Ask, anticipate, automate
AgentFlow brings three modes into one governed system:
The workflow is what connects an answer worth repeating to an operation the business can trust.
A workflow is a declarative agent
Most agent platforms give you a chatbot that picks tools at runtime. That’s fine for generic tasks, but it’s the wrong primitive for proprietary domain knowledge, such as a 14-step quality-deviation investigation, a regional production-yield rollup, or a supplier SLA breach playbook. Those need predictability, auditability and reuse. In AgentFlow:- A workflow is a declarative, data-driven way of building an agent.
- Each agentic step of a workflow is a small, scoped agent.
- A workflow is deterministic orchestration of agentic and deterministic steps.
Workflows are your IP
Domain workflows are data: JSON specs, versioned in storage, not application code. The teams who own the know-how, such as process engineers, quality leads and supply-chain analysts, author and evolve them without engineering changing the application.Why compiled is cheaper and safer
Because each step has a focused context and deterministic steps skip the model, a compiled workflow is predictable, fast, cheap and auditable. See Safe by design for the safety side. On a 5-step TPC-DS analytics workflow, e6data compared the compiled workflow (per-step scoped agents with per-step prompt caching) with the same spec on an interpreted runtime (one large agent over all steps, no caching):
The interpreted path used 19.03 times the tokens for the same workflow, data and output. The saving is structural, so it grows as workflows grow.