Your next agent is one click away from your previous step. Describe a process in conversation, point at the document that defines it, or pick the workflow that already runs it — AutoX AutoCreates the agent and its workflow, and the verifiable agentic transformation continues without skipping a beat.
Enterprises don’t start from a blank canvas. The process you want to agentify already exists somewhere: in someone’s head, in a document, or in an automation. AutoX starts from any of them — and every surface ends in the same two verbs: AutoCreate Agent and AutoCreate Workflow.
Describe the process in plain language. AutoX drafts the agent — skills, orchestration, gates — and shows you its execution graph before anything is born. Refine by talking; approve by clicking.
Point at the runbook, SOP, or spreadsheet that already defines the work. AutoX compiles it into a governed agent whose source stays attached as the ground-truth baseline and judge.
Pick a Governed Workflow you built — or import a legacy one (Conductor, n8n, Temporal) with an honest conversion report — and AutoCreate the agent that runs it, earning autonomy stage by stage.
Every Agentlet™ carries a Canonical Execution Graph: one versioned graph of everything the agent can execute. It is the same graph whether the agent runs Cognitive (the LLM reasoning loop picks tools at runtime), Deterministic (an agentic workflow invocation, step by step), or Hybrid (a deterministic head and tail around a cognitive body).
Deterministic steps are explicit nodes. The cognitive loop is a first-class node whose available tools render as availability edges — you can see exactly which skills the LLM may reach, under which preconditions, before it ever runs. Hybrid agents show head, body, and tail in one picture. No mode is a black box.
The CEG isn’t a diagram of the agent — it is the agent’s contract. Tighten a skill’s callability or preconditions, drop a human-approval gate in front of a consequential step, cap iterations and cost on the loop, attach Data Protection Guards — and the runtime honors it on the next call. Changes version; every edit seals to the record.
Agent platforms show you code. Workflow tools show you flowcharts of deterministic steps. Security tools show you traffic. To our knowledge, no other vendor renders — let alone lets you govern — the canonical execution graph of a cognitive agent: the reasoning loop, its reachable tools, and the gates around each one, in one editable, versioned, sealed artifact. That graph is what makes multi-surface AutoCreate safe: whatever surface you start from, you arrive at the same governable object.
AutoX is Prove7’s multi-surface AutoCreate engagement mode: it creates governed agents and workflows from wherever your process already lives — a conversation, a documented process (runbook, SOP, spreadsheet), or an existing workflow — with every step of the transformation sealed to a verifiable record.
The Canonical Execution Graph is the single, versioned graph of everything an agent can execute — its skills, gates, guards, and (for cognitive agents) the reasoning loop with availability edges to each reachable tool. It provides visibility into agents running in Cognitive, Deterministic, or Hybrid mode, and control: you govern the agent’s behavior by editing the graph itself.
A workflow diagram shows deterministic steps. A CEG also renders the non-deterministic part honestly: the cognitive loop is a first-class node, tools the LLM may call appear as availability edges (not fixed sequence), and every edge carries its policy gates — so even an LLM-driven agent is visible and governable before and during execution.
Yes. Per-skill callability and preconditions, human-approval gates, iteration and cost caps, rate limits, and Data Protection Guards are all properties of the graph. Edit them and the runtime honors the new contract on the next call — with the change versioned and sealed.
If you’re the one who answers when the machine acts — a CISO, a CFO, a COO — watch Prove7 Control Vector™ take an agent from discovered to governed to proven, live.
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