Runtime Control Layer v1.0 // Operational
Research Abstract .001

One control room
for your entire agent fleet.

Beyond the limits of a single agent. AI Agent Platform is a runtime control layer that manages fleets of dozens of AI agents (Dals) at a global scale. Declarations live in Git; execution is centrally controlled.

Core Directive

Whole-Agent
Management.

This is not about managing individual chatbots. The platform orchestrates the full lifecycle of multiple AI containers at the infrastructure level, so they operate as a cohesive unit.

01

Declarative Config, Live Execution

Every agent's configuration is defined as a declarative config template in a Git repository. The platform watches this declarative state and reflects changes into the runtime environment in real time.

Without manual intervention, it wakes, sleeps, and syncs multiple containers simultaneously.

02

Full-Spectrum Orchestration

Agents built on Claude, Codex, Gemini, and other models are unified under a single control surface. Repository changes, credentials, and memory state are continuously verified.

All control flows and fleet status alerts are transparently relayed through team communication platform, giving your operations team complete visibility.

FLEET_STATUS_MONITOR 00:00:00 UTC
dal-claude-ops-01
RUNNING
Model: claude-3-opus | Uptime: 14h 22m
Task: Log Analysis & Triage
dal-gemini-data-02
SYNCING
Model: gemini-1.5-pro | State: Fetching declarative config
Task: Dataset Processing
dal-codex-build-03
SLEEP
Model: codex-v2 | Trigger: Pending PR
Task: Automated Code Review
dal-claude-sec-04
RUNNING
Model: claude-3-sonnet | Uptime: 02h 10m
Task: Vulnerability Scanning
Take command of your fleet.