Flows & agents

Compose pipelines and agents from governed prompts.

Real AI features are rarely one prompt. VernaOne lets you chain your existing, versioned prompts into multi-step flows on a visual canvas — and lets models call tools in a governed loop — without writing orchestration code.

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~15 providers & tools behind one API — LLMs, media, search & scraping

OpenAIAnthropic ClaudeGoogle GeminiMeta LlamaOpenRouter

Orchestration code is where AI features rot

Multi-step AI logic hand-wired in code becomes a tangle of calls, retries, branching, and array fan-out that no one wants to touch. Adding a step or swapping a model means editing brittle glue, and there's no trace of what ran when it breaks.

Agent loops are worse: without hard caps they can run away on cost and iterations.

How flows and agents work

  1. 1

    Visual flow builder

    Chain prompts into pipelines on a canvas. Every node is one of your governed, versioned prompts, so a flow is composed from building blocks you already trust.

  2. 2

    Composable steps

    Build from prompt, parallel, map, and transform steps — run work in sequence, concurrently, or across arrays with fan-out and data shaping built in.

  3. 3

    Versioning & run tracing

    Version flows like prompts and watch every run with step-level status, retries, and configurable error policies — so failures are visible, not mysterious.

  4. 4

    Agentic tool-calling (preview)

    Let a model call tools — web search, web scrape, HTTP request, and your own prompts — inside a governed, provider-agnostic loop with cost and iteration caps so an agent can't run away.

Highlights

🎛️

Visual canvas

Compose flows from prompt, parallel, map, and transform steps — no orchestration code.

🧵

Run tracing

Step-level status, retries, and error policies make every run auditable.

🤖

Governed agents

Tool-calling loops with cost and iteration caps keep agents safe and bounded.

🧩

Built from your prompts

Every step is a versioned prompt you already govern — reuse, don't rebuild.

Agentic tool-calling runs provider-agnostic with hard cost and iteration caps — the guardrails are part of the runtime, not something you bolt on.

Ship on this — free to start.

Author a prompt once and call it by name. VernaOne handles the model, the fallback, the cost, and the alerting.

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Frequently asked

What step types can a flow use?

Flows are built from prompt, parallel, map, and transform steps — letting you run work in sequence, run branches concurrently, fan out across arrays, and shape data between steps.

Is agentic tool-calling available now?

It's in preview. A model can call web search, web scrape, HTTP request, and your own prompts inside a governed loop with cost and iteration caps that keep it bounded.

Can I see what a flow run did?

Yes. Flows are versioned and every run is traced with step-level status, retries, and configurable error policies, so you can audit exactly what happened.