Prepared data. Repeatable runs.
We provision test data, verify configuration and permissions, isolate conflicting scenarios, and restore agreed baselines before interpreting failures.
Your code moves faster.Your QA should keep up.
Experienced QA engineers. Purpose-built agents. One accountable quality operation, connected to your product.
AUTOMATION + EXPLORATION + HUMAN JUDGMENT
A CONNECTED QA OPERATION WORKFLOW ILLUSTRATION
YOUR TOOLS. YOUR CODE.HUMAN ACCOUNTABILITY.
01 / THE OPERATING MODEL Agent execution. Expert direction.
EXAMPLES FROM OUR QA PRACTICE
Playwright TestRail Confluence Your codebase Jira
Integrations are scoped to your stack.
A DIFFERENT WAY TO RUN QAMore execution.
01 / READY TO RUN 02 / KNOWLEDGE THAT CARRIES FORWARD
More execution.
Still accountable.
Faster development creates more behavior to verify. Adding a testing tool still leaves someone to connect the context, direct the work, and judge the result.
Mantis brings the agents and the QA expertise. We build the workflows, run the checks, review the evidence, and keep the remaining risks visible.
Product knowledge, maintained.
Reviewed business rules, testing conventions, setup procedures, and known constraints give future work a consistent starting point. QA engineers check and update that knowledge as requirements and behavior change.
INSIDE THE OPERATIONSee the work.
See the work.
Follow the evidence.
Explore the workflows behind the service.
Choose a task, then follow each step.
MANTIS / WORKFLOW EXPLORERINTERACTIVE ILLUSTRATION · NOT A LIVE RUN
Agreed journey → reviewed automation
From a product journey to trusted coverage.
Start with requirements, existing test cases, or a user journey agreed with your team. Agents build coverage; a QA engineer reviews what it proves.
CODE + REQUIREMENTS + CASES OR AGREED JOURNEYS
Agree what the product should do.
Read the implementation, available requirements, and reviewed product knowledge. Agree the scenarios and flag outdated cases or conflicting sources before generating tests.
Review item
Spec and test case disagree on who can invite a member.
◈
Human review
A QA lead resolves the intended behavior with your product owner.
EXAMPLE CONTENT · ACTUAL SCOPE AGREED PER ENGAGEMENTAGENT EXECUTION → HUMAN JUDGMENT
WHERE EXPERTISE MATTERSThe agent can run it.
The agent can run it.
A QA expert asks
if it’s enough.
Automation scales execution. Judgment decides what deserves confidence.
Our QA engineers challenge the coverage, investigate ambiguity, and take the exploration further. Your team gets a clear view of the evidence and its limits.
01 / INTENT
Are we testing the right behavior?
Resolve conflicts between specs, cases, and implementation.
02 / DEPTH
What could we still be missing?
Challenge assertions, permissions, data states, and negative paths.
03 / RELIABILITY
Can the team trust this result?
Investigate failures, review repairs, and make skips visible.
04 / RELEASE RISK
Where does the evidence stop?
Report what was tested, what was blocked, and what remains uncertain.
FROM WORKFLOWS WE’VE BUILTFrom our own
From our own
QA practice.
In an existing client engagement, we connected a custom TestRail MCP integration, product specs, code, and visual browser tools to an agent workflow that generates and runs Playwright coverage.
We also built PR-based exploratory workflows that investigate the interface and report candidate bugs to Jira. Our QA engineers review the work and extend the testing where needed.
IMPLEMENTATION EXPERIENCE · CLIENT KEPT ANONYMOUSINPUTCases + specs + code
↓EXECUTIONBrowser validation
& Playwright coverage
↓& Playwright coverage
ACCEPTANCEExpert QA review
Run the tests.
Challenge what they prove.
WHAT YOUR TEAM GETSA working QA operation.
A working QA operation.
With work you can inspect.
The outputs belong in your workflow.
The accountability stays with Mantis.
01
Maintainable automation
Reviewed tests in your repository, with agreed configuration, setup assets, and run instructions.
02
Reviewed findings
Reproducible defects with expected behavior, actual behavior, and evidence your engineers can act on.
03
Release evidence
A clear record of what ran, what failed, what was reviewed, and which risks remain.
04
Coverage that evolves
Maintained product knowledge, reviewed suite updates, and a visible backlog of uncovered risk.
START WITH SOMETHING REALONE PRODUCT AREA. AN AGREED STANDARD.
Your product.
One focused pilot.
Evidence to decide.
Bring one important workflow. We’ll agree the scope, connect the context, and show you how an agentic QA operation works on your product.
Scope a QA pilotScope, timing, and pricing agreed after a fit call.
- 01
Choose the risk.
Pick a product area, baseline, and scenarios worth protecting.
- 02
Run the operation.
Connect approved tools. Execute, investigate, and review.
- 03
Judge the evidence.
Compare accepted coverage, human effort, repeatability, and confirmed defects.
BEFORE WE TALKA few good
A few good
questions.
Are you replacing our QA team?
We can own an agreed QA scope or work alongside your team. Agents handle repeatable execution and investigation; experienced QA engineers direct the work, review it, and explore risks the agents miss. The right staffing model depends on your product and risk.
Is this another testing platform to buy?
This is a managed QA service. We connect approved tools and operate the workflow with your team. Your engineers receive tests and findings in the delivery process they already use, rather than another platform to manage.
Do we need TestRail or documented test cases?
No particular test-management tool is required. We can start with requirements, existing cases, or agreed user journeys. If cases are missing, we first establish the intended behavior and scenarios with your team. Discovery effort and integrations are agreed when scoping the engagement.
What access and data arrangements are needed?
We agree the repository, documentation, test environment, and tool access needed for the scope. Approved AI providers, permitted data, credential handling, and access limits are agreed with your team before connecting the workflow.
Can you work with our existing automation?
We assess your suite and framework first. Playwright is used in the workflows shown here. For another framework, we agree whether to extend it or propose a different approach; migration is not a prerequisite.
Which applications and testing types fit?
The workflows shown here focus on browser-based web applications: functional journeys, regression coverage, and exploratory testing. We confirm application and environment fit during scoping. Native mobile, performance, security, accessibility, and AI model evaluation need a separate assessment.
What does a passing run actually mean?
It means the executed checks passed in the tested environment. We review whether those checks reflect intended behavior, and report the scenarios and risks they do not cover. Passing tests are evidence within a scope, not proof that a product is defect-free.
What do we receive, and what can we run ourselves?
Tests are delivered into your repository, with agreed configuration, setup assets, run instructions, maintained product knowledge, and evidence. We identify what your team can run independently and any Mantis, AI-provider, or tool dependencies. Handover scope is agreed up front; your team keeps the release decision.
How do we start?
We scope a pilot around one important product area. Together we agree the access, environments, baseline, deliverables, and success measures. We propose timing and pricing after understanding that scope.
SHIP WITH A CLEARER PICTURE.Let’s put your next
Scope a QA pilot Explore ongoing QA support