Decision Infrastructure
Decision Infrastructure for AI Systems
Architectures change. Decisions still fail the same way.
SignalSmith focuses on the governance of why a system acts, whether it should act, and who is accountable when consequences land.
Decision infrastructure keeps intent, execution, and accountability connected across MCP, A2A, RAG, workflows, and copilots.
Decision layers
Three decision layers hold regardless of choreography.
- Forge: intent formation
- SignalFrame: governed execution
- Atlas: post-decision accountability
Same decision layers, different choreography
Architectures collapse into the same decision layers, even when the choreography looks different.
- Forge — intent formation before commitments.
- SignalFrame — governed execution with authority checks.
- Atlas — post-decision accountability and consequence.
Centralized access vs decentralized agency
MCP centralizes access through a unified control plane. A2A decentralizes agency across many agents. Decision infrastructure makes both architectures accountable to the same intent, execution, and accountability layers.
Research that stress-tests decisions
Our research POV pressure-tests the same decision layers across architectures, proving how intent, execution, and accountability hold up under real-world demand.