The Control Plane for an Agentic Economy: Data-Blind Multi-Agent Workflows | DeCompute 26, Miami
Data-Blind Multi-Agent Workflows for Anti-Fraud, Commerce and Settlement
Hosted by Silence Laboratories and LFDT.
Every gain in AI so far has been vertical: bigger models, deeper reasoning inside a single agent. That has a ceiling. Practical intelligence, the kind that screens a payment, closes a purchase or settles a position, is collective: agents that work together, delegate to one another, reason jointly and act. Cells did it. Traders did it. Firms did it. Software agents are doing it now.
The catch is that collaboration and delegation only scale with two ingredients most agent frameworks still lack: a boundary on what each agent may see and do, and enforcement when it is crossed. Prompts and policies are neither. A society of agents needs a control plane: mandates enforced in the protocol, and workflows in which agents compute jointly on inputs none of them can see. Privacy is not a tax on the outcome here; it is what makes the outcome optimal. The moment an agent's private state can leak, it stops reporting truthfully and the joint result degrades.
The discussion is anchored on AP3, the Agent Privacy-Preserving Protocol that Silence Laboratories open-sourced to LF Decentralized Trust at the DeCompute 26 San Francisco chapter: an open substrate for data-blind multi-agent workflows, with mandates as the boundary, cryptography as the enforcement, and Google's A2A and AP2 as the connectivity and settlement rails. We will use it as a reference design to test against the three cases below, not as the answer.
This invite-only roundtable brings together senior leaders from banks, payment networks, fintechs and regtechs, alongside the LFDT community and agentic-security practitioners, under Chatham House rules.
Themes
Anti-fraud: Mule networks, synthetic identities and coordinated attacks that no single detection system sees; agents resolving entities and sharing signals across trust boundaries while raw records stay where they are.
Agentic commerce: Agents transacting under mandates and spend limits on a principal's behalf, without revealing the principal's intent to the counterparty.
Treasury and settlement: Agents negotiating liquidity, FX and routing while positions, limits and client flows stay private.
The control plane: Consent, authority, delegation, revocation and auditability as agents cross trust boundaries, inside an institution and between them.
Expected Outcomes
A reference model for data-blind multi-agent workflows across the three cases: architecture, privacy, mandates, governance and incentives.
A shortlist of high-value use cases ready for a pilot or consortium, with AP3 and LFDT as an open home for the work.
A practitioner working group to take a priority use case to proof-of-concept, and an industry white paper drawing on the discussion.
Who Should Attend
Fraud, financial crime and AML leaders; heads of payments, treasury and digital assets; and the AI, security and privacy teams at banks, payment networks, fintechs and regtechs building agent-driven workflows.
Due to space limitations, we are reviewing all interested registrations.