How it works

From "here's the architecture diagram, go test it" to a structured, prioritized testing plan — in about two minutes, without uploading anything.

1 · Match your architecture

Pick your industry, then answer a handful of adaptive questions about the integration — direction of data flow, the kinds of systems on each end, event-driven vs batch vs synchronous, fan-out, staging, deferred posting. Each answer sharpens a live confidence score against our library of generic reference architectures. You accept a match whenever it looks close enough; nothing forces you through every question.

2 · Make it yours, then lock it

The matched pattern renders as a professional architecture diagram: labeled zones, typed components, directional animated flows. You layer your real component names on top of the preserved generic types (a "Function Adapter" you name "retailPO" becomes "retailPO Function Adapter" in every generated artifact) and drag things to match your mental model. Locking the diagram is the confirmation act — it snapshots everything downstream generation uses.

3 · Read it in plain English

The first deliverable — free, no account — is a plain-English summary of what the whole architecture does end to end: how data is captured, staged, transformed, routed, delivered, and finally applied by the target system, including the classic risks like eventual-consistency gaps between delivery and posting.

4 · Test between checkpoints

The flow is broken into derived checkpoints — natural seams like "capture & transform", "event routing & execution", "target delivery", and "target posting & application". Each checkpoint states what correct observably looks like, what typically goes wrong there, and the concrete techniques to validate it: dead-letter-queue inspection, correlation-ID tracing, read-back queries, batch-job log checks, payload replay.

CP1 — Event Routing & Execution

RPN 16

Acme Corp SaaS Platform: Source events are emitted for every business action, with stable IDs and complete payloads retrievable via the vendor API.

CP2 — Target Delivery

RPN 15

Order Management System: The staged record/journal is visible in the target UI with correct values, pending its internal application step.

CP3 — Target Posting & Application

RPN 25

Fulfillment / Shipment Trigger: The internal job picks up staged records on schedule and applies the business effect (e.g. on-hand inventory updates).

5 · Prioritize, plan, and hand off

Every path through the architecture is enumerated and ranked by the risk it carries, with the primary business flow always first. An E2E execution plan gives entry and exit criteria per stage. Sample test-data payloads are generated for every stage of the flow. And a condensed, ticket-ready description pastes straight into Jira/Xray to feed your existing AI test-case generation tooling.

6 · Track and report

A progress matrix tracks pass/fail/pending per checkpoint per event type. One click turns it into a stakeholder status report — portfolio summary with RAG status, KPI tiles, risks, and per-area checkpoint detail — print-ready for your weekly update.

Risk-weighted progress

Bar height = checkpoint RPN · color = pass / fail / pending

CP1CP1 — Event Routing & Execution: RPN 16 (S4 O4 D1)CP2CP2 — Target Delivery: RPN 15 (S5 O3 D1)CP3CP3 — Target Posting & Application: RPN 25 (S5 O5 D1)850 · Purchase Order850 · Purchase Order — CP1 Event Routing & Execution: pass850 · Purchase Order — CP2 Target Delivery: pass850 · Purchase Order — CP3 Target Posting & Application: pending856 · Ship Notice856 · Ship Notice — CP1 Event Routing & Execution: pass856 · Ship Notice — CP2 Target Delivery: pending856 · Ship Notice — CP3 Target Posting & Application: fail810 · Invoice810 · Invoice — CP1 Event Routing & Execution: pending810 · Invoice — CP2 Target Delivery: fail810 · Invoice — CP3 Target Posting & Application: pass

Real checkpoints and risk scores from the diagram above; the pass/fail pattern here is illustrative — yours fills in as you actually run tests.

The methodology in one sentence

Every deliverable is a projection of one annotated architecture graph: components typed against an ontology rooted in Enterprise Integration Patterns, each type carrying test knowledge — what correct looks like, typical failure modes, validation techniques, and a risk weight. Deterministic analysis computes the checkpoints, paths, and priorities; language generation only writes the prose, in your vocabulary.