Meet BQA and Teammaite at AutomationSTAR: from testing expertise to AI-powered quality

Visit BQA and Teammaite at AutomationSTAR and discover how testing expertise, AI and automation come together – with AI as the accelerator and the professional in the driver-seat.

AI-powered development is delivering code faster, sometimes producing an entire feature in a single iteration. Testers therefore need to analyse specifications, risks, test strategy, coverage and automation just as quickly – without sacrificing quality.

That raises a practical question:

How do you stay relevant, valuable and effective as quality becomes more AI-driven?

At AutomationSTAR, BQA and Teammaite will explore that question with testers, automation engineers, QA leads and business owners. Our message is simple: AI should not replace testing expertise; it should make that expertise more powerful.

Quality Starts Before Testing Starts

Requirements often look clear until testing reveals the gaps: exception flows are undefined, acceptance criteria are not measurable, risks are unclear or the business expectation does not match what was built.

BQA therefore believes quality must move upstream. Requirements, user stories and acceptance criteria should be analysed before development starts, with risks and test ideas linked to business intent from the beginning.

With AI support, Teammaite can analyse requirements for ambiguity, missing information, inconsistencies and testability, helping teams build a stronger foundation for test design and automation.

The challenge is not simply generating tests faster, but deciding what should be tested:

What does the specification really mean?
Are the requirements complete, unambiguous and testable?
Where are the biggest product and business risks?
Which test techniques and level of coverage are appropriate?
How do we translate those choices into existing processes and tools in a traceable way?

From Dpecification to the Right Test Coverage

At our stand, we will demonstrate one recognisable end-to-end quality flow:

Specifications -> requirements -> quality improvement -> risk analysis -> test strategy -> test design -> execution and management

Teammaite can process documents, models, tables or existing tickets, while a BQA consultant determines the appropriate context and extraction approach.

Teammaite then identifies ambiguity, inconsistencies, missing information and testability issues. AI can propose product risks, impact and priorities, but consultants and stakeholders validate the business context and risk weighting.

Based on clearer requirements and validated risks, teams can define relevant test levels, test types, techniques and desired coverage.

The goal is not automatically more tests, but targeted and explainable coverage of the risks that matter.

From Tester to AI Test Orchestrator

AI accelerates the process, but it does not remove the need for testing expertise. Experienced testers understand context, recognise risk, judge whether test cases are meaningful and decide what should be automated or explored by people.

BQA calls this role the AI test orchestrator: a quality professional who uses AI deliberately, critically and effectively across the software development lifecycle. For test managers and QA leads, governance, prioritisation, traceability and release confidence remain essential.

The key question is no longer only:

“Can AI create tests?”

It is:

“Can we explain why these tests cover the right risks?”

That is the central question behind our stand at AutomationSTAR.

AI in Control: People Make the Decisions

Responsible AI must be visible in the way quality decisions are made: AI makes proposals; people make decisions.

Important steps can include review and approval. Sources, assumptions, modifications and decisions remain traceable, uncertainty is explicit, and the degree of autonomy can be adjusted to the organisation and the risk involved.

Teammaite delivers the intelligent, integrated workflow. BQA provides the human link – from selecting the approach and facilitating stakeholder discussions to risk analysis, test strategy, governance and implementation.

Connect AI to the Tools you Already Use

AI-supported quality should not become an isolated experiment. Approved results need to fit the organisation’s existing way of working.

The approach can connect with tools such as Robot Framework, Testersuite, Jira and Azure DevOps while maintaining traceability from specification through requirements and tests to findings.

Together, BQA and Teammaite support the full quality flow: requirements analysis, test strategy, test cases, automation and release insight.

Teammaite brings the AI capability; BQA brings experienced consultants who understand testing, test management, automation, governance and software delivery in complex organisations.

AI tooling alone does not change an organisation. People, process and implementation determine whether AI becomes a useful colleague or just another experiment.

Bring Us Your Specification

At AutomationSTAR, we want to go beyond a generic AI product presentation.

Bring a specification or sample requirement and take the spec-to-strategy challenge.

In a few minutes, Teammaite can highlight potential improvements, risks and suggested test coverage. A BQA consultant will discuss which proposals make sense, which assumptions need challenging, where human judgement is required and what integration into your quality process could look like.

You leave with a compact AI-in-control quick scan and a clearer view of what AI-supported quality could mean for your organisation.

Come and Challenge Us

We believe in practical quality improvement, not AI hype for its own sake.

Come to the BQA and Teammaite stand with a testing challenge, requirements problem, automation bottleneck, management concern or simply one existing specification.

Ask us what AI can do, where human expertise remains essential and how your team can move from specification to improved requirements, validated risks, an appropriate test strategy and integrated test facts.

And come prepared for one question from us:

Can you explain why your current tests cover the right risks?