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Quality Assurance for systems with complex workflows

Azati provides QA outsourcing for fintech, core banking, insurance, AI, and enterprise SaaS, where production failures can cost a fortune, and compliance is non-negotiable. We specialize in QA for complex systems and high-risk solutions with multi-service workflows. Make sure Azati reduces production bugs by 60-80% without slowing down your release cycle.

Get a QA risk audit
2-4 weeks
to the first improvements
60-80%
reduced production bugs
2.5X faster
release speed
Postman Fiddler Jmeter Gatling TestRail Allure Cucumber Cypress Playwright Selenide Selenoid Serenity WebdriverIO Postman Fiddler Jmeter Gatling TestRail Allure Cucumber Cypress Playwright Selenide Selenoid Serenity WebdriverIO

Azati helps clients prevent production failures. Here’s what they say

Clutch Badge
"What might take me three or four days to figure out how to do, Azati can do in a couple of hours because of their existing knowledge."
Axel Sturmann
IT Manager, Venstar Exchange
5 star rating
"The app has never crashed, which is a testament to the quality of the code they put into this."
Enrique Franklin
Co-founder at HOPNBR
5 star rating
"Azati shows great experience, knowledge, and professionalism. We are well satisfied with their work and are planning to include Azati in future development and operation."
Sebastian Schmidt
COO at MusicDNA
5 star rating
"Our users love the portal, which is the reason we've been successful."
Martin Goffman
CEO at SequenceBase
5 star rating
"They expected pain points and responded to our needs, flexibly adapting to the ever-changing scope or requirements."
Liza Sudareva
CMO at LoveMobile
5 star rating

A snapshot of Azati's QA expertise

2002

Azati's dedicated QA department was created

70+

successful QA projects

17

industries covered

25+

professional QA engineers

BFSI & Petroleum

signature market sectors

Europe

major delivery region

GDPR, DORA, KYC, AML

regulations compliance

ISO 27001, 27701, 9001

accreditation in progress

Before you scroll. When to engage Azati’s QA for complex systems?

Azati QA experts are your guys if you're dealing with at least one of these:

  • Releases feel risky ("Fingers crossed nothing breaks" every time)
  • Expensive, compliance-sensitive bugs already reach production
  • Internal QA is overloaded with frequent deployments
  • Automation is already in place, but is missing many real-world edge cases
  • QA support is slowing down development, not the other way round
  • Your system depends on multiple collaborative services

Azati provides specialized QA for high-risk systems

Sometimes standard QA isn't enough. Specifically, if you handle payments or loans, support AI infrastructure, juggle multiple sensitive workflows, or face regulatory pressure. Azati’s outsourced QA prevents costly failures by providing:

  • Core banking QA and loan processing systems
  • Financial workflow QA services for transactional platforms
  • AI testing for data-heavy enterprise ecosystems
  • QA services for enterprise SaaS with multi-step workflows, scaled
  • Testing AI document systems and claims automation
  • QA for payment processing and billing engines

Azati QA serves regulated environments

Azatians have been addressing high-stakes projects for decades. Where each step defines the outcome’s success, our QA team finds the optimized winning path. They introduce test automation for legacy apps, migrate to modern testing frameworks, and establish quality gates without slowing down non-stop development.

  • Validation for complex transactions spans multiple steps and services
  • Maintaining European data sovereignty and compliance is an absolute must
  • Workflows run on legacy systems, and you consider migration
  • Systems depend on automated QA for APIs and microservices
  • AI solutions handle sensitive data or business-critical operations
  • Releases are shipped weekly or even daily

Azati's recent quality assurance projects

Nine out of ten clients tend to note Azati's proactive approach to quality assurance. This deep understanding of what a single bug may cost in data-heavy systems has won us tens of contracts involving AI testing, core banking QA, system testing for fintech, and validation for complex transactions.

Revolutionizing Banking: Automated Promotions Management
Banking & Finance

Revolutionizing Banking: Campaign Processing QA

90% Reduction in Critical Defects Post-release
3x faster regression cycles across promotion services
95% test-case automation coverage for the core promotion engine
  • Java
  • Spring
  • Kafka
  • Test Automation

⚡ Pain Points We Tackled

A major banking institution needed to modernize its promotions management system. Its legacy module had issues with access control, frequent production bugs, and manual workload across campaign management. The goal was to automate the promotion engine, ensure high reliability in a regulated banking environment, and streamline continuous deployment of promotional campaigns.

Our Approach

Azati embedded QA and testing expertise from the start of the project. Our team helped the client define test strategies for the promotions microservice, set up full-cycle testing (unit, integration, end-to-end), and created a strong feedback loop covering both business and technical risks. We paid special attention to banking-specific concerns: access control, data integrity, regulatory documentation, and high throughput for campaigns.

Applied Methods and Practices

  • Defined a layered test strategy: Unit tests for business logic (Java/Spring), integration tests for service communication (Kafka, PostgreSQL), and end-to-end tests for promotion workflows.
  • Used test-containers and Docker environments: Replicated production-like infrastructure for reliable testing.
  • Incorporated security and access tests: Role-based access, promotion entitlement, audit trails.
  • Integrated QA into CI/CD pipelines: Each build triggered tests, preventing low-quality code from reaching production.

Solution Features

  • Automated Promotions Engine: Fully automated microservice with verified business logic, deployed in a regulated, banking-grade architecture.
  • QA Dashboards: Real-time visibility on pass/fail rates, code coverage, regression cycle times, and critical bug trends.
  • Security Compliance: Embedded security tests, role-based access controls, and audit trails to ensure compliance with banking regulations.
  • Audit-Ready Documentation: Comprehensive documentation of test cases, business risks, and regulatory requirements for full traceability.
Read Full Case Study
Insurance Self-Service QA
Insurance

Insurance Self-Service QA: Security, UX, Scalability

92% fewer production bugs
2.5x faster regression testing
99% test-case pass rate before release
  • Web QA
  • Mobile QA
  • JUnit
  • TestNG

⚡ Pain Points We Tackled

The client, an insurance company with a self-service web platform, faced complex workflow inconsistencies, data integrity risks, and limited QA coverage, which affected customer experience and operational efficiency. Multi-step processes like policy management and customer interactions were prone to errors, slowing down releases and increasing support overhead. Our task was to provide full-cycle quality assurance to stabilize the platform, ensure workflow accuracy, and improve release reliability.

Our Approach

Azati's QA team worked closely with the client to analyze insurance-specific workflows such as policy management, customer self-service actions, and backend integrations. We combined manual and automated testing, focusing on validating business logic, ensuring data consistency across systems, and covering real-world user scenarios. Special attention was given to multi-step workflows, integrations with backend systems (CRM, billing, databases), and edge cases that could impact compliance and customer trust.

Applied Methods and Practices

  • Comprehensive Test Plan: Designed a full QA strategy covering functional, regression, integration, and usability testing, ensuring all insurance workflows and user scenarios were validated.
  • Automated Regression Testing: Implemented automation for critical user journeys such as policy updates, account management, and data submission, reducing regression time and improving release speed.
  • Manual Exploratory Testing: Focused on uncovering edge cases in complex workflows, including multi-step user interactions, data validation issues, and rare failure scenarios.
  • Integration Testing: Validated interactions between the self-service platform and backend systems (CRM, billing, and data services), ensuring consistency and reliability across the ecosystem.
  • Data Integrity Validation: Ensured accuracy and synchronization of customer and policy data across all stages of the workflow.
  • QA Integration in CI/CD: Embedded QA processes into the development pipeline, enabling continuous testing and faster feedback.

Solution Features

  • End-to-End Workflow Coverage: Comprehensive validation of insurance processes, including policy management, customer interactions, and backend operations.
  • Automated Regression Suite: Fast verification of critical workflows after each release, enabling safer and quicker deployments.
  • Integration Reliability: Stable communication between frontend and backend systems, reducing data inconsistencies and system errors.
  • Risk-Based Bug Prioritization: Issues prioritized based on business impact (e.g., policy errors, data inconsistencies), ensuring critical problems were addressed first.
Read Full Case Study
Oil & Gas QA
Oil & Gas

Oil & Gas Corporate Web Platform Quality Assurance

87% critical production bugs reduction
2.5x faster regression testing
99.3% test-case pass rate before release
  • Test automation
  • Web QA
  • JavaScript
  • PHP

⚡ Pain Points We Tackled

The client, an oil & gas enterprise undergoing digital transformation, relied on a web platform for managing operational data, workflows, and reporting. The system faced issues with inconsistent data across modules, performance bottlenecks, and limited QA coverage, which slowed down adoption and created risks in decision-making. Our task was to establish a reliable QA process, ensure data consistency across integrated systems, and improve platform stability and performance during ongoing transformation.

Our Approach

Azati's QA team focused on validating complex enterprise workflows, large data flows, and system integrations. We combined manual and automated testing, with emphasis on ensuring accuracy of operational data, stability under load, and correctness of multi-step business processes. Special attention was given to data synchronization across modules and services, performance under real-world usage scenarios, workflow validation for operational processes, and integration reliability across legacy and modern systems.

Applied Methods and Practices

  • Comprehensive Test Strategy: Defined and executed a QA approach covering functional, regression, integration, and performance testing for the enterprise platform.
  • Data Integrity Validation: Ensured consistency and correctness of operational data across dashboards, reports, and backend systems.
  • Integration Testing: Validated interactions between multiple system components, including legacy infrastructure and new digital modules.
  • Performance Testing: Identified and addressed bottlenecks in data-heavy operations and reporting workflows.
  • Manual Exploratory Testing: Tested real-world usage scenarios and edge cases in complex operational workflows.
  • Automation for Regression: Implemented automated tests for critical user paths to support continuous delivery and reduce regression risks.

Solution Features

  • End-to-End Workflow Coverage: Validation of operational processes across the platform, ensuring accuracy and reliability.
  • Data Consistency Assurance: Robust checks across systems to prevent discrepancies in critical business data.
  • Improved System Performance: QA-driven insights helped optimize platform responsiveness and stability.
  • Integration Reliability: Stable communication between legacy and modern components.
  • Risk-Based Testing Approach: Focused on high-impact areas such as reporting accuracy, data flows, and system performance.
Read Full Case Study
Life sciences QA
Life sciences

AI-Powered Patent & Sequence Intelligence QA

30% better stability across 8 releases
~20% faster response for complex queries
40% fewer irrelevant recommendations
  • QA
  • Python
  • Llama
  • MinIO

⚡ Pain Points We Tackled

The client, a platform for high-speed search across biological sequences and patent data, faced challenges with result accuracy, system stability under heavy computational load, and session-level data confidentiality. Resource-intensive operations (e.g., BLAST searches, combined queries, large dataset exports) increased the risk of inconsistent results, slow response times, and unreliable outputs. Our task was to establish a predictable QA and validation process, reduce the risk of false or ambiguous results, and ensure the platform met strict reliability and performance standards required by a professional audience.

Our Approach

Azati's QA team focused on deep validation of data accuracy, system behavior under load, and AI-assisted recommendations. We combined manual and automated testing, with emphasis on domain-specific scenarios, complex query logic, and multi-step processing pipelines. Special attention was given to high-load scenarios and performance bottlenecks, data consistency across search, filtering, and export flows, validation of AI-driven recommendations, and end-to-end workflow reliability under real usage conditions.

Applied Methods and Practices

  • Comprehensive Test Strategy: Designed a QA framework covering functional, regression, performance, and data validation testing for complex search and analysis workflows.
  • Performance & Load Testing: Simulated heavy computational scenarios (BLAST queries, combined searches, large exports) to identify bottlenecks and optimize system response times.
  • Data Accuracy Validation: Ensured that search results, filtered datasets, and exported data remained consistent and correct across all workflows.
  • AI Output Validation: Implemented structured validation of AI-generated recommendations, including feedback loops with domain experts to improve relevance and reduce ambiguity.
  • Manual Exploratory Testing: Tested edge cases in complex query combinations and rare scenarios that could impact result accuracy or system stability.
  • Workflow & State Validation: Verified correctness of multi-step processing pipelines and state transitions, ensuring reliability across chained operations.

Solution Features

  • High-Load Stability Coverage: Robust QA processes ensure stable system behavior under resource-intensive operations.
  • Data Integrity Assurance: End-to-end validation of search results and exported datasets, guaranteeing consistency with applied filters.
  • AI Recommendation Accuracy: Improved reliability of AI outputs through continuous validation and expert feedback integration.
  • Performance Optimization Support: QA-driven insights contributed to faster response times and more efficient processing pipelines.
  • Risk-Based Validation Approach: Focused testing on high-impact areas such as query accuracy, data consistency, and system performance.
Read Full Case Study

Meet the leaders behind Azati's QA success stories

QA Team Lead
At Azati, quality assurance doesn’t boil down to testing. As we deal with high-stakes projects with no room for mistakes, ours is to encode trust right into the product. Our approach? We balance manual and automated testing to ensure ultimate security and stability, regardless of edge cases. Our QA team sits with development folks to catch issues early, minimize risks, and speed up delivery. We are proactive, project after project. This gives our clients an edge, no matter how rigid the standards are within regulated industries.
Dzimitry
Director of QA and Test Automation
Lead Software QA Engineer
Azati teaches me to be many things to many people. From advisor to strategic testing heavy-lifter, all the way to the main point of contact between the client and the team. Leadership roles are not really about being superior to teammates. Mine is about juggling massive challenges, burning tasks, and responsibilities, graciously.
Kasia
Lead Software QA Engineer
Lead Test Automation Engineer
Test automation takes analytical thinking, more than anything. This, alongside my fascination with mathematically predictable outcomes, landed me where I belong, at the Azati QA automation team. Testing evolves non-stop, meaning our approach should become more intelligent as well. Which is why my mission is to supercharge each solution I design with future-ready scalability and performance.
Eugene
Lead Test Automation Engineer

Product types Azati QA specializes in

From insurance platforms to real-time pricing calculation and contract testing solutions integrated into CI/CD pipelines, Azati QA steps in to rescue stuck deployments, flag impactful anomalies, and save you millions on production recovery.

Transactional systems

Azati QA performance by system type

System type QA model Automation % Bug reduction Time to impact
Core banking Dedicated QA 85% 75% 6-8 weeks
Fintech SaaS Hybrid QA 80% 65% 4-6 weeks
Insurance workflows Dedicated QA 90% 70% 6-10 weeks
API platforms Automation-heavy 75% 60% 3-5 weeks
AI document systems Hybrid QA 70% 55% 4-6 weeks

How Azati reduces production bugs in complex systems by 60–80%

Azati’s outsourced QA team has fine-tuned its process to score a 99% bug-detection rate before production, resulting in up to 80% fewer post-release issues. Our end-to-end QA covers test planning, automation, performance, and security validation. Today, Azati’s battle-tested framework ensures efficient system testing for fintech, banking, insurance, AI workflows, and other complex workflows.

Azati identifies your system’s failure points and where the breaks can seriously affect operations.

  • Mapping critical workflows, including payments, claims, and approvals
  • Detecting weaknesses across APIs and services
  • Executing a QA risk audit to prioritize high-impact areas

Struggling to reduce production bugs? Azati handles QA risk audits

No need for long-term lock-ins. Start small and scale whenever ready. Make sure the engagement with Azati's outsourced QA team is low-risk for you:

  • Start with a QA risk audit, not a full commitment
  • Zoom in on your critical workflow and API vulnerabilities
  • Obtain a clearly prioritized QA roadmap before scaling
  • Witness measurable improvements within weeks
Book an initial QA risk assessment

What you get: Azati’s full QA coverage for high-risk systems

What’s Azati QA team’s endgame? In a nutshell, it’s your confidence before release, real-world workflow coverage, and fast feedback loops in CI/CD. This is what turns 95% of our customers into repeat clients and partners.

Web and mobile testing

  • Cross-platform and cross-browser testing
  • End-to-end user experience testing
  • Regression testing (manual and automation)

Backend and API validation

  • Automated QA for APIs
  • Contract testing for financial systems
  • Data integrity checks

Automated testing

  • Regression automation (Cypress, Playwright)
  • Performance testing and integration testing services
  • CI/CD integration to automate QA in your pipeline
  • Faster, safer releases with continuous feedback

Manual testing

  • Exploratory testing for edge cases and critical workflows
  • End-to-end validation of integrated systems, from UI to backend
  • User experience validation within real usage conditions

Workflow-driven AI systems

  • End-to-end AI workflow testing (approval systems)
  • Validating AI decisions inside complex financial workflows
  • Edge scenarios for systems where errors have real cost
  • Integration testing across multiple synced services

AI document systems

  • Testing AI document systems
  • AI output validation (AI invoice processing, claims automation)
  • AI components testing in API-driven architectures (banking platforms, backend AI services)
  • Regression testing for AI systems

Financial workflow QA services

  • QA for payment processing and billing systems
  • Loan origination and servicing
  • Core banking QA and transactional systems

Insurance workflows QA services

  • Claims processing validation, policy management testing
  • Underwriting and approval business logic validation
  • Integration testing for CRM, MDM, billing, and third-party services
  • Data integrity checks across systems and lifecycle stages

Result: faster, safer releases

  • Reduce production bugs by 60-80%
  • Reduced rework and faster time-to-market
  • Fewer production incidents
  • More predictable delivery
  • Assessment for regulatory compliance

Quick self-check. If you’re searching for “financial workflow QA services” or "automated QA for APIs", your live system’s bugs might’ve already cost you a month of downtime. Worth evaluating real visibility into failure points.

Estimate your QA effort

Azati’s go-to tech stack for quality assurance

Azati’s manual QA stack (QA Engineering)

Test management

QA tools & technologies: TestRail, Zephyr for Jira, Xray for Jira, Qase, Allure TestOps, Test IT, QTest, TestLink, Test IO

Clients’ wins: Full process transparency: Azati lets you track test coverage, progress, and results in real time

Issue tracking

QA tools & technologies: Jira, YouTrack, Azure DevOps, Redmine, Trello, Yandex Tracker, Bitrix24

Clients’ wins: Seamless integration with your workflows. Azati uses your go-to tools

API testing

QA tools & technologies: Postman, SoapUI, Swagger, GraphQL

Clients’ wins: Fast validation of integrations and business logic with no need to wait for the frontend

Web inspection

QA tools & technologies: Chrome DevTools, XPath, CSS Selectors, HTML5, Figma, Zeplin

Clients’ wins: Pixel-perfect validation against designs and faster root-cause analysis of UI issues

Cross-platform testing

QA tools & technologies: BrowserStack, iOS, Android, Windows, macOS, Linux

Clients’ wins: Help Azati ensure consistent performance across all target devices and operating systems

Network debugging

QA tools & technologies: Charles Proxy, Fiddler, Proxyman

Clients’ wins: Allow Azati to test unstable network scenarios, intercept and modify requests to simulate real-world conditions

Data validation

QA tools & technologies: SQL (PostgreSQL, MySQL, Oracle, MSSQL), MongoDB, PL/SQL, DBeaver

Clients’ wins: Used by Azati QA to verify data integrity and enforce business rules at the database level

Data formats

QA tools & technologies: JSON, XML, CSV

Clients’ wins: Ensure correct processing and display of structured data across systems

Monitoring & logs

QA tools & technologies: Kibana, Grafana Loki, Splunk, New Relic, Grafana

Clients’ wins: Assist Azati QA in faster incident investigation through logs and system metrics analysis

Collaboration

QA tools & technologies: Confluence, XWiki, Google Docs, MS Office, SharePoint

Clients’ wins: Employed by Azati for clear documentation, structured reporting, and fast alignment with stakeholders

Server access

QA tools & technologies: WinSCP, PuTTY, FileZilla, MobaXterm, SSH, Super PuTTY

Clients’ wins: Ensure Azati’s direct access to logs and configs in test environments for faster debugging

AI assistants for test design

QA tools & technologies: ChatGPT (OpenAI), Claude (Anthropic), Microsoft Copilot, Gemini (Google), Perplexity AI, Qwen

Clients’ wins: Help Azati QA speed up creation of comprehensible test plans, checklists, test cases, onboarding docs, and release notes

Azati’s test automation stack: QA Automation Engineering

Programming languages

QA tools & technologies: Java, JavaScript/TypeScript, Python, C#, SQL

Clients’ wins: Flexibility to match your tech stack. Azati uses your product’s language to build tests

UI automation

QA tools & technologies: Playwright, Selenium (WebDriver/Grid/IDE), Cypress, WebdriverIO, Selenide, Serenity

Clients’ wins: Help Azati develop stable, fast, and maintainable tests that don’t break with minor UI changes

Mobile automation

QA tools & technologies: Appium, Android Studio, Xcode

Clients’ wins: Azati’s unified testing approach for native and cross-platform mobile apps

API automation

QA tools & technologies: RestAssured, Karate, Postman/Newman, GraphQL, Node.js libraries

Clients’ wins: Allows Azati QA to automate the validation of hundreds of integration scenarios in minutes

Frameworks & patterns

QA tools & technologies: TestNG, JUnit, Cucumber (BDD), Robot Framework, Page Object Model, Data-Driven

Clients’ wins: Azati’s foundation for scalable, readable tests that double as product specifications

Execution & infrastructure

QA tools & technologies: Jenkins, GitLab CI/CD, TeamCity, Docker, Selenoid

Clients’ wins: Automated test execution on every Azati’s commit. Ensure that bugs are detected early

Build & dependencies

QA tools & technologies: Apache Maven, Gradle, Apache Ant, npm, Nexus Repository, DockerHub

Clients’ wins: Used by Azati for seamless integration into your build and deployment pipelines

Reporting

QA tools & technologies: Allure Report, Allure TestOps, Grafana

Clients’ wins: Azati’s clear dashboards for showcasing quality trends, coverage, and bottlenecks with no need to scrape through the code

Search & queues

QA tools & technologies: Elasticsearch, Conduktor (Kafka UI)

Clients’ wins: Helps Azati test asynchronous flows and full-text search scenarios

Performance testing

QA tools & technologies: Apache JMeter, Gatling, k6

Clients’ wins: Assist Azati in validating system behavior under peak load before users experience it

Platform integrations

QA tools & technologies: Apache Tomcat, WebLogic, JBoss EAP, WebSphere, Liferay, Camunda, Documentum

Clients’ wins: Provides experience with enterprise environments close to production conditions

Version control

QA tools & technologies: Git, SVN, GitLab, GitHub, Bitbucket

Clients’ wins: Log full test change and code review history, and create Azati’s collaborative test development

IDE & development environments

QA tools & technologies: IntelliJ IDEA, VS Code, PyCharm, WebStorm, Eclipse

Clients’ wins: Modern IDEs help Azati develop and debug tests faster

AI assistants for test design

QA tools & technologies: ChatGPT (OpenAI), Claude (Anthropic), Microsoft Copilot, Gemini (Google), Perplexity AI, Qwen

Clients’ wins: Help Azati QA accelerate building comprehensible test plans, checklists, test cases, onboarding guides, and release notes

AI agents for test development

QA tools & technologies: Cursor, GitHub Copilot, Qwen-Coder, Codeium

Clients’ wins: Assist in quickly creating tests with auto-generation, locator suggestions, and pattern guidance, which drives 2-3X faster development by Azati QA

Azati implements test automation that scales with your product

Azati builds robust, maintainable automation frameworks covering UI, API, integration, and regression testing. Our solutions integrate with CI/CD pipelines, enable parallel execution, and deliver instant feedback, accelerating release cycles without compromising quality.

Azati’s extended QA service range

Quality assurance consulting

Our experienced QA engineers provide custom QA consulting to help you optimize processes and define the most effective quality assurance strategy for your project.

Dedicated testing teams

Hire a dedicated QA team from Azati to focus solely on your project, ensuring seamless collaboration, consistent quality, and faster, more reliable software delivery.

Extended QA coverage

Azati delivers robust, reliable testing using functional, integration, and unit tests, covering up to 87% of your codebase to minimize risk and ensure stability.

Azati supports flexible QA engagement options

Model

QA risk audit

Cost

$5k-$10k

Ideal for

Identifying gaps before release

Model

Dedicated QA team

Cost

$15k-$35k/month

Ideal for

Ongoing development and QA support for AI, banking, finance, and insurance systems

Model

Staff augmentation

Cost

$35-$70/hr

Ideal for

Scaling internal QA teams

Common questions answered

The costs for Azati's QA services are $15k-$35k per month for dedicated teams, with $5k-$10k per month for initial audits. Staff augmentation will cost $35-$70 per hour.

Azati serves QA teams in the Netherlands, Poland, Spain, and Switzerland.

Azati offers a variety of pricing models to provide clients with the best cost-quality ratio. We'll help you choose the one that best fits your challenge specifics. The most widely used ones are Time and Materials and Fixed Price, yet some projects take a dedicated pricing approach.

Time & Materials (T&M), Time & Materials NTE

Ideal for agile engineering. Features monthly billing, based on the number of hours your development team works. Flexible model that suits projects with changing scopes.

You may also add a not-to-exceed (NTE) cap to control the project's cost ceiling from the get-go and approve the key payment milestones.

Fixed Price

Best for smaller projects where a client provides clear requirements, alongside a reasonable deadline. We determine a scope to prevent overruns, settle on an inflexible price, and seal the deal.

Dedicated Team

Great option for large-scale, long-term arrangements where clients need a consistent team that works exclusively on their project. The monthly fee will cover the dedicated experts' salaries based on their seniority levels and administrative costs. The client can freely manage the team according to changing requirements.

Azati suggests combining contract testing for financial systems, automated QA for APIs, and exploratory testing for edge cases, no matter your business case. For continuous validation, it's critical to integrate CI/CD.

We at Azati combine automation with manual testing to minimize bugs creeping in upon your product release. Even though we rely on test automation for stable, high-risk flows and regression tests, manual testing is an absolute must for edge cases, user behavior, and exploratory testing at each project.

Azati QA experts ensure initial improvements in 2-4 weeks, with full impact in 4-8 weeks.

Azatian Quality Assurance utilizes a large stack of tools to cover complex, high-stakes projects. Below is its convenient breakdown per use cases:

Automation & UI testing

  • Cypress
  • Playwright
  • Selenium

These help Azati ensure fast, stable regression testing with reliable cross-browser coverage.

API & integration testing

  • Postman
  • REST Assured
  • Pact

The tools allow Azati to validate business logic, microservices, and system integrations before release.

Performance & load testing

  • Apache JMeter
  • k6

Azati's go-to pair to ensure system stability under peak load and high-traffic conditions.

CI/CD & infrastructure

  • Jenkins
  • GitHub Actions
  • Docker

Enable automated testing pipelines with fast feedback on Azati's every release.

Mobile testing

  • Appium

Helps Azati in establishing consistent behavior across iOS and Android devices.

Manual QA & data validation

  • SQL
  • JSON
  • Browser DevTools
  • Cross-device testing

Azati's optimized stack for catching edge cases, validating workflows, and ensuring data integrity.

AI-assisted QA

  • ChatGPT
  • Copilot
  • Claude

Azati QA go-to trio enabling faster test design, better coverage, and improved documentation. Speed up releases, reduce production bugs, and increase confidence in complex systems.

QA engineers at Azati automate testing when workflows are stable, involve high risks, and are repeated frequently. Test automation is ideal for integration testing services and performance testing of banking software.

Absolutely. Make sure Azati QA will click with your developers and internal QA.

Yes, Azati supports automation and manual testing alike. Both are required for QA for complex systems.

Azati specializes in testing core banking, finance, billing systems, insurance, AI apps and automation workflows, and API platforms.

Based on Azati's experience, testing financial workflows carries a higher risk due to more integrations, stricter requirements, and more edge cases. Financial workflow QA services require deep expertise in the domain itself, as well as in compliance testing services.

Unlock the right talent for your project

Tap into Azati's QA expertise to reduce production bugs, improve release confidence, and speed up delivery in high-risk systems.
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    • 3. Start with measurable QA impact
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