AI Control Plane
Centralize acceptable use enforcement across AI apps, agents, and developer tools with runtime policy controls, audit logging, dashboards, and flexible managed or self-managed deployment options.
Turn AI usage policies into real-time controls with Trussed AI. Our platform helps enterprises enforce acceptable use standards across apps, agents, and developer tools while improving audit readiness, reducing manual oversight, and giving teams clear visibility into risk, usage, and cost before issues escalate.
Explore the core governance, enforcement, and assurance capabilities that help enterprises control AI usage in production.
Centralize acceptable use enforcement across AI apps, agents, and developer tools with runtime policy controls, audit logging, dashboards, and flexible managed or self-managed deployment options.
Apply policy checks before every tool call, data access event, and workflow trigger so autonomous agents operate within approved boundaries in real time.
Generate continuous evidence for internal reviews and external audits with complete traces, policy evaluation records, timestamps, and data lineage for governed AI interactions.
Track AI spend by team, workflow, and provider while enforcing budgets, alerts, and usage thresholds to keep acceptable use aligned with financial controls.
Design enterprise AI usage policies, approval workflows, and operating models that move organizations from experimentation to governed, production-ready deployment.
Connect governance controls into existing cloud, model, and enterprise environments through SDKs, APIs, and partner integrations with leading platforms.
A GenAI acceptable use policy only works when it is enforced in real time. Trussed AI helps enterprises apply approved rules directly across prompts, models, agents, tools, and workflows, so risky behavior is blocked before execution. With centralized visibility, continuous monitoring, and audit-ready records, teams can scale AI adoption with stronger security, compliance, and operational confidence.
Trussed AI helps enterprises operationalize acceptable use policies with enforceable controls, not static documents.
Policies are evaluated at runtime across models, agents, tools, and workflows before risky actions execute.
Every governed interaction produces traceable evidence for compliance teams, internal audit, and regulatory reviews.
Choose managed or self-managed deployment to fit enterprise security, infrastructure, and operational requirements.
Built with enterprise-grade controls for regulated environments, with alignment to HIPAA, GDPR, FERPA, and NIST AI RMF.
Experienced founders building enterprise AI governance 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 governance. His background includes senior roles at Google Cloud, AWS, Adobe, and PayPal/eBay, where he worked on large-scale infrastructure, reliability, and cost optimization challenges. 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. That blend of infrastructure depth and financial risk innovation informs Trussed AI's approach to governed, production-ready AI. Ajay holds a master's degree in Electrical Engineering and Computer Science from the University of Florida and a Bachelor of Technology from IIT Delhi.
Co-Founder
Branden McIntyre is Co-Founder of Trussed AI and focuses on infrastructure that helps enterprises deploy AI reliably at scale. Across product roles at Rakuten, Cisco, JustAnswer, and Oracle, he saw the same recurring issue: organizations could experiment with AI, but lacked the controls and operational tooling needed for safe production deployment. At Rakuten and JustAnswer, he led AI prediction initiatives that improved customer experience and platform efficiency, giving him firsthand insight into the governance gaps that emerge as models move into real workflows. His work today centers on helping enterprises implement AI systems safely, effectively, and with stronger operational discipline. Branden holds an MBA from UC Berkeley Haas and a Master of Science from New York University.
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 involved product innovation, unified communications, and strategic partnerships with major technology providers. She also holds multiple patents in location-based fraud detection, adding valuable perspective for regulated industries managing risk-sensitive AI use cases. Sunita holds graduate and undergraduate engineering degrees from the University of Maryland and Osmania University.
Start by defining approved AI use cases, restricted activities, data handling rules, human review requirements, and accountability across business, legal, security, and engineering teams. An effective enterprise policy should also specify how rules are enforced in practice. Trussed AI supports this by helping organizations design governance workflows and apply policies automatically at runtime across apps, agents, and developer tools.
Talk with our team about policy design, enforcement, and deployment options.
Share your AI governance goals, current risks, and deployment needs. Our team will help you evaluate the right policy enforcement approach for your enterprise.
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