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Customers

Three engagements that shaped the platform.

We name what we can. Where a customer would rather not be named, we describe the work and the outcome and leave the logo out.

01 / Low-code platform vendor

A test automation platform for an entire partner ecosystem.

Before Sahasa.AI existed as a product, this team built and ran the test automation platform for a leading low-code vendor's ecosystem: recording and generating tests for its interfaces, process models and integrations, running them across environments, and reporting to release owners.

  • Test authoring moved from specialist engineers to the wider delivery team
  • Regression became a routine gate on every release instead of a project
  • Taught us how QE platforms get adopted, and kept alive, inside a large ecosystem

What we took from it

The model we still use: a platform plus the people who operate it. A tool on its own doesn't change how a delivery team works; a tool with a team inside the customer does.

02 / Low-code product company

Faster releases and a shorter penetration test.

A fast-moving low-code product uses Sahasa.AI in its day-to-day: requirements to test cases to runnable suites, with bug and security analysis on every change, across engineers who use different AI coding assistants.

  • Faster path from feature idea to tested release, with tests in the team's own frameworks
  • Code-level security findings and the threat model handled before the penetration test starts, so the assessment focuses on what remains
  • One quality standard across Claude Code, Copilot and Cursor users

Why it mattered

Their leadership can read the result: measured, generated only, or not applicable. Nobody has to translate a green build into a decision.

03 / Large Canadian retailer

A platform shaped to their own quality model.

A large retailer with an established quality organisation and its own standards. We learned their expectations and modules first, then tailored the platform to them: AI-led engineering across requirements, generation, security and traceability, reported in the language the organisation already used.

  • Their taxonomy, their gates, their dashboards
  • Enterprise-scale traceability across many teams and repositories
  • Proof that the platform bends to a large customer rather than the other way round

What it proved

Customisation is part of the product, not a services afterthought. White-labelling, custom modules and customer-specific quality gates ship as configuration.

Who it's for

Built for the whole engineering team, not just QA.

Different people get different things out of the same run.

Developers

Unit and integration tests, bug findings with fixes, blast radius, root cause from a stack trace. All inside the PR.

Automation engineers

Runnable suites in their framework, contract tests, live runs, failure triage, suite de-bloat.

Security engineers

SAST, DAST, CVEs, secrets and a corroborated threat model, without a separate portal.

Manual QA and analysts

Testability, scenarios, cases and plans from requirements, and the requirement-to-test truth check. No code.

Engineering leadership

One dashboard per product: quality, security, risk and coverage, measured or marked N/A.

AI product teams

Evals, red teaming and drift for the AI features in the application, via Vigil.

Next step

Bring one repository. We'll show you what comes back.

A demo runs on your code, not ours. Forty-five minutes, one service, real findings. If it's useful, we go into a four-week pilot inside your CI.

Book a demo How a pilot works