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Proof, not promises.

Every case study here comes from a real program with real numbers attached: certification reviews measured in hours, test campaigns measured in days, savings measured in dollars. Whether you build autonomous systems, deploy AMR fleets in your facilities, or assess the safety cases behind them, there's a program below that looks like yours.

Case studies

  • Amazon

    $30M+ in cost avoidance and deployment six months sooner: how Amazon built Proteus's safety case on the ASAP Platform

    Amazon's Proteus is a cross-docking autonomous mobile robot operating at scale across fulfillment facilities. Taking a fully autonomous, AI-driven system of that scale through certification demands rigorous functional safety work and third-party assessment: historically, weeks of review standing between finished engineering and commercial deployment. By building the safety case on Fennec's ASAP Platform, the Proteus program moved certification off the critical path, with safety evidence produced continuously in a standardized form assessors could work from directly.

  • Amazon

    Things that never happen keep happening: How ASAP Testing replaced dozens of manual tests in Amazon's Proteus perception program

    When Amazon Robotics needed to prove that Proteus, its first fully autonomous mobile robot, could safely perceive the people and obstacles around it, the testing plan was rigorous, approved by TÜV Rheinland in advance, and executed almost entirely by hand. Engineers manually positioned standardized test objects around a moving robot, ran dozens of repetitions per test point, and then spent weeks compiling the data into 200-plus-page report documents. Fennec's automated test cells replaced that process end to end: connected directly to the robot and its environment, physically repeatable, and audit-ready reports generated in hours instead of weeks.

  • TÜV Rheinland

    How a T2-qualified toolset makes certification assessment more efficient and focused

    When TÜV Rheinland assessed the safety case for Amazon's Proteus autonomous mobile robot, the core technical review stayed focused. Because the evidence arrived standardized and structurally traceable, assessors could concentrate their scrutiny where it mattered. This is what the review process can look like when the underlying evidence is consistent and connected from the start.

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