AI that reads your code — and never leaves your cloud.
FlowGuard puts a reasoning model at the center of your UAT: it reads your codebase, generates flows, and verifies every screen. Here is what that AI actually does — and the private, contracted boundary that keeps your code and data inside your own cloud.
What the AI actually does
No black box. Four concrete jobs, each grounded in your own code and UI. See the full product.
Reads your codebase
AI scans your pages, routes, forms and APIs, then auto-generates test flows covering critical journeys.
Verifies with vision
At every checkpoint, Claude vision analyzes screenshots to confirm the UI matches expectations.
Heals itself
When page elements move between deployments, AI suggests the selector fix instead of failing the run.
Files the tickets
Failures become Bug and Enhancement tickets in Azure DevOps, Jira or GitHub — automatically.
And how it's contained
Powerful AI is only trustworthy if it is boxed in. Three boundaries do that work.
Private AI, not public
Claude runs on Pintor Project's private Azure AI Foundry. No public Anthropic API, no model training on your data.
Encrypted & isolated
TLS 1.2+ in transit, Azure SQL TDE + AES-256 at rest, database-per-tenant isolation, per-tenant keys in Key Vault.
Regional residency
Independent deployments per region with no cross-region replication. EU, UK and AU available; wrong-region requests are refused.
On compliance we'd rather under-claim: SOC 2 controls are implemented today and a Type I readiness assessment is scheduled — we don't claim certification until the report is in hand. See the full posture.
Go deeper
Bring the security review. We'll answer it.
Sub-processors, DPA, residency, private-AI architecture — it's all documented, and the team will walk your security team through any of it.