Low-code studio

Design an agent in plain language, then inspect the Agno shape underneath.

Start with a template, describe the job in your own words, then shape the brain, tools, live connections, and specialist paths directly from this workspace.

Modes

Beginner first

Natural-language planning and plain words lead the experience, with Agno details shown alongside.

Runtime target

Agno on Cloud Run

Every hosted build is shaped around the DataFluid Agno runtime and an A2A-facing surface.

Publishing stance

Private by default

Builders can explore safely first, then choose public or unlisted visibility after testing tools and connections.

Starter templates

Pick a direction

Creator share: 70% of each successful charge. The rest stays with DataFluid for platform costs, payment operations, and support.

Selected template: General-purpose helper. You can keep the starter prompt or rewrite it in your own words.

Choose the brain

How should this agent think?

Long context keeper

Name and promise

Make the draft understandable

People who want practical help without technical setup overhead

Give it arms

Skills, MCPs, and specialist agents

1 selected
0 specialists0 live connections1 reusable skills

Saving turns on after you sign in and create your organization.

Draft overview

General-purpose helper

A beginner-friendly starting point for a helpful assistant that can answer, guide, and hand off. It starts with reference library.

Audience

People who want practical help without technical setup overhead

Who this first draft is designed to serve.

Brain

Long context keeper

A better fit when the agent should read policies, FAQs, manuals, or a large knowledge base.

Price setup

$0.015 / 1K tokens

Begin with a fixed credit price per call, then introduce token-based pricing once real usage patterns are stable. Creator share: 70%.

Launch

private

This stays inside your workspace until you feel comfortable sharing it more broadly.

Unsaved draftGuest session
BrainModel | datafluid/long-context-keeper

A better fit when the agent should read policies, FAQs, manuals, or a large knowledge base.

Personality and rulesInstructions

Be calm, clear, and beginner-friendly in every answer. Ask a short clarifying question only when the next safe step is unclear.

ArmsTools, skills, MCP, live agents

Lets the agent answer from FAQs, policies, manuals, and company documents.

TeamworkTeams, routers, loops, and parallel work

Start with one main helper and only call specialists when the request is outside the safe default lane.

Workflow preview

How the draft works

Main helperagent
General-purpose helper

Handles the main conversation and keeps the experience friendly for non-technical users.

Reference libraryskill
Reference library pack

Lets the agent answer from FAQs, policies, manuals, and company documents.

Saved drafts

Workspace history

Draft history appears here after you sign in, create an organization, and save your first builder draft.

Capabilities

Recommended arms and specialists

Reference libraryDataFluid curated
Reference library pack

Lets the agent answer from FAQs, policies, manuals, and company documents.

Official or curated source | easy
4 starter brains7 starter capabilities6 editable templates

Agno preview

What this means underneath

Runtime model key

datafluid/long-context-keeper

Instructions

  • Act as General-purpose helper.
  • Answer in plain language first and keep technical details optional.
  • State what you can do now, what needs a connected system, and when a human or specialist should step in.
  • Prefer the attached reference library before guessing.

Tools and connections

  • Reference library pack

Orchestration

  • Start with one main helper and only call specialists when the request is outside the safe default lane.

Launch advice

What to do next

  • Start private until your connections and guardrails behave the way you expect.
  • Use fixed price per call first, then refine token pricing once usage data is real.
  • Load your FAQs, policies, or operating notes early so the agent answers with your real language.