Pricing
Transparent & predictable pricing
Platform fee, SQAI credits and optional add-ons. All four pillars of the platform are included in every paid tier, with no feature gating.
TEAM
€11,800
per year — €983/month, billed annually
- All four pillars, no gating
- 1 workspace
- Unlimited users and connections
- Includes 10,000 SQAI Credits
- Pooled customer success manager
SCALE
€22,650
per year — €1,888/month, billed annually
- All four pillars, no gating
- Up to 5 workspaces
- Unlimited users and connections
- Includes 25,000 SQAI Credits
- Dedicated customer success manager
ENTERPRISE
Custom quote
tailored to your footprint
- All Scale features
- Custom number of workspaces
- Priority support
- Tailored SQAI Credits
- Add-ons bundled into one quote
Custom add-ons — available on top of any paid tier, and they do not change your tier.
Single Sign-On — SAML or OIDC with your own identity provider. Private tenancy — dedicated, isolated infrastructure instead of shared hosting. Regional hosting — data residency in a specific region. Automated test execution — managed runners, parallel execution and environment provisioning.
Every tier is EU-hosted and multi-tenant, with logical isolation per customer. Your code is processed, never used to train models, under zero-retention arrangements with every model provider. SSO, RBAC and a full audit log are in the platform, a DPA is ready to sign before a proof of concept starts, and a penetration test report is available under NDA. Read more about security.
Credits
SQAI credits, explained
Credits are consumed per action, so you pay for what the team actually generates. 10 credits cost €1, from a €1,000 minimum.
Frequently asked question
Still not sure how many licenses you need?
Choosing the right number of SQAI workspaces (licenses) depends on how your projects and integrations are structured.
You only need an extra workspace when you manage unrelated projects, products, or teams. If your integrations (like Jira, Confluence, or Azure DevOps) all belong to the same application and QA process, you can safely keep everything under one license.
If they’re for different products or departments, it’s best to separate them so the AI context stays clean and accurate.
Technically you can — but it’s not ideal.
When AI agents receive mixed data from multiple projects, they may “hallucinate” or give irrelevant answers because the contexts overlap.
Separating workspaces ensures your test generation, analysis, and reporting remain focused and consistent per project or product.
The AI starts blending unrelated requirements, user stories, and test cases. That can cause false test coverage, duplicate stories, or confusing summaries. By isolating each project or product into its own workspace, you keep the AI grounded — and your results far more reliable.
Not always.
If teams work on the same product and share the same QA workflow, one license is fine. But if departments manage separate applications, releases, or environments, separate workspaces will maintain clarity and governance.
No problem — you can always expand your workspace with unlimited integrations as long as they belong to the same project or product line.
If your team starts managing a new, unrelated application, you can spin up a fresh workspace in seconds.
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