Alternatives
Products that do what PrivacyCore™ — AI Control Plane does
Intent routing for regulated AI agents
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Much of my work right now involves complex, long-running, multi-agentic teams of agents. I kept running into the same problem: “How do I keep these guys in line?” Rules weren’t cutting it, and we needed a scalable, agentic-native STANDARD I could count on. There wasn’t one. So I built one. Here are two open-source protocols that extend A2A, granting AI agents behavioral contracts and runtime integrity monitoring: - Agent Alignment Protocol (AAP): What an agent can do / has done. - Agent Integrity Protocol (AIP): What an agent is thinking about doing / is allowed to do. The problem:…
Feb 2026 · mnemom.ai
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Jul 2026 · github.com
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2023 · parsepolicy.com
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I’m an independent researcher proposing State Discrepancy, a public-domain metric to quantify how much an AI system changes a user’s intent (“the Ghost”). The goal: replace vague legal and philosophical notions of “manipulation” with a concrete engineering variable. Without clear boundaries, AI faces regulatory fog, social distrust, and the risk of being rejected entirely. Algorithm 1 (on pp.16–17 of the linked white paper) formally defines the metric: 1. D = CalculateDistance(VisualState, LogicalState) 2. IF D < α : optimization (Reduce Update Rate) 3. ELSE IF α ≤ D < β : warning (Apply…
Jan 2026
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Monitor, govern, and trust every AI agent decision
May 2026 · skeptick.ai
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