Research, field notes and product news from the team building the end-to-end AI trust platform.
The line between human language and programming languages is blurring as AI agents interpret plain-language instructions as executable code. This shift democratizes…
Agentic AI acts like an employee—making decisions, writing code, and taking actions—but without identity, oversight, or IAM policies. Traditional security built for…
Auditing an AI agent means more than capturing logs; it means understanding what an agent did, why it did it, and whether…
Agentic AI doesn't just generate text; it takes actions, makes decisions, and touches real systems, raising the stakes for security teams. These…
Questionnaire-based vendor diligence and self-attestations no longer provide real assurance in the AI era. Evidence-based, continuous technical assessment and AI Bills of…
Cranium AI announced new agentic AI capabilities and feature releases for its AI Governance and Security Platform, including AgentSensor, CloudSensor, ComplianceAgent, and…
Unlike a traditional firewall that polices IP packets, an LLM firewall inspects natural language—the prompts users send and the responses models return.…
Porting legacy human-led processes straight into agentic systems leaves them brittle and inefficient. The smarter path is to design backwards from outcomes…
Public LLMs offer baseline safety, but their built-in safeguards leave real gaps in security, privacy, and compliance. A dedicated AI firewall adds…
AI agents now make decisions and take actions with growing autonomy, introducing real but often invisible risk. Without AI-native oversight, enterprises are…
See how Cranium helps your organization accelerate the secure adoption of AI — from your first model to your entire agentic supply chain.
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