Governance Advisory
Strategic advisory for SaaS teams moving from LLM pilots to governed production systems, including operating models, review workflows, stakeholder alignment, and deployment planning.
Build and scale LLM-powered product features with governance designed for real-world SaaS delivery. Trussed AI helps teams enforce policies at runtime, reduce compliance overhead, control costs, and maintain audit-ready visibility across copilots, agents, and embedded AI workflows before risk slows product launches.
Governance solutions for SaaS teams deploying LLM features, agents, and production AI workflows at scale.
Strategic advisory for SaaS teams moving from LLM pilots to governed production systems, including operating models, review workflows, stakeholder alignment, and deployment planning.
A runtime control layer that enforces policies across AI apps, agents, and developer tools while providing audit logs, usage visibility, and regulatory alignment.
Execution-layer governance for agentic systems that authorizes tool calls, data access, and workflow triggers before actions occur across multi-agent environments.
Real-time spend monitoring and enforcement that tracks AI usage by team, workflow, and provider while applying budgets, alerts, and routing controls.
Continuous audit evidence generation with complete traces, policy results, model versions, timestamps, and data lineage for internal and external reviews.
Built-in governance capabilities aligned to frameworks like SOC 2, HIPAA, GDPR, FERPA, NIST AI RMF, and ISO 27001 for regulated SaaS environments.
For SaaS companies embedding LLMs into customer-facing products, governance has to work inside live application flows, not as a separate checklist. Trussed AI helps teams enforce policies in real time, monitor usage and costs, generate audit-ready evidence automatically, and keep agents and copilots within approved boundaries. The result is faster production rollout with stronger security, compliance, and operational confidence.
Helping enterprises operationalize governed AI with measurable control, visibility, and deployment readiness.
Trussed AI helps SaaS teams operationalize governance where LLM risk actually appears: at runtime.
Policies are enforced live across models, agents, tools, and workflows instead of relying on static documentation.
Every governed interaction creates traceable evidence, simplifying reviews for SaaS security, compliance, and enterprise customer diligence.
Drop-in proxy architecture and SDKs help product teams add governance without major application rewrites.
Founded by leaders from Google Cloud, AWS, Adobe, Microsoft, and other enterprise technology environments.
Experienced builders behind production-ready enterprise 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, and PayPal/eBay, where he worked on scaling, reliability, and cost optimization challenges that mirror today's production AI demands. At AWS, he led product management for Elastic Load Balancing and helped drive major adoption growth. He also founded Finsphere, later acquired by Visa, where he pioneered fraud detection using mobile location data. At Trussed AI, Ajay focuses on helping organizations scale generative and agentic AI with stronger control, resilience, and operational discipline 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 at scale. Across product roles at Rakuten, Cisco, JustAnswer, and Oracle, he saw the same recurring issue: organizations could prototype AI quickly but struggled to operationalize it safely in production. His work leading AI prediction initiatives improved customer experience and platform efficiency while exposing the need for stronger governance and deployment tooling. At Trussed AI, Branden applies that experience to closing the gap between experimentation and production by helping teams implement AI systems with better controls, visibility, and operational confidence. His perspective is grounded in practical product delivery, enterprise systems, and real-world AI adoption challenges.
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, partnerships, and enterprise collaboration platforms. At Trussed AI, Sunita helps organizations identify high-impact AI use cases and operationalize them with governance, partner alignment, and production-ready controls that support long-term adoption.
The four pillars commonly used in responsible AI are governance, transparency, fairness, and accountability. For SaaS companies embedding LLMs, that means defining approved use cases, documenting model behavior, monitoring outputs and risks, and assigning ownership for policy enforcement, incident response, and audit evidence. Strong governance connects these pillars to runtime controls rather than leaving them as policy statements alone.
Speak with our team about controls, compliance, and rollout planning.
Validated controls for security and trust.
International standard for information security.
Supports structured AI risk management.
Tell us about your SaaS product, AI use cases, and governance goals. We'll help you evaluate the right controls, deployment model, and path to production readiness.
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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.