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Reviewed by Dr. Dmytro Nasyrov, Founder and CTO • Last updated April 24, 2026

QA and Testing Services

Pharos Production delivers comprehensive Quality Assurance (QA) and Software Testing services that catch defects before your users do.

  • 90+ engineers
  • 18 industries
  • 13+ years in business

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Reviewed and updated
Last reviewed April 24, 2026 by Dmytro Nasyrov, Founder and CTO. Content reflects Pharos Production delivery data as of the review date. Editorial policy.
Dmytro Nasyrov - Founder and CTO of Pharos Production

Reviewed by Dmytro Nasyrov

Founder and CTO

23+ years in custom software development. Led 70+ projects across FinTech, healthcare, Web3 and enterprise. ISO 27001 certified team.

What is quality assurance and software testing?

Quality assurance and software testing is the engineering discipline of verifying that software meets requirements, performs reliably under realistic load, and handles failure modes gracefully before reaching users. It covers manual testing (exploratory, usability, UAT), automation (unit, integration, E2E, contract), performance and load testing, security testing, accessibility testing, mobile device testing, API contract testing and regression suites tied to CI/CD pipelines. Production QA requires defect leakage metrics, test pyramid discipline, automation coverage targets, flaky test management and clear escalation paths for release blockers. Pharos has run QA engagements across FinTech, healthcare, blockchain, high-load consumer and SaaS platforms since 2015.
Authoritative citations 12 sources
  1. DORA State of DevOps Report The Google DORA State of DevOps annual report defines the four key software delivery metrics (deployment frequency, lead time for changes, mean time to restore, change failure rate) that we instrument on every production engagement to benchmark delivery performance. dora.dev
  2. Stack Overflow Developer Survey The Stack Overflow Developer Survey documents language, framework, database and tooling adoption across tens of thousands of engineers annually, and we use the trend lines to validate stack choices against hiring pool depth for each client. survey.stackoverflow.co
  3. ThoughtWorks Technology Radar The ThoughtWorks Technology Radar tracks tools, platforms, techniques and languages across adopt, trial, assess and hold rings twice yearly, and is a cross-check we use to validate architectural recommendations against industry consensus. thoughtworks.com
  4. Google SRE Book The Google SRE book codifies service-level objectives, error budgets, incident response and postmortem culture that our production readiness gates adopt directly when handing over a platform to a client operations team. sre.google
  5. Martin Fowler bliki Martin Fowler's bliki is the most cited reference for enterprise architecture patterns including microservices, strangler fig, CQRS, event sourcing and refactoring, which shapes how we describe and implement architecture decisions in ADRs on every client engagement. martinfowler.com
  6. Gartner Custom Application Services Magic Quadrant Gartner publishes multiple Magic Quadrant reports covering custom application services, digital engineering and outsourced development that identify market leaders, completeness of vision and niche specialists across the global software services industry. gartner.com
  7. ISO 27001 Information Security Standard ISO 27001:2022 defines the internationally recognized information security management system requirements that Pharos Production operates under, shaping the control framework we inherit and extend for client software engagements. iso.org
  8. OWASP Top 10 The OWASP Top 10 ranks the highest-impact web application security risks and is the single most cited threat reference for application security programs, which every Pharos build is reviewed against before production release. owasp.org
  9. NIST Secure Software Development Framework NIST SSDF SP 800-218 defines secure development practices including threat modelling, SBOM generation, vulnerability disclosure and supply chain controls, which we treat as the baseline Software Development Lifecycle checklist on every client engagement. csrc.nist.gov
  10. CNCF Cloud Native Landscape The CNCF Cloud Native Landscape maps the full cloud-native ecosystem across orchestration, runtime, observability, security and database categories, useful reference material we consult when validating platform choices for client Kubernetes and service mesh engagements. landscape.cncf.io
  11. Accelerate by Forsgren, Humble, Kim Accelerate distills the multi-year DORA research program into the book-length case for DevOps practices correlated with high-performance software delivery, and is the single most cited academic reference for the delivery metrics we ship inside every client engagement. itrevolution.com
  12. IEEE SWEBOK The IEEE Software Engineering Body of Knowledge codifies the professional knowledge areas covering requirements, design, construction, testing, maintenance, configuration management and engineering economics that underpin every professional software services engagement. computer.org
What we do not do
  • Projects without a defined quality bar or release criteria
  • Manual-only QA where automation would pay back in 3 months
  • Compliance-theater QA without remediation budget
  • QA engagements without a client-side product owner answering requirements questions

Quality assurance and testing at Pharos Production at a glance

  • QA engagements: 30+ formal QA engagements since 2015 across FinTech, healthcare, blockchain, high-load consumer and SaaS
  • Test types: Unit, integration, E2E, contract, performance/load, security (SAST/DAST), accessibility (WCAG 2.1 AA), mobile device matrix
  • Stack: Jest, Vitest, Playwright, Cypress, JUnit, pytest, Go testing, k6, Gatling, Burp Suite, axe-core, Firebase Test Lab, BrowserStack, Detox, Maestro
  • CI/CD integration: GitHub Actions, GitLab CI, CircleCI, Jenkins; quarantine-then-fix flake policy; per-PR regression on critical paths
  • Pricing: QA MVP $20,000-$60,000; full test platform $60,000-$180,000+; embedded QA engineers from $8,000/month
  • Timeline: Discovery 1-2 weeks; automation MVP 4-8 weeks; full test platform 3-6 months
  • Standards: Test pyramid discipline, defect leakage < 2%, flake rate < 1%, WCAG 2.1 AA, OWASP top-10 coverage
  • Honest scope: We recommend the lightest engagement that fits and decline compliance-theater QA

In-house QA vs outsourced QA partner: which is better?

In-house QA gives you continuous context, domain knowledge and deep product ownership. Outsourced QA partners give you specialized tooling, cross-industry experience and surge capacity for releases. According to the 2024 World Quality Report, 67% of growth-stage companies use a hybrid model: a small in-house QA team for continuous coverage plus an outsourced partner for specialized work (performance, security, accessibility, mobile device matrix).

Factor In-house QA Outsourced QA partner
Domain knowledge Deep; grows with the product over years Shallow at first; deepens over the engagement
Specialized skills Limited to who you can hire Specialists across perf, security, accessibility, mobile
Ramp time 4-12 weeks for a new QA hire to be productive 1-2 weeks for Pharos engineers to ramp on the product
Cost model Fixed salary + benefits ($80K-$180K per QA engineer) Time-and-materials or monthly retainer; scales with needs
Tooling You invest in licenses, infrastructure, training Partner brings mature tooling stack amortized across clients
Surge capacity Hard to scale up for releases; backlog risk Scale up and down as release cadence demands
Quality ownership Clear: the in-house team owns it Shared: client owns quality bar, partner owns execution
Best combination Day-to-day coverage on active product work Specialized audits, release surges, skills transfer

How we structure QA engagements

QA engagements follow Pharos Verified Delivery with test-specific gates: discovery scopes test pyramid, automation coverage targets and CI/CD integration; build delivers test suites at the appropriate level (unit → integration → E2E); production readiness covers flaky test management, defect leakage metrics and release criteria; support includes quarterly automation reviews and test maintenance.

Pharos Verified Delivery 4-phase methodology with typical durations and deliverables
  1. Phase 01 / 04

    Paid Discovery

    2-4 weeks
    • Technical validation
    • Architecture proposal
    • Scope refined estimate
    82% on-schedule with discovery
  2. Phase 02 / 04

    Iterative Build

    2-week sprints
    • Working demos every sprint
    • CTO review at milestones
    • ADRs documented
    Transparent progress tracking
  3. Phase 03 / 04

    Production Readiness

    • Monitoring and alerting
    • Security audit Pen test
    • Runbooks and rollback
    ISO 27001 compliant
  4. Phase 04 / 04

    Support

    Ongoing
    • Security patches
    • Performance tuning
    • 4h SLA response
    Continuous improvement

Pharos Verified Delivery applied to 70+ production applications since 2013

QA wins from real projects

Three QA engagements with test pyramid changes that moved defect-escape and release-cycle numbers.

Test automation rollout Q4 2024 · FinTech scale-up, EU
Before

All testing was manual. Regression cycle took 6 days before each release. Engineering team avoided risky changes between releases. Defect escape rate to production 12%.

After

Pyramid-balanced automation suite: 78% unit + 18% integration + 4% E2E. Regression cycle down to 38 minutes. Defect escape rate dropped to 1.4%. Release cadence shifted from biweekly to 2-3 times per week.

We rebuilt the test pyramid from the wrong end up. The existing "automation" was 95% slow Selenium tests against the full stack. We moved coverage to the unit layer first, then integration, then kept only 12 E2E tests for the critical user journey. Speed and reliability both improved together.

Flaky test cleanup Q1 2025 · SaaS platform, US
Before

14% of CI runs failed on flaky tests. Engineers ignored CI failures or disabled tests to unblock. Test trust was zero. Real regressions leaked to production.

After

Quarantine-then-fix policy: flaky tests moved to a separate quarantine suite, root-caused within 3 days or deleted. Flake rate dropped to 0.3%. Test trust restored; engineers actually read CI output again.

The fix was cultural, not technical. We instrumented flake detection per test, auto-quarantined any test that failed + passed on rerun, and wrote the quarantine rule into the CI config. No flake got to block a PR twice. The 3-day root-cause window forced real fixes.

Load test harness Q2 2025 · Sportsbook platform, global
Before

Load testing was a pre-launch event, not an ongoing practice. Peak betting windows caused cascading timeouts. No early warning.

After

k6 + Grafana load test harness running nightly against staging. Targets: 50,000 concurrent users, p99 latency < 200ms. Zero peak-window incidents in the 4 months since adoption. Engineering has daily visibility into regression before production.

The key move was making load testing continuous, not eventual. Nightly runs catch regressions within 24 hours; the test scenarios are version-controlled alongside the code, so load expectations travel with the features they test.

Client names anonymized under NDA. Full case studies at /cases/.

When a full QA engagement is not the answer

We decline roughly 30% of RFPs we receive. Forcing a bad fit costs both sides 3-6 months and damages outcomes. Here is how we think about scope:

Projects we decline
  • Projects without a defined quality bar or release criteria
  • Manual-only QA where automation would pay back in 3 months
  • Compliance-theater QA without remediation budget
  • QA without a client-side product owner answering requirements questions
  • "Automate everything" projects without a test pyramid plan
We recommend the right depth of QA

Not every project needs a full QA team. Sometimes a unit test culture and a small E2E smoke suite is the right level of investment. Sometimes a 2-week test automation bootcamp transfers skills to the client team and exits. We start by understanding the actual quality problem and recommend the appropriate depth. We have closed engagements with "your unit tests are good, the gap is a 6-test E2E smoke suite" as the whole deliverable.

Pharos Production QA and testing portfolio observations

Observations from 26 QA engagements delivered 2020-2026 across FinTech, healthcare, SaaS and e-commerce.

  • Teams with over 80 percent unit coverage plus contract tests had 3.4x lower production defect rate than teams with unit-only coverage in matched cohorts.

  • Flake-rate budgets under 1 percent correlated with over 90 percent engineer confidence in suite signal; budgets over 3 percent correlated with engineers disabling or ignoring failures.

  • Ephemeral per-PR environments reduced PR merge time by 38 percent on average across 8 projects that adopted them.

  • Teams of 2 to 4 QA engineers plus test-engineering platform support sustained full coverage across 50-plus service codebases in our portfolio.

QA and testing outlook 2026-2027

How to evaluate a QA engagement before production gate

Lesson from production: the flaky test tax

A SaaS customer had 2,400 E2E tests in 2023 with 18 percent weekly flake rate. Engineering disabled failing tests rather than fixing them; the suite became meaningless, and 4 production incidents in 6 months traced to scenarios the disabled tests had originally covered. Root cause: flake rate over 3 percent destroys signal-to-noise; engineers disabled as a coping mechanism. We declared flake-rate bankruptcy: quarantined the flaky 18 percent, rebuilt the critical 15 percent with stronger fixtures and deterministic test data, and set a flake budget of 1 percent beyond which the suite blocks merges. Six months later, suite is 1,800 tests with 0.7 percent flake rate, and production incidents traceable to E2E gaps dropped to zero. The lesson: a flaky test suite is worse than no test suite because it teaches engineers to ignore signal.

How defect leakage and flake rates are measured
QA metrics counted: production engagements with defect leakage measurements and automation coverage against the test pyramid. Regression cycle times measured against client-reported pre-engagement baselines. Flake rates measured from actual CI statistics, not estimates. Last reviewed: April 2026. Editorial policy.
Scope and testing limits
Pharos Production provides QA and testing services. Testing reduces defect risk but cannot eliminate it. Compliance certifications (SOC 2, ISO 27001) are issued by accredited auditors based on the systems we deliver, not by Pharos.

Platforms We Work With

Trusted by Coinbase, Consensys, Core Scientific, MicroStrategy, Gate.io and 10+ more Web3 and enterprise platforms

16+ partners

Our 16 technology partners include:

  • Consensys
  • Gate Io
  • Coinbase
  • Ludo
  • Core Scientific
  • Debut Infotech
  • Axoni
  • Alchemy
  • Starkware
  • Mara Holdings
  • Microstrategy
  • Nubank
  • Okx
  • Uniswap
  • Riot
  • Leeway Hertz
  • Consensys logo Consensys
  • Gate Io logo Gate Io
  • Coinbase logo Coinbase
  • Core Scientific logo Core Scientific
  • Debut Infotech logo Debut Infotech
  • Axoni logo Axoni
  • Alchemy logo Alchemy
  • Starkware logo Starkware
  • Mara Holdings logo Mara Holdings
  • Microstrategy logo Microstrategy
  • Nubank logo Nubank
  • Okx logo Okx
  • Uniswap logo Uniswap
  • Riot logo Riot
  • Leeway Hertz logo Leeway Hertz

About Founder and CTO

Dmytro Nasyrov

Dmytro Nasyrov

Founder and CTO Pharos Production

Ask the founder a question

I design and build reliable software solutions — from lightweight apps to high-load distributed systems and blockchain platforms.

PhD in Artificial Intelligence, MSc in Computer Science (with honors), MSc in Electronics & Precision Mechanics.

  • 12 years in architecture of great software solutions tailored to customer needs for startups and enterprises

  • 23 years of practical enterprise customized software production experience

  • Lecturer at the National Kyiv Polytechnic University

  • Doctor of Philosophy in Artificial Intelligence

  • Master’s degree in Computer Science, completed with excellence

  • Master’s degree in Electronics and precision mechanics engineering

Choose your cooperation model

MVP
MVP sprint

Scoped MVP with core user flows, clean codebase and production-ready deployment.

$8,500 - $21,000
Popular choice
Production
Production release

Full-feature build, QA, CI/CD and post-launch stabilization with SLA-backed support.

$22,000 - $45,000
Full-cycle
Full-cycle platform

End-to-end engagement: discovery, architecture, build, DevOps, QA and long-term evolution.

$45,000 - $85,000

Prices vary based on project scope, complexity, timeline and requirements. Contact us for a personalized estimate.

Or select the appropriate interaction model

Request staff augmentation

Need extra hands on your software project? Our developers can jump in at any stage – from architecture to auditing – and integrate seamlessly with your team to fill any technical gaps.

Outsource your project

From first line to final audit, we handle the entire development process. We will deliver secure, production-ready software, while you can focus on your business.

187+ technologies

Technologies, tools and frameworks we use

Our engineers work with 187+ technologies across blockchain, backend, frontend, mobile and DevOps - chosen for production reliability and performance.

Frameworks

Backend Frameworks 8

Spring Boot
Spring Boot
Erlang OTP
Erlang OTP
NodeJS
NodeJS
Phoenix
Phoenix
NestJS
NestJS
Django
FastAPI
Express.js

Front End Frameworks 8

React
React
Next.JS
Next.JS
Svelte
Svelte
Angular
Angular
Vue.js
Remix
Astro
Nuxt.js

AI and Machine Learning

LLM Providers 8

OpenAI GPT
Anthropic Claude
Google Gemini
Meta Llama
Mistral AI
Cohere
Ollama
xAI Grok

AI Frameworks 15

LangChain
LangGraph
CrewAI
AutoGen
Hugging Face
PyTorch
TensorFlow
scikit-learn
LlamaIndex
Keras
XGBoost
LightGBM
OpenCV
spaCy
ONNX Runtime

Vector Databases 7

Pinecone
Weaviate
Qdrant
Chroma
pgvector
Milvus
FAISS

MLOps and Infrastructure 11

MLflow
Weights & Biases
DVC
Kubeflow
AWS SageMaker
Azure ML
Google Vertex AI
NVIDIA Triton
Airflow
Ray Serve
vLLM

AI Agent Tools 4

OpenAI Agents SDK
Claude MCP
Semantic Kernel
Haystack

Blockchains

Private and Public Blockchains 33

Ethereum
Ethereum
TON
TON
Corda
Corda
Tron
Tron
Hedera
Hedera
Stellar
Stellar
Consensys GoQuorum
Consensys GoQuorum
Solana
Solana
Arbitrum
Arbitrum
Binance Smart Chain (BSC)
Binance Smart Chain (BSC)
Sei
Sei
Celo
Celo
Hyperledger
Hyperledger
MultiversX
MultiversX
IOTA
IOTA
Polkadot
Polkadot
Aptos
Aptos
Neo
Neo
Flow
Flow
Algorand
Algorand
Avalanche
Avalanche
EOS
EOS
Optimism
Optimism
Polygon
Polygon
Cosmos
Cosmos
Sui
Sui
Tezos
Tezos
Ontology
Ontology
Fantom
Fantom
NEAR Protocol
NEAR Protocol
VeChain
VeChain
Base
Base
IPFS
IPFS

Cloud Blockchain Solutions 4

Amazon Managed Blockchain
Amazon Managed Blockchain
Amazon QLDB
Amazon QLDB
IBM Blockchain
IBM Blockchain
Oracle Blockchain
Oracle Blockchain

DevOps

DevOps Tools 15

Kubernetes
Kubernetes
Terraform
Terraform
Docker
Docker
Istio
Istio
Prometheus
Prometheus
Grafana
Grafana
Jenkins
Jenkins
ArgoCD
ArgoCD
Ansible
Ansible
GitHub Actions
GitLab CI
Pulumi
Datadog
New Relic
Vault

Clouds

Clouds 6

Amazon Web Services
Amazon Web Services
Azure
Azure
Google Cloud
Google Cloud
Cloudflare
Vercel
DigitalOcean

Databases

Databases 15

PostgreSQL
PostgreSQL
MySQL MariaDB
MySQL MariaDB
Redis
Redis
Cassandra
Cassandra
Neo4J
Neo4J
MongoDB
MongoDB
Elasticsearch
Elasticsearch
Solr
Solr
Ignite
Ignite
ClickHouse
TimescaleDB
DynamoDB
Supabase
CockroachDB
ScyllaDB

Brokers

Event and Message Brokers 7

Kafka
Kafka
RabbitMQ
RabbitMQ
Flink
Flink
Apache Pulsar
Amazon SQS
Amazon SNS
NATS

Tests

Test Automation Tools 6

Postman
Postman
Appium
Appium
Cucumber
Cucumber
Selenium
Selenium
JMeter
JMeter
Cypress
Cypress

Programming

UI/UX

UI/UX Design Tools 12

Figma
Figma
Zeplin
Zeplin
InVision
InVision
Sketch
Sketch
Miro
Miro
Marvel
Marvel
Balsamiq
Balsamiq
Photoshop
Photoshop
Illustrator
Illustrator
XD
XD
After Effects
After Effects
Corel Draw
Corel Draw
Trusted & Certified

Partnerships & Awards

Recognized on Clutch, GoodFirms and The Manifest for software engineering excellence

  • Partner1
  • Partner2
  • Partner3
  • Partner4
  • Partner5
17+ industry awards

An approach to the development cycle

The Pharos Delivery Framework divides every project into 2-week sprints. After each sprint there is a retrospective of the work done, planning for the next sprint, a report of the work done and a plan for the next sprint. This methodology is why agile projects are 3x more likely to succeed than waterfall (Standish Group CHAOS Report, 2024).
  1. Team Assembly

    Our company starts and assembles an entire project specialists with the perfect blend of skills and experience to start the work.

  2. MVP

    We’ll design, build, and launch your MVP, ensuring it meets the core requirements of your software solution.

  3. Production

    We’ll create a complete software solution that is custom-made to meet your exact specifications.

  4. Ongoing

    Continuous Support

    Our company will be right there with you, keeping your software solution running smoothly, fixing issues, and rolling out updates.

FAQ

Last updated: Reviewed by: Dmytro Nasyrov (Founder and CTO)

Quick answers to common questions about custom software development, pricing, process and technology.

  • Copy link Copies a direct link to this answer to your clipboard.

    The right answer depends on release cadence, regression cost and team size - but the shape should be a pyramid. Target ~70% unit tests (fast, focused on logic), ~20% integration tests (fast, focused on boundaries), ~10% E2E tests (slow, focused on the 5-10 critical user journeys).

    If your ratio is flipped (mostly E2E), your CI is slow and flaky by construction. The fix is to move coverage down the pyramid, not to add more E2E tests.

  • Copy link Copies a direct link to this answer to your clipboard.

    QA MVP (audit + critical-path automation + CI integration): 4-8 weeks. Full test platform (automation coverage targets, performance harness, security baseline, accessibility audit): 3-6 months.

    Embedded QA engineer supporting release cycles: month-to-month. We do not recommend engagements under one month - the ramp cost outweighs the value.

  • Copy link Copies a direct link to this answer to your clipboard.

    QA audit + roadmap from $8,000. Automation MVP $20,000-$60,000 (critical-path suite + CI integration).

    Full test platform $60,000-$180,000+ (pyramid, performance, security, accessibility, monitoring). Embedded QA engineer from $8,000/month. Cost drivers: codebase size, test pyramid starting state, release cadence, compliance requirements.

  • Copy link Copies a direct link to this answer to your clipboard.

    Quarantine-then-fix policy. Any test that fails then passes on rerun gets auto-quarantined into a separate suite.

    Quarantined tests have a 3-day root-cause window before being deleted. We instrument per-test flake rates in CI dashboards so flakes surface early. Flaky tests are worse than no tests - they train engineers to ignore CI, which is how real regressions leak to production.

  • Copy link Copies a direct link to this answer to your clipboard.

    Yes. k6 or Gatling for scripted load testing, Grafana + Prometheus for observability, JMeter for legacy protocols.

    Tests run in CI nightly against staging with clear targets (concurrent users, request rate, p99 latency, error rate). We have built load harnesses for sportsbook platforms at 50,000 concurrent users, payment systems at 12,000 transactions/second and SaaS platforms handling millions of daily API calls.

  • Copy link Copies a direct link to this answer to your clipboard.

    Yes. Accessibility: axe-core in CI for WCAG 2.1 AA, manual screen reader audits (NVDA, VoiceOver) on critical flows.

    Security: Semgrep + CodeQL for SAST, OWASP ZAP or Burp Suite for DAST, Snyk or Trivy for dependency scanning, secrets detection via gitleaks. Both are integrated into the CI pipeline so regressions surface at PR time.

  • Copy link Copies a direct link to this answer to your clipboard.

    Yes. Firebase Test Lab for Android (15-25 representative devices per run), BrowserStack or Sauce Labs for iOS + Android + browser matrix, Appium or Detox for cross-platform UI automation, XCUITest for native iOS, Espresso for native Android.

    We scope the device matrix during discovery based on the target market - emerging markets need different devices than US-only apps.

  • Copy link Copies a direct link to this answer to your clipboard.

    We decline projects without a defined quality bar or release criteria, manual-only QA where automation would pay back in 3 months, compliance-theater QA without remediation budget, engagements without a client-side product owner answering requirements questions, and “automate everything” projects without a test pyramid plan. We also decline engagements shorter than one month.

The Pharos takeaway on QA and testing

QA and testing in 2026 is a continuous capability, not a release gate. Pharos Production builds QA programs with contract tests, deterministic E2E, ephemeral environments and production observability closed into the QA loop, so defects surface in CI, not in production.

Dmytro Nasyrov, Founder and CTO at Pharos Production
Dmytro Nasyrov Founder & CTO Let’s work together!

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Our offices

Headquarters in Las Vegas, Nevada. Engineering office in Kyiv, Ukraine.

Las Vegas, United States

Headquarters PST (UTC-8)
5348 Vegas Dr, Las Vegas, Nevada 89108, United States

Kyiv, Ukraine

Engineering office EET (UTC+2)
44-B Eugene Konovalets Str. Suite 201, Kyiv 01133, Ukraine