AI Control Plane
Centralize runtime governance for LLM apps, agents, and developer tools with policy enforcement, data leakage prevention, audit logging, and resilient routing across enterprise AI environments.
Secure enterprise AI systems with runtime guardrails, policy enforcement, and audit-ready oversight. Trussed AI helps organizations reduce prompt injection risk, prevent data leakage, and govern LLM apps, copilots, and agents without disrupting existing workflows or slowing production adoption.
Enterprise controls, governance, and assurance services for securing LLM applications, agents, and AI workflows.
Centralize runtime governance for LLM apps, agents, and developer tools with policy enforcement, data leakage prevention, audit logging, and resilient routing across enterprise AI environments.
Control agent actions before every tool call, API request, and workflow trigger so autonomous systems operate within approved boundaries and policy-defined permissions.
Generate continuous audit evidence for governed AI interactions with traceability from prompt to output, supporting internal reviews, compliance teams, and external examinations.
Design governance strategy, approval workflows, stakeholder alignment, and deployment plans that move enterprise AI from experimentation into controlled production operations.
Track AI spend by team, workflow, and provider while enforcing budgets and usage thresholds in real time to reduce overruns and improve ROI visibility.
Apply real-time controls that help prevent prompt injection, unauthorized data access, and unsafe outputs across models, workflows, and enterprise integrations.
Enterprise LLM security requires more than static policies or one-time reviews. Trussed AI helps organizations enforce controls during live AI interactions, reducing prompt injection exposure, limiting sensitive data leakage, and creating audit-ready records automatically. With support for apps, copilots, agents, and developer tools, teams gain practical security, governance, and operational visibility without rebuilding existing systems.
See how enterprises strengthen AI security, governance, and compliance with production-ready controls.
Built for enterprises that need secure, governed AI in production.
Policies are enforced during live AI interactions, not left as static documentation.
Platform capabilities align with SOC 2 Type II and ISO 27001 expectations.
Every governed interaction creates traceable evidence for compliance, risk, and internal review teams.
Choose self-managed or managed deployment to fit enterprise cloud and security requirements.
Experienced founders building secure enterprise AI infrastructure.
Co-Founder
Ajay Dankar is Co-Founder of Trussed AI and brings nearly three decades of cloud product and engineering leadership to enterprise AI security. His background includes senior roles at Google Cloud, AWS, Adobe, PayPal, and eBay, where he worked on scaling, reliability, and cost optimization challenges central to production AI systems. At AWS, he led product management for Elastic Load Balancing, helping expand adoption while improving operational efficiency. He also founded Finsphere, later acquired by Visa, where he helped pioneer fraud detection using mobile location data. At Trussed AI, Ajay focuses on helping enterprises deploy generative and agentic AI with stronger governance, resilience, and operational control 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 and safely at scale. Across product roles at Rakuten, Cisco, JustAnswer, and Oracle, he saw firsthand how organizations struggled to move from AI experimentation to dependable production systems. His work leading AI prediction initiatives improved customer experience and platform efficiency while revealing the need for stronger operational controls and deployment tooling. At Trussed AI, Branden applies that experience to building practical governance and security infrastructure for enterprise LLM applications, copilots, and agents. His approach centers on helping teams reduce deployment risk, improve oversight, and operationalize AI systems with confidence in regulated and high-stakes environments.
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 enterprise 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, partnerships, and enterprise collaboration platforms. At Trussed AI, Sunita helps organizations identify high-impact AI use cases while building the governance, operational structure, and partnerships needed to deploy them securely and effectively.
Yes. Generative AI can support cyber security through threat analysis, alert triage, investigation assistance, policy drafting, and security workflow automation. It can also help summarize incidents and accelerate analyst productivity. However, enterprise use requires controls for prompt injection, data leakage, access permissions, audit logging, and output validation so AI improves security operations without introducing unmanaged risk.
Talk with our team about securing enterprise LLM deployments.
Independent controls validation for enterprise trust.
Recognized information security management standard.
Continuous evidence generation for compliance teams.
Share your AI security goals, deployment model, and governance needs. Our team will help you evaluate controls for prompt injection prevention, data protection, and runtime oversight.
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