AI Control Plane
Centralize runtime governance for AI apps, agents, and tools with policy enforcement, data leakage prevention, code PII protection, and audit-ready visibility across every governed interaction.
Protect sensitive data before it leaves your AI systems. Trussed AI helps enterprises detect, mask, and redact PII in LLM outputs with real-time policy enforcement, audit-ready visibility, and controls that fit production environments. Explore how governance, security, and runtime safeguards reduce leakage risk without slowing down AI adoption.
Runtime controls, governance, and audit capabilities that help secure sensitive data in enterprise AI outputs.
Centralize runtime governance for AI apps, agents, and tools with policy enforcement, data leakage prevention, code PII protection, and audit-ready visibility across every governed interaction.
Control how autonomous agents access data, call tools, and trigger workflows so sensitive information is evaluated against policy before any action or output is allowed.
Maintain complete records of prompts, outputs, policy decisions, timestamps, and data lineage to support internal reviews, compliance teams, and external audit requirements.
Design governance strategies, approval workflows, and operating models that help teams move from AI experimentation to production with enforceable privacy and risk controls.
Track and control AI usage costs while aligning model selection, budgets, and runtime policies with secure, compliant deployment of LLM-powered workflows.
Connect existing models, applications, and developer tools through proxy-based integrations and SDKs to apply PII controls without major application rewrites.
PII detection and redaction in LLM outputs works best when it happens during execution, not after the fact. Trussed AI helps enterprises inspect prompts and responses, enforce masking and redaction policies instantly, and maintain full audit trails for regulated use cases. The result is safer AI deployment, stronger compliance posture, and better control over how sensitive information moves through models, agents, and workflows.
Enterprise AI controls designed to reduce risk, improve compliance, and support production-scale deployment.
Built for enterprises that need enforceable AI privacy, governance, and operational control.
Policies are applied during every AI interaction, not delayed until after risky output is generated.
Every governed interaction produces traceable evidence with logs, lineage, timestamps, and policy evaluation results.
Founded by leaders from Google Cloud, AWS, Adobe, Microsoft, Cisco, and other enterprise platforms.
Deploy self-managed or managed environments with proxy-based integration and minimal disruption to existing systems.
Experienced founders building enterprise-ready AI governance.
Co-Founder
Ajay Dankar is Co-Founder of Trussed AI and brings nearly three decades of cloud product and engineering leadership to enterprise AI governance. His background includes senior roles at Google Cloud, AWS, Adobe, PayPal, and eBay, where he worked on scaling, reliability, and cost optimization for complex production systems. At AWS, he led product management for Elastic Load Balancing, helping drive broad adoption and operational savings. He also founded Finsphere, later acquired by Visa, where he helped pioneer fraud detection using mobile location data. At Trussed AI, Ajay applies that deep infrastructure and security experience to help enterprises govern generative and agentic AI safely, reliably, and at scale across public and hybrid cloud environments.
Co-Founder
Branden McIntyre is Co-Founder of Trussed AI and focuses on infrastructure that helps enterprises deploy AI reliably in production. Across roles at Rakuten, Cisco, JustAnswer, and Oracle, he saw firsthand how organizations struggled to move from promising AI experiments to dependable, governed systems. His work leading AI prediction initiatives improved customer experience and platform efficiency while revealing the need for stronger operational tooling around machine learning and LLM deployment. At Trussed AI, Branden helps shape solutions that close the gap between experimentation and production by embedding governance, visibility, and runtime control directly into AI systems. His practical product background supports enterprises that need secure, scalable AI operations rather than isolated proofs of concept.
Co-Founder
Sunita Reddy is Co-Founder of Trussed AI, where she leads AI, operations, and partner strategy for enterprise adoption of generative and agentic AI. With more than two decades of experience across product, AI, and design, she specializes in turning emerging technologies into scalable business solutions. At JustAnswer, she led initiatives that integrated large language models into core workflows, including copilots, conversational interfaces, and human-in-the-loop systems that improved engagement and accuracy. Earlier roles at Microsoft and Accellion strengthened her expertise in product innovation, collaboration platforms, and strategic partnerships. At Trussed AI, Sunita helps enterprises identify high-impact AI use cases while ensuring governance, security, and operational readiness are built into deployment from the start.
PII masking in AI is the process of identifying personally identifiable information and obscuring it before, during, or after model processing. Common masking methods include replacing names, emails, phone numbers, account numbers, or identifiers with tokens, partial values, or placeholders. In enterprise AI systems, masking is often enforced through runtime policies so sensitive data is protected consistently across prompts, outputs, logs, and downstream workflows.
Talk with our team about runtime controls and redaction strategies.
Validated controls for security and trust.
Recognized information security management standard.
Built for compliance-focused enterprise deployments.
Share your AI use case and our team will help you evaluate practical options for detecting, masking, and redacting sensitive data in production.
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To help us assist you faster, please include the reason for your message so the relevant team can reach out as soon as possible.