AI-native Software Quality

Supercharge(d) Software Delivery

Development went 4x with AI. Your analysis, documentation, testing and traceability should too.

Living documentation, requirements analysis, diagrams, test cases, automation and test data – in minutes, not weeks.

Faster releases
+ 0 %
Cost of quality
- 0 %
Leadership insights
x 0

Trusted by teams delivering quality at scale

These brands have joined us in exploring innovative ways to transform SDLC processes.

The problem

Where software delivery breaks

Rework runs at 40 to 50 percent of development effort, and most of it traces back to ambiguity introduced long before anyone writes code. Between 50 and 60 percent of defects originate in the requirements phase, which is the cheapest place to fix them and the least tooled.

Meanwhile the documentation has already drifted from the code. Requirements sit in Confluence, test cases in Zephyr, results in CI, and release decisions get made on feel rather than on evidence.

For who

Quality is a shared success, not a shared burden.

Analysis, documentation and testing are one continuous flow — not three
handovers. SQAI Suite gives every role in that flow the same verified context, and
takes the manual work out of each of them.

Most asked question?

Aren't you a testing tool?

It's the question we get most, so: no. Testing is one of four things we do.
Code copilots own roughly 20% of delivery effort — the application code. SQAI Suite owns
the other 80%: the analysis, the specification, the documentation, the test design, the
traceability and the reporting. If your analysts and product owners aren't using it, you're
using a quarter of it.

SQAI Suite redefined QA by turning documentation into a strategic asset.

EverESSt's requirements lived across Confluence and Jira, and much of it was out of date — so testers built test cases from stale pages, then had to fix the documentation by hand. Today their product owners and business analysts query SQAI themselves, correct documentation at the source, and hand testers a verified starting point. The result: the equivalent of two full-time team members freed up in a team of three, and documentation that improves as a by-product of everyday work.
Kristof Creemers
EverESSt

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