Governance, observability and guardrails so your AI operates within business and regulatory rules, with a 100% on-premises option.
The question that stalls AI adoption in companies isn't whether it works, it's whether it's safe: who answers for what the agent says? Where does the data go? How do we prevent manipulation? AI Trust exists to answer with engineering, not promises: guardrails that limit agent behavior, automatic anonymization of personal data, anti prompt-hacking filters and audit trails.
Governance defines the framework: usage policies, roles and responsibilities, use-case approval criteria and AI risk management, aligned with the LGPD and the emerging AI-regulation frameworks.
A model in production without monitoring is a silent risk. The AI Observability track tracks answer quality, cost per use case, behavior drift and degradation over time, with alerts and dashboards. And for data that can't leave home, the on-premises option runs everything in your datacenter, with full sovereignty.
They are technical controls that limit agent behavior: answer scope, content filters, protection against prompt hacking and blocking of sensitive-data leakage.
With anonymization of personal data before sending it to models, legal bases mapped for each processing activity, audit trails and, when needed, 100% on-premises operation.
It's monitoring models in production as you would any critical system: answer quality, cost, latency, behavior drift and degradation, with alerts and indicators.
When there are data-sovereignty requirements, sector regulation or information that can't travel to external clouds. Intelliway deploys the full stack in your datacenter, including the EVA Platform.
Talk to the AI Trust team.
