Centralized controls sit in a shared layer, typically a gateway or middleware, that every agent's traffic passes through on its way to a model or tool. That gives an organization one place to define, update, and audit policy, and it applies consistently no matter which team built the agent generating the traffic. Embedded controls are built directly into each application or agent's own code, tailored to that specific app's logic and context. Both are legitimate ways to enforce AI security policy, and most mature programs end up running both at once rather than treating this as a choice between two exclusive architectures. The real question isn't which one wins, it's which controls actually need to be consistent everywhere and which ones only make sense in the context of one specific application.
What centralization actually buys you
The core value of a centralized layer is consistency. Write a rule once, and it applies identically to every agent whose traffic routes through the gateway, whether that agent was built last week or three years ago by a team that's since moved on. That consistency also gives you a single audit point: one place to look for a complete record of what every agent in the organization actually did, rather than piecing together fragments from a dozen different applications with a dozen different logging conventions. Updating policy org-wide becomes a change in one place instead of a coordinated rollout across every team's codebase.
What centralization costs you
None of that comes free. A centralized layer requires every agent's traffic to actually route through it, which means integration work for every application, existing or new, and a dependency the whole system now has on that layer being available and fast. If it's not designed with real request volume in mind, it becomes a bottleneck, adding latency or, worse, a single point of failure that can take down enforcement for every agent at once if it goes down. Centralization also tends to push policy toward the lowest common denominator: rules general enough to apply sensibly across very different applications, which can miss risks that only make sense in the context of one specific app's domain.
What embedding actually buys you
Controls built directly into an application's own code can be as specific as that application needs them to be. A check written by the team that owns a given agent can reason about that agent's exact business logic, its specific data model, and the particular ways it could misuse a tool that a general-purpose centralized rule would never be able to express cleanly. There's no added infrastructure dependency either: the check runs as part of the application, with no separate service to route through, no additional network hop, and no shared layer that could become a bottleneck for everyone at once.
What embedding costs you
The tradeoff shows up as soon as you have more than one application. Embedded controls have to be implemented and maintained separately in every app, which means the same policy intent can end up expressed slightly differently, or not at all, depending on which team got around to it and how thoroughly. That drift is hard to catch, because auditing embedded controls consistently across a growing fleet of agents means checking each application's code individually rather than reviewing one shared configuration. An organization can end up with twenty agents, twenty slightly different implementations of what was meant to be the same rule, and no easy way to confirm they're actually equivalent.
Where the two genuinely overlap
Both approaches are ultimately trying to enforce the same organizational intent: what an agent is and isn't allowed to do. The overlap shows up most clearly in a mature setup, where a centralized layer handles the broad, universal rules, and embedded checks handle the narrow, app-specific logic on top of that. Neither one is trying to be the whole solution in that setup; they're dividing the work along the line that actually matches where each is strongest.
Deciding which controls belong where
A control belongs in the centralized layer if it needs to apply the same way across every agent, regardless of which team owns it, things like authentication, broad authorization boundaries, and organization-wide hard limits. A control belongs embedded in an application if it depends on business logic specific to that app, logic a shared gateway has no visibility into and shouldn't be expected to reimplement generically. Getting this split wrong in either direction causes real problems: forcing app-specific logic into a centralized layer makes that layer bloated and hard to reason about, while pushing organization-wide rules down into every app's own code guarantees inconsistency as the fleet of agents grows.
Where TELEON fits
TELEON's architecture is centralized: it deploys as a gateway or middleware between agents and the model providers and tools they call, giving an organization one place to enforce policy consistently and one place to see a complete audit trail of agent activity across the fleet. That model corresponds to the centralized side of this comparison, not the only valid approach, but the one suited to organizations that want consistent, auditable enforcement without relying on every application team to implement and maintain the same logic independently. App-specific logic still belongs embedded in each application; TELEON's layer is for the controls that genuinely need to apply the same way everywhere.
A short checklist
- List which policies genuinely need to apply identically across every agent; those are candidates for centralization.
- List which checks depend on logic specific to one application's domain; those belong embedded.
- Confirm your centralized layer is designed for your actual request volume so it doesn't become a bottleneck.
- Audit embedded controls across your fleet of agents for drift between apps that are supposed to enforce the same rule.
- Check whether any organization-wide rule currently only exists embedded in one or two applications.
- Verify your centralized layer's audit trail actually covers every agent that's supposed to route through it.
- Revisit the split periodically as new agents and new applications get added to the fleet.
Most programs need the split, not a single winner
Treating this as a binary choice misses how these two approaches actually complement each other. Centralized enforcement gives an organization consistency and a single point of audit for the rules that matter everywhere; embedded checks give each application the specificity a shared layer can't provide on its own. The programs that struggle are usually the ones that picked one exclusively, either drowning a centralized layer in app-specific exceptions or discovering, usually during an incident, that the same rule was implemented three different ways across three different agents.