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AI for Traceability

Our AI suggests potential links between work items, requirements, test cases, and code changes — speeding up the creation of a complete traceability matrix. What used to take hours now takes minutes.

Saves a team of 100 developers ~2,000 hours per month on manual traceability tasks.

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AI for Requirements

Automatically generate acceptance criteria, test case skeletons, and risk tags from natural language requirements. Reduces the time from requirement to test-ready by up to 50%.

Cuts requirement-to-test conversion time in half, improving quality from day one.

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AI for Impact Analysis

When a code change is proposed, Arcadia's AI analyzes potential impact on existing tests, requirements, and downstream functionality — surfacing risks before they become problems.

Runs automatically with every pull request. Developers see impact before merge.

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Human in the Loop

Our AI doesn't replace your team — it augments them. All AI suggestions are reviewable and require human approval. Train the AI on your domain-specific terminology: medical device safety terms, automotive ISO standards, aerospace DO-178C concepts.

Domain-trainable AI that learns your industry's specific language and standards.

Measurable Impact

AI is reshaping the ALM market today — and Arcadia is at the forefront.

20-30%

Reduction in development cycle times (McKinsey data)

15-20%

Cut in defect rates with AI-assisted traceability

2,000h

Hours saved per month for a 100-developer team

Experience AI-powered ALM firsthand

Watch Arcadia's AI in action — see how it generates test cases, analyzes impact, and builds traceability in real time.

Request a Demo