From Cloud-Native to Trust-Native: A Protocol for Verifiable Multi-Agent Systems
This addresses the need for reliable and compliant multi-agent systems in regulated industries such as pharmaceuticals and legal workflows, representing a novel architectural shift rather than an incremental improvement.
The paper tackles the problem of ensuring verifiability in autonomous agents used in high-stakes domains by introducing TrustTrack, a protocol that embeds structural guarantees like verifiable identity and tamper-resistant logs into agent infrastructure, enabling a trust-native autonomy paradigm.
As autonomous agents powered by large language models (LLMs) proliferate in high-stakes domains -- from pharmaceuticals to legal workflows -- the challenge is no longer just intelligence, but verifiability. We introduce TrustTrack, a protocol that embeds structural guarantees -- verifiable identity, policy commitments, and tamper-resistant behavioral logs -- directly into agent infrastructure. This enables a new systems paradigm: trust-native autonomy. By treating compliance as a design constraint rather than post-hoc oversight, TrustTrack reframes how intelligent agents operate across organizations and jurisdictions. We present the protocol design, system requirements, and use cases in regulated domains such as pharmaceutical R&D, legal automation, and AI-native collaboration. We argue that the Cloud -> AI -> Agent -> Trust transition represents the next architectural layer for autonomous systems.