SNB Β· Agentic System Integration Testing

One place to run, trace and audit every change.

A change is picked up from the tracker, classified, and routed to the right lane. Impact is computed deterministically from a knowledge graph, a risk-ranked regression suite is selected with a reason for every include and exclude, the tests run against the banking APIs, defects are filed with evidence, and every step is traceable end to end. Pick a surface to begin.

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Live SIT Dashboard

Watch the agents work in real time β€” intake, impact, test design, execution, the human approval gates, defects and the evidence report.

Open the dashboard β†’
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Test Knowledge Graph

The native graph of requirements, test cases, APIs, code modules and defects. Select a change and the impacted subgraph lights up with the ranked regression suite.

Open the graph β†’
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Banking API (Swagger)

The AlAhli Online and Cards Management APIs the tests run against β€” try the endpoints and see the daily-limit and credit-limit controls the agents verify.

Open the API docs β†’
How a work item is routed β€” deterministically, by its tracker marking
Change Request

CR Impact lane. Graph traversal finds exactly which requirements and test cases the change touches, a risk-ranked regression suite is selected, the 11-agent SIT runs the impacted tests, and the run is written back to the graph as an audit node.

New Request

New Request lane. A net-new feature with no existing coverage β€” the agent generates user stories and test scenarios and gives an indicative, parametric effort estimate with its basis. Ready for SIT once built.

Requirement

Standard SIT. An ordinary requirement runs the full 11-agent pipeline unchanged β€” design, review gate, execution, defect gate, evidence β€” exactly as delivered.

Grounding: impact and regression selection are deterministic graph facts, not model guesses β€” the language model only narrates them. Intake and impact are checked against a labelled golden set; the run KPIs are computed deterministically from the graph on a seeded reference dataset. The reuse-versus-new split is derived from each change, not a fixed ratio.