Software QA & AI Validation
Software testing and AI validation to move your business forward
Launch with confidence. Grow with quality.
Your applications need to work correctly. Your AI solutions also need to provide relevant information, respect access permissions, and operate within the boundaries your business defines.
At ITS Solutions, we help businesses evaluate their applications and AI solutions before release. Our testing services combine software quality assurance, test automation, and AI validation to identify defects, reduce risks, and support release decisions with evidence.
Scope
From business platforms to virtual assistants and AI agents, we design tests around your processes, your users, and the consequences of an incorrect response or action.
01
Business Value
Make quality an advantage for your business
A production issue can interrupt operations, increase support costs, and affect customer confidence. With AI, problems can also take the form of a convincing but incorrect answer, a request that exposes restricted information, or an agent that takes an unauthorized action.
Our services help you
- Reduce release risks: Identify defects in your most important user journeys and business processes.
- Support faster delivery: Automate repetitive tests and detect regressions during development.
- Improve the user experience: Evaluate functionality, performance, and consistency.
- Measure AI quality: Assess responses and actions against agreed criteria.
- Prioritize improvements: Focus on issues with the greatest business impact.
- Make informed release decisions: Understand test results, limitations, and unresolved risks before deployment.
02
Our Services
Testing expertise for your software and AI solutions
01
Functional Software Testing
Check that your applications support the way your business works
We verify that features meet requirements and that business processes work correctly from start to finish.
Our testing covers web and mobile applications, business platforms, forms, business rules, user roles, and integrations. We test typical scenarios, invalid inputs, and exceptions that could affect your operations.
The goal: Identify defects before they affect your customers or employees.
02
Test Automation & Regression Testing
Keep existing functionality in focus as your software changes
We develop automated tests to detect whether changes introduce problems into existing features.
We focus on critical processes and repeatable scenarios to build a maintainable test suite that can run during development and before each release.
The goal: Support frequent releases with better visibility into software quality.
03
API & Integration Testing
Validate the connections your business depends on
We evaluate how information moves between applications, external services, and internal systems.
Testing covers data contracts, authentication, permissions, error responses, and behavior during service interruptions. We check whether workflows preserve data integrity across connected systems.
The goal: Support reliable business processes across your integrations.
04
Performance & Capacity Testing
Understand how your solution responds as demand increases
We assess response times, stability, and resource consumption under representative workloads. We define test scenarios around expected usage, concurrent activity, and critical workflows to help identify bottlenecks and capacity limitations.
For AI solutions, the evaluation can also consider response latency and resource consumption per interaction.
The goal: Give your team evidence to plan capacity and address performance issues before release.
05
Generative AI & Business Assistant Validation
Evaluate the quality of AI responses
We assess whether an AI system’s responses are accurate, relevant, and consistent with its intended role.
We build evaluation datasets with representative questions, reference answers, and challenging cases. We test instruction following, unsupported claims, and behavior when information is missing.
The goal: Identify when the AI responds appropriately and when it should request context, acknowledge a limitation, or refer the user to a person.
06
RAG & Enterprise Knowledge Evaluation
Check that AI answers are supported by the right information
Retrieval-augmented generation, or RAG, allows an AI system to reference documents and other information sources when generating answers.
We evaluate both information retrieval and the final response: whether the system finds the right documents, uses current information, cites relevant sources, and respects access permissions.
The goal: Assess whether your business information is being turned into useful, supported answers.
07
AI Agent & Workflow Testing
Test the actions behind the answers
AI agents can retrieve information, use tools, and take action. Testing needs to consider the full workflow and its effects.
We test tool selection, permissions, human approval checkpoints, and error recovery. Scenarios can include ambiguous instructions, unavailable services, and attempts to take actions outside the authorized scope.
The goal: Evaluate whether agents operate within the boundaries established by your business.
08
AI Risk & Control Testing
Find weaknesses in how your AI handles challenging requests
We design scenarios to assess how the system responds to malicious instructions, attempts to extract restricted information, and requests that conflict with its rules.
Depending on the use case, we also evaluate inappropriate responses and differences in behavior across relevant groups or situations.
The goal: Identify weaknesses and provide evidence to improve technical controls and human monitoring.
Functional Software Testing
01
Functional Software Testing
Check that your applications support the way your business works
We verify that features meet requirements and that business processes work correctly from start to finish.
Our testing covers web and mobile applications, business platforms, forms, business rules, user roles, and integrations. We test typical scenarios, invalid inputs, and exceptions that could affect your operations.
The goal: Identify defects before they affect your customers or employees.
Test Automation & Regression Testing
02
Test Automation & Regression Testing
Keep existing functionality in focus as your software changes
We develop automated tests to detect whether changes introduce problems into existing features.
We focus on critical processes and repeatable scenarios to build a maintainable test suite that can run during development and before each release.
The goal: Support frequent releases with better visibility into software quality.
API & Integration Testing
03
API & Integration Testing
Validate the connections your business depends on
We evaluate how information moves between applications, external services, and internal systems.
Testing covers data contracts, authentication, permissions, error responses, and behavior during service interruptions. We check whether workflows preserve data integrity across connected systems.
The goal: Support reliable business processes across your integrations.
Performance & Capacity Testing
04
Performance & Capacity Testing
Understand how your solution responds as demand increases
We assess response times, stability, and resource consumption under representative workloads.
We define test scenarios around expected usage, concurrent activity, and critical workflows to help identify bottlenecks and capacity limitations. For AI solutions, the evaluation can also consider response latency and resource consumption per interaction.
The goal: Give your team evidence to plan capacity and address performance issues before release.
Generative AI & Business Assistant Validation
05
Generative AI & Business Assistant Validation
Evaluate the quality of AI responses
We assess whether an AI system’s responses are accurate, relevant, and consistent with its intended role.
We build evaluation datasets with representative questions, reference answers, and challenging cases. We test instruction following, unsupported claims, and behavior when information is missing.
The goal: Identify when the AI responds appropriately and when it should request context, acknowledge a limitation, or refer the user to a person.
RAG & Enterprise Knowledge Evaluation
06
RAG & Enterprise Knowledge Evaluation
Check that AI answers are supported by the right information
Retrieval-augmented generation, or RAG, allows an AI system to reference documents and other information sources when generating answers.
We evaluate both information retrieval and the final response: whether the system finds the right documents, uses current information, cites relevant sources, and respects access permissions.
The goal: Assess whether your business information is being turned into useful, supported answers.
AI Agent & Workflow Testing
07
AI Agent & Workflow Testing
Test the actions behind the answers
AI agents can retrieve information, use tools, and take action. Testing needs to consider the full workflow and its effects.
We test tool selection, permissions, human approval checkpoints, and error recovery. Scenarios can include ambiguous instructions, unavailable services, and attempts to take actions outside the authorized scope.
The goal: Evaluate whether agents operate within the boundaries established by your business.
AI Risk & Control Testing
08
AI Risk & Control Testing
Find weaknesses in how your AI handles challenging requests
We design scenarios to assess how the system responds to malicious instructions, attempts to extract restricted information, and requests that conflict with its rules.
Depending on the use case, we also evaluate inappropriate responses and differences in behavior across relevant groups or situations.
The goal: Identify weaknesses and provide evidence to improve technical controls and human monitoring.
03
AI Evaluation Criteria
What do we evaluate in an AI solution?
AI quality needs clear criteria. We work with you to define what an acceptable result looks like for each use case.
We combine automated metrics with human review based on the complexity and potential impact of the task. When AI is used to support an evaluation, we check its assessments against reference criteria and specialist review.
01
Exactitud
Do responses and results meet the agreed reference criteria?
02
Grounding
Are claims supported by the available information sources?
03
Relevance
Does the response address the user’s actual need?
04
Instruction Following
Does the system follow its rules, required formats, and restrictions?
05
Permissions & Privacy
Does the system limit information access and actions to the authorized scope?
06
Robustness
How does the system respond to ambiguity, incomplete information, and attempts to manipulate its behavior?
07
Agent Execution
Does the agent select appropriate tools and complete its tasks correctly?
08
Performance & Resource Usage
How long does each interaction take, and what resources does it consume?
04
Our Process
A testing approach connected to your business goals
01
Understand your solution and its risks
We review your business goals, users, architecture, and critical processes. Together, we identify the failures that could have the greatest consequences.
02
Define the testing strategy and acceptance criteria
We establish the scope, scenarios, test data, and thresholds that will be used to evaluate each release.
03
Design and run the tests
We combine manual testing, automated testing, and AI-specific evaluations. We document findings so your team can reproduce and address them.
04
Prioritize and verify improvements
We classify defects by impact and work with your team to verify fixes.
05
Assess readiness for production
We provide results, unresolved risks, and recommendations to support your release decision. Relevant evaluations are repeated when the software, AI model, prompts, or information sources change.
05
Deliverables
Clear findings that help you decide what comes next
Depending on the agreed scope, deliverables may include:
- A testing strategy and acceptance criteria.
- Test cases and AI evaluation datasets.
- Automated tests and maintenance documentation.
- Defect reports with supporting evidence and priorities.
- Quality, performance, and regression test results.
- A record of limitations and unresolved risks.
- Recommendations for release and future improvements.
Each finding should help you decide what to fix, what to prioritize, and which risks need attention.
06
Engagement Options
Testing support for every stage of development
01
Project or Release Assessment
For businesses that need to evaluate an application, a new feature, or an AI solution before putting it into production.
02
Ongoing QA for Development Teams
For organizations that need recurring testing, automation, and quality monitoring throughout their release cycles.
03
Specialized AI Validation
For businesses developing assistants, RAG applications, or AI agents that need to evaluate responses, actions, and controls.
04
Scalable Testing Services
For organizations managing multiple products or initiatives that need coordinated QA capacity, consistent evaluation criteria, and clear reporting.
07
Why ITS Solutions
Quality testing that supports your business decisions
Business-Focused Priorities
We focus on the scenarios that matter most to your operations, customers, and business goals.
Software and AI Evaluated Together
We connect interface, API, and workflow testing with the evaluation of AI responses and actions.
Collaboration With Your Team
We integrate quality evaluation into the development process so findings can be addressed and fixes verified.
Evidence for Every Release
We present understandable results, limitations, and priorities to support informed release decisions.
08
FAQ
Frequently Asked Questions
What is a software testing factory?
A software testing factory is an organized QA service that brings together people, processes, and tools to evaluate applications continuously. It coordinates testing, automates repeatable scenarios, and maintains consistent quality criteria across projects.
What is the difference between software QA and AI validation?
El QA de software comprueba funcionalidades, reglas de negocio e integraciones. La validación de IA también evalúa respuestas variables: su exactitud, fundamentación, relevancia y comportamiento frente a diferentes instrucciones. Una solución empresarial con IA necesita ambas evaluaciones.
Can AI testing be automated?
Yes. You can automate test execution, response collection, and parts of the evaluation. Ambiguous scenarios and higher-impact cases may require human review. The approach depends on the use case and acceptance criteria.
How do you evaluate AI hallucinations?
We compare responses with reference sources and evaluation criteria to identify incorrect or unsupported claims. We also test how the system responds when it lacks sufficient information.
Testing helps measure and reduce this risk, but it does not guarantee that hallucinations will be eliminated.
Can you evaluate a solution developed by another provider?
Yes. We can evaluate existing solutions once we have the necessary access, environments, documentation, and permissions. The scope depends on the information available and the project’s goals.
When should testing begin?
Start testing early in the project. Defining quality criteria during design helps identify problems before they become more costly to correct.
Testing should continue as features, models, instructions, and data sources change.
How much do software QA and AI validation services cost?
The cost depends on the solution size, its integrations and environments, the level of automation, and the depth of the evaluation.
After reviewing your project, we define the scope, deliverables, and a proposed engagement.