Multi-Agent Automation Platform
Orchestrate fleets of AI agents across asynchronous execution graphs. Otogent's multi-agent infrastructure manages workflow DAGs, parallel agent coordination, and per-agent token budgets — so you can ship production-grade automation without managing the runtime yourself.
Asynchronous Execution Graphs
Traditional automation tools execute agents sequentially. Otogent models agent pipelines as directed acyclic graphs (DAGs), allowing any branch of your workflow to execute in parallel the moment its upstream dependencies resolve. This cuts wall-clock time dramatically for complex multi-step automations and ensures your infrastructure scales linearly with parallelism.
Per-Agent Token Management
Each agent in a workflow runs with an isolated token context. Otogent tracks cumulative token consumption per agent per execution, enforces configurable budget ceilings, and emits real-time telemetry — preventing runaway cost spikes before they hit your billing dashboard. Token allocation is inherited from the workflow definition and can be overridden at the node level.
Workflow DAG Architecture
Every Otogent workflow is stored as an immutable DAG snapshot. Conditional branches, fan-out merges, and human-in-the-loop approval gates are all first-class graph primitives. The runtime evaluates topological order at execution time, meaning you can dynamically re-route execution without rebuilding the entire workflow from scratch.
| Feature / Architecture | Otogent | Traditional Automation Tools |
|---|---|---|
| Asynchronous Agent Execution | - | |
| DAG-based Workflow Graphs | - | |
| Per-agent Token Management | Manual only | |
| Parallel Agent Coordination | Native | Limited |
| Runtime State Persistence | - | |
| Model-Agnostic Routing | - |
Explore Platform Infrastructure
Agentic Workflows
Design stateful, long-running agentic workflows backed by persistent runtime state machines that survive restarts and execution loops.
AI Workflow Orchestration
Model-agnostic routing that abstracts Gemini, Claude, and OpenAI into a single composable orchestration layer.
Deploy Your First Multi-Agent Workflow
Connect your models, define your agent graph, and execute — Otogent handles the orchestration runtime so your team ships faster.