The Enterprise Interpretive Control Plane for AI & Agents.
Signal & Prism translates raw system signals and AI agent proposals into authority-aware, auditable meaning before execution. It sits above analytics, AI, and automation — ensuring intelligent systems operate within explicit institutional boundaries.
As AI agents begin invoking tools and modifying enterprise systems, interpretation can no longer be implicit. Meaning must be governed before action — not reconstructed after the fact.
Interpretation is not inferred. It’s designed.
Prediction is solved. Interpretation isn’t.
Modern systems overflow with signals — events, alerts, metrics, traces, behavioral logs, and model outputs. We’ve become excellent at collecting data and generating predictions.
What’s missing is a dedicated architecture that can say: “this is what it means, in context, and this is why it matters.”
Enterprises have mastered prediction and automation. What’s missing is a governed interpretive layer that ensures AI-driven action aligns with authority models, audit requirements, and security review processes.
- Analytics describe what happened
- AI predicts what might happen
- Observability alerts when something breaks
- Signal & Prism interprets what it means
Domain-based interpretation at the core.
Signal & Prism models complex problem spaces using domain-authored interpretive frameworks. These frameworks capture how experts understand entities, relationships, baselines, and change—without hard-coding meaning into models or pipelines.
Modern AI systems fail not because they lack intelligence — but because the domain expertise that gives signals meaning lives in people, not systems. Signal & Prism turns domain expertise into infrastructure: knowledge is explicitly authored, versioned, and governed as part of the system — so meaning remains consistent, reviewable, and governed even as models change, workflows evolve, and humans step out of the loop.
- Expertise is captured, not implied
- Judgment is formalized, not absorbed by operators
- Meaning is controlled upstream — before systems act
At runtime, the system:
- Separates signal ingestion from interpretation
- Applies domain context to evaluate meaning and significance
- Produces explainable, human-ready understanding
- Maintains continuity of interpretation over time
The goal is simple: meaning should be explicit, governable, and reviewable— especially in domains where context matters more than prediction.
Signal & Prism can operate in advisory mode — interpreting signals and delivering governed understanding without taking action or changing existing systems.
Authority-aware agent action.
An AI agent proposes a tool call or privilege change. Signal & Prism interprets the proposed action against explicit authority models and institutional context — producing a governed meaning artifact before execution.
- Evaluates scope and institutional impact
- Surfaces admissibility and boundary conditions
- Generates audit-ready explanation
- Supports advisory or gated execution modes
For teams building or governing AI systems in complex, high-stakes environments.
Signal & Prism is early-stage and intentionally focused. We’re engaging with enterprise builders, operators, and design partners who care about authority boundaries, auditability, and trustworthy automation.