Assemble AI agents from a component library, test them in a live console, and deploy them into your workflows — with guardrails on by default.
From idea to a verified run — without code or credit math.
Pick a role, allowed tools and memory scope.
Validate behaviour step by step, safely.
Ship into a workflow with limits enforced.
Everything is transparent, verifiable, and yours to keep.
Drag composable, color-coded blocks across 14 families: Inputs, AI models, Processors, Integrations, MCP, Memory, Verification, R-Series, Agent Control, Knowledge (RAG), Timing, Human Approval, Control and Outputs — each tinted by kind so a flow reads at a glance.
Dry-run an agent and inspect each step before you ship.
Egress allowlist, receipts and tier limits inherited automatically.
Give agents native apps, MCP servers, or any API you allow.
Run agents inside workflows, on a schedule, or on demand.
Every agent step is signed and independently verifiable.
Orchestrate many agents, route by intent, and hand off between specialists.
Attach a knowledge base, vector search, and document readers for grounded answers.
Delay, schedule, or wait-until — pace flows to the real world.
Insert approval gates and human review before an agent acts.
Native apps, AI models, and any MCP server — bring your own keys.
Plus a universal API connector for any REST/OAuth endpoint.