better than a person reading every ticket. And we test AI products for clients who ship them, which is a different discipline again: non-deterministic outputs, LLM-as-a-judge evaluation, adversarial prompt testing.

What it doesn't mean is that AI replaces judgement. AI test design covers the space you've described faster and more completely than a person can. It won't find the bug nobody thought to look for.

How is this different from a QA outsourcing firm?

An outsourcing firm sells you people by the month, and the longer you need them, the better the arrangement works for them.

Three of our four services are fixed scope, fixed price, with a defined end and a handover. We're paid to change how quality works, not to stay. The fourth runs monthly and rolling, with no minimum term — so if it isn't working, you leave.

We already have a QA team. Where does this fit?

Most of our work is with teams that already exist.

The constraint is rarely the people. It's the test architecture they inherited, the process built around a release cadence you no longer run, or the absence of anyone senior enough to set a standard. We work alongside your team and hand over what we build, because a team that can't maintain the new approach reverts to the old one within two quarters.

If the honest answer after an assessment is that you need one more engineer rather than us, we'll tell you that.

You're a small team. What happens if you're busy?

We're a core team of senior practitioners, extended with specialists we've worked with before when an engagement needs particular depth. We don't keep a bench of juniors to place.

That means the people you meet are the people who do the work. It also means we take a small number of clients at a time and occasionally can't start when you'd like — which we'll tell you on the first call rather than stretch and under-deliver.

Do you need access to our production data?

Usually not, and we'd rather not.

We work with synthetic data built to match your real distributions — including the edge cases your production set happens not to contain. In healthcare that keeps us outside your PHI scope entirely, so there's no Business Associate Agreement to negotiate before anything starts. In financial services it means no PII leaves your environment.

Where an engagement genuinely needs production access, we'll say so up front and work to your security requirements rather than around them.

What does an engagement cost, and how is it structured?

Three of our four services are fixed scope, fixed price, four to six weeks. You know the cost before it starts and there's no open-ended engagement to exit.

Intelligent Quality Operations runs as a monthly retainer, rolling, no minimum term.

Price depends on the size of your estate and how much of it is in scope. Every service page carries a starting-from figure so you can size it before you talk to us.

Book a call

Schedule an engineering call.

Thirty minutes with an engineering team, not a sales. Bring a release problem, a compliance deadline or an AI feature you cannot yet trust.

Schedule an Engineering Call

Or send the brief first

We reply within one business day. Rotterdam · Kraków · Lviv.

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