A security architecture where detection, search, and investigation operate on data wherever it lives, instead of requiring everything centralized into one store first.
You define the transformation. The agents work wherever your data is.
A federated SIEM decouples the analytical functions of security operations from the storage of security data. Instead of ingesting everything into one repository, the analytic layer reaches out to data in place: existing SIEMs, data lakes, cloud platforms, and security tools. Nothing has to move, nothing gets duplicated, and where data lives becomes a cost decision instead of a constraint on what security can see. And because detection becomes its own layer, it becomes a system that improves instead of a rulebook that decays.
What you can detect no longer depends on what you have ingested. The analytic layer and the storage layer are independent decisions.
Search, correlation, and investigation run against data where it already resides. Movement is the exception, not the prerequisite.
One copy serves both its original purpose and security analytics. No shadow copies, no double storage bills, no sync drift.
A SIEM, data lakes, cloud stores, or a vendor lake can all participate, in any combination, and the mix can change.
Shrink the SIEM, grow the lake, or keep everything where it is, without re-platforming the security operation.
Investigation outcomes feed back into detection content. The system sharpens over time instead of accumulating stale rules.
Two questions. Can you change where your data lives without changing what you can detect? And is your detection content getting better, or just getting bigger? In a traditional SIEM, visibility is whatever you ingested and rules pile up stale. In a federated SIEM, detection was never coupled to storage, and it is a managed, improving system.
The data world already made this shift. When federated query engines arrived, nobody ripped out the warehouse, they kept it where it earned its cost, moved cold data to cheaper lakes, and queried all of it as one. Security is the last discipline still paying to centralize everything before it can ask questions.
No. Federated search is one function: finding data across multiple stores. A federated SIEM federates the full analytical stack: continuous detection, correlation, investigation, and response all operate across data in place. Search tells you where something is. A federated SIEM decides what it means and what to do about it.
No. Your SIEM becomes one participating layer. Keep it at the center, shrink what you send to it, or retire it over time. Because detection is abstracted from storage, that is a choice you make on your own timeline, not a forced migration.
Two pressures converged. SIEM consumption costs keep climbing, forcing teams to choose between visibility and budget. And security data has already sprawled beyond the SIEM into data lakes, cloud platforms, and SaaS tools, so centralization is a losing race. A federated architecture resolves both: full analytical reach without paying to move and store everything twice.
The opposite. In a centralized model, visibility is capped by what you could afford to ingest. In a federated model, the analytic layer reaches everything that participates, including data that never would have justified SIEM ingestion costs.
Ingestion and Pipelining (collection, routing, and inline watchlisting), Storage (7AI-hosted, customer-owned, or both), Detection and Query (continuous detection analytics plus analyst-driven search and reporting), and Intelligence (the management layer that tunes detection content over time based on outcomes). Every layer is an independent choice.
Through the agentic flywheel. Every detection triggers an autonomous investigation, and every investigation outcome (validated threat, benign pattern, coverage gap) feeds back into detection content through the Intelligence layer. Rules get tuned, stale logic retired, gaps closed, continuously and per environment. Traditional detection content decays; this sharpens.
Search is step one. 7AI's agents don't just find the data; they run continuous detections against it, investigate autonomously with full reasoning shown, and act. Search tools return results. Agents deliver outcomes.
This is where the foundation matters. Detections flow directly into autonomous investigation by the same agents, drawing on your environment's context and investigation memory, with the full reasoning trail recorded. You get a validated, explained verdict, not another alert in a queue, and the outcome feeds the flywheel.
PLAID ELITE is a managed overlay across whichever layers 7AI runs. It is not a fifth layer; it is 7AI's security experts operating the federated architecture as an extension of your SOC, 24x7.