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Swedbank, a Temenos T24 customer evaluated Oracle Flexcube

Moog, an UKG AutoTime customer evaluated Workday Time and Attendance

Westpac NZ, an Infosys Finacle customer evaluated nCino Bank OS

Citigroup, a VestmarkONE customer evaluated BlackRock Aladdin Wealth

Cantor Fitzgerald, a Kyriba Treasury customer evaluated GTreasury

Michelin, an e2open customer evaluated Oracle Transportation Management

Wayfair, a Korber HighJump WMS customer just evaluated Manhattan WMS

List of Protect AI Recon Customers

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Logo Customer Industry Empl. Revenue Country Vendor Application Category When SI Insight Insight Source
Atomicwork Software India Professional Services 100 $10M India Protect AI Protect AI Recon Threat Modeling,Vulnerability Management 2024 n/a In 2024, Atomicwork Software India implemented Protect AI Recon to strengthen pre-production checks for its GenAI and large language model deployments. Protect AI Recon, in the Threat Modeling,Vulnerability Management category, was applied to identify and remediate security blindspots before models reached production. The implementation leveraged the automated red-teaming capability originally delivered as SydeLabs’ SydeBox and now branded Protect AI Recon, focusing on adversarial testing of LLM behavior and systematic identification of model-level vulnerabilities. Functional use included orchestrated red-team test runs, vulnerability detection workflows, and issue routing to engineering for remediation. Operational coverage centered on supporting Atomicwork’s IT and ITSM engineering efforts in the United States, with the tool positioned as a pre-deployment security verification layer for GenAI initiatives. Deployment scope emphasized model-level threat analysis and remediation handoffs rather than enterprise-wide infrastructure changes. Governance adjustments routed red-team findings into existing IT/ITSM workflows to ensure remediation occurred prior to production release, aligning security testing with engineering change processes. Reported outcomes included an improved ability to detect and remediate LLM vulnerabilities before deployment, reflecting tighter control over model release readiness.
Leidos Aerospace and Defense 47000 $16.7B United States Protect AI Protect AI Recon Threat Modeling,Vulnerability Management 2025 n/a In 2025, Leidos deployed Protect AI Recon to provide full lifecycle AI security for U.S. government systems. The deployment uses Protect AI Recon in the Threat Modeling,Vulnerability Management category to address model vulnerability scanning, automated red teaming, and runtime protections for mission critical government and national security applications in the United States. The implementation centers on three functional modules, model vulnerability scanning to identify weaknesses in model inputs and architectures, automated red teaming labeled Recon to simulate adversarial manipulation, and runtime protections that monitor model behavior in production. Configuration priorities included scanning cadence, curated attack scenario libraries for Recon, and runtime policy enforcement and alerting. These capabilities map to standard threat modeling and vulnerability management workflows for AI systems. Operational scope covers government customers and mission critical systems across development, testing, and production environments, with Protect AI Recon embedded during model development and runtime monitoring. The engagement emphasizes adherence to federal security standards and procedural integration points across engineering and security operations rather than named commercial integrations. No system integrator or implementation partner was provided in the public disclosure. Governance and rollout are organized as a collaborative program between Leidos and Protect AI that formalizes red team driven workflows, vulnerability triage, and incident escalation across engineering and security operations teams. The stated purpose of the deployment is to help government customers detect adversarial manipulation and meet federal security standards.
Telus Communications 106800 $14.5B Canada Protect AI Protect AI Recon Threat Modeling,Vulnerability Management 2025 n/a In 2025 Telus Digital implemented Protect AI Recon to extend its Threat Modeling,Vulnerability Management posture for AI APIs and production AI tooling. Telus deployed Protect AI Recon as a runtime security and red-teaming capability to strengthen detection across its digital services and AI transformation initiatives in Canada. Protect AI Recon was configured to provide automated red-teaming workflows and runtime threat detection, with functional emphasis on simulated adversary testing, anomaly detection in API payloads, and vulnerability discovery for model inference endpoints. The implementation used Protect AI Recon capabilities to instrument API activity logging, alerting on malicious inputs, and classifying detection events for downstream security triage. The deployment was integrated with Palo Alto Networks Prisma AIRS which incorporates Protect AI capabilities, enabling telemetry sharing between Protect AI Recon and the broader Prisma AIRS monitoring fabric. Operational coverage focused on Telus Digital engineering and security operations, applying Protect AI Recon across AI tooling and customer-facing digital services to capture API call context and threat signals. Governance and rollout followed an early adopter pattern, aligning Protect AI Recon outputs into security operations workflows and AI engineering feedback loops to remediate exposed weaknesses. Reported outcomes from the deployment include improved visibility into API calls and consolidated threat detections across AI tooling, while instrumentation supported ongoing vulnerability management and threat modeling activities.
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