AI agents and workflow automation for organizations

Turn AI into working systems.

Build and run AI agents and workflows with Radon Studio. Connect internal systems through a customer-side connector, choose your model endpoint and deploy in your environment. Bring role-based AI into everyday work with Radon Mini.

Watch one request become a finished task.

A customer asks a question. Radon reads the answer from an internal system, an agent prepares the reply and a follow-up lands in the CRM. Every step stays visible in Studio.

Support intakeProduction

A customer asks a product question and asks for a follow-up.

Interactive walkthrough of the support-request scenario. Interfaces are simplified for illustration; the demo shows the release itself.

See it with your own systems. Bring one process and we’ll show how Radon builds, connects and runs it.

Request a demo

Build AI around the systems your organization already uses.

Radon brings three things together: access to internal systems, one path from canvas to running service, and open choices for models and infrastructure.

  • Reach systems behind the firewall

    Connect workflows to internal services through an encrypted, customer-side tunnel. Agents work with the systems where your operational data already lives.

    See the private connection
  • Shorten the path to production

    Design, test, publish and trace work in one environment, then keep inspecting it after it goes live.

    Follow a flow from canvas to service
  • Keep model and infrastructure choices open

    Match local or compatible model endpoints, and the place your workflows run, to cost, quality and data policy.

    Trace the data path
  • Reuse what you have built

    Extend Flow Blocks, import or export projects and add custom Python nodes as needs grow, instead of rebuilding each integration.

    See reuse in Studio

One platform, two ways to work.

Teams build and run agents and workflows in Studio. Employees use personal and role-based agents in Mini.

Build with Radon Studio

Use a visual canvas and AI assistance to design agents and workflows. Connect data and tools, test each step, publish the flow and inspect its execution.

  • Describe a change, approve the plan. Build or edit flows from prompts, and review the AI-generated plan before anything is applied.
  • Agents that take action. Connect models to tools, memory and sub-agents that work across real systems.
  • Knowledge from your documents. Build retrieval from organizational files and databases with vector search and AI blocks.
  • A runtime included. Studio runs what you build. Radon Self-hosted is an optional organizational runtime.
Radon Studio canvas: a support flow with web chat, an internal customer database, document search, an agent and a proposed CRM follow-up step awaiting approval.

Work with Radon Mini

Bring personal and role-based agents into everyday work, with the files and tools your organization makes available.

  • An agent for each role. Give procurement, HR or support their own agent with instructions that fit the job.
  • Your files, your tools. Agents work with the documents and tools your organization approves for each person.
  • From answer to follow-up. Where supported, turn a result into a task with an owner and a date.
Radon Mini workspace: a procurement agent compares three supplier quotes from shared files and offers to create a follow-up task.

From canvas to operational service.

The same flow moves through four stages without leaving Studio, and stays inspectable after it is published.

  1. 01

    Design

    Lay out the flow on a visual canvas, or describe what you need and review the plan the AI assistant proposes before it is applied.

  2. 02

    Connect

    Attach data, tools and internal systems, and choose the model endpoint each agent uses. Private services are reached through the customer-side connector.

  3. 03

    Test

    Run each step on its own, read its output and fix what fails before anyone depends on it.

  4. 04

    Run and operate

    Publish an entry point, keep development and production apart, follow every execution and return to an earlier version when you need to.

Start where the work repeats.

Three recognizable jobs, each with a clear input and a result you can check.

Knowledge-based support

Studio
Input

A customer question arrives in web chat.

  1. Read the customer record and the relevant documents
  2. An agent drafts the answer with the chosen model
  3. Record a follow-up in the CRM
Result

An answer for the customer and a follow-up the team can act on.

Operations automation

Studio
Input

A form submission or a system event.

  1. Read the matching internal record
  2. Update the database
  3. Notify the owner in Telegram or by email
Result

An updated record and an owner who knows what changed.

Everyday agent work

Mini
Input

Files an employee shares with a role-based agent.

  1. Review and summarize the files
  2. Propose next actions
  3. Turn the result into a task, where supported
Result

A summary and a task with an owner and a date.

Also suited to employee assistants, document processing, reporting, system synchronization and knowledge-based support.

Connect the systems your work depends on.

Combine private services, APIs, databases, files, models and approved tools in one connected workflow.

Swipe to explore the full scene

  1. The flow asks for an order record.
  2. The request travels through an encrypted tunnel to the connector inside your network.
  3. Your internal API answers.
  4. The result returns to the flow, and the agent continues.
  • Private services

    Internal APIs and databases behind your firewall, reached through Radon Private Network.

  • APIs and webhooks

    Call REST services, receive webhooks and start flows from events.

  • Data and files

    Databases, file storage and documents, with retrieval through vector search.

  • Models

    Local model endpoints or compatible providers, chosen for each agent.

  • MCP tools

    Give agents approved tools through the Model Context Protocol, an open standard for connecting AI to tools.

  • Channels

    Web chat, Telegram, forms, webhooks and scheduled tasks, delivered through APIs and MCP.

Choose where your AI runs.

Three separate decisions shape your data path: where workflows run, which model endpoint receives requests and which systems supply the data. Try them.

Workflows run on
Model endpoint

Studio runs the workflow with its own runtime. Each model request goes to your local endpoint, so inference happens on infrastructure you operate.

Swipe the scene to see all of it

Local hosting alone does not prevent data from leaving the organization. Align your runtime, model endpoint and data path.

Clear roles for each part of the family

Radon StudioBuild and run
Design, test, deploy and execute agents and workflows. Studio includes its own runtime.
Radon Self-hostedOptional organizational runtime
Import Studio projects and operate them internally with roles, access controls and audit logs.
Radon GatewayOptional model access
A separate product for model routing, API keys, budgets and usage reporting.
Radon Private NetworkConnectivity
A customer-side connector with an encrypted tunnel that links workflows to internal services.

Studio runs independently. Self-hosted is optional. Gateway is not required.

Studio organizes teams and projects with organizational sign-in. Self-hosted adds operational roles and audit logs. Control Center, for centralized operator administration, is in preparation.

Look inside a running flow.

Execution history, recovery, deployment and reuse are part of Studio, so a published flow stays something you can inspect and change.

Find the step that failed. Resume from it.

Every execution keeps each step’s input, output and state. When a run is interrupted, you see where it stopped and resume the stateful work from that step instead of starting over.

Separate development and production. Keep every version.

Work in development, publish to production and keep a record of each deployment. If a change misbehaves, return to an earlier version.

Build a step once. Use it everywhere it fits.

Package steps as a Flow Block and drop it into other flows. Move projects between environments with import and export, and write a custom Python node when a block does not exist yet.

Questions teams ask first.

Something else on your mind? Add it to your demo request and we’ll cover it.

Where should we start?

With one real process that repeats, touches a few systems and has a result you can check. In the demo we use your systems, model requirements and data path to show how Radon would build, connect and run it.

How does Radon reach systems behind our firewall?

Radon Private Network places a customer-side connector inside your network and links it to your workflows through an encrypted tunnel. Flows can then call internal APIs and databases where your operational data already lives.

Which models can we use?

A local model endpoint for internal inference, or compatible external providers, chosen to fit cost, quality and data policy. An external provider receives the data included in each model request. Radon Gateway, a separate optional product, adds model routing, API keys, budgets and usage reporting.

Can we host Radon in our own environment?

Yes. You can host workflows and project resources in your environment, with databases and file storage kept separate by project. Radon Self-hosted is an optional organizational runtime for imported Studio projects, with roles, access controls and audit logs.

What is the difference between Studio and Mini?

Studio is where teams design, connect, test, publish and inspect agents and workflows. Mini is a workspace where employees use personal and role-based agents with the files and tools the organization makes available.

Do we need Self-hosted or Gateway to use Studio?

No. Studio includes its own runtime and runs independently. Self-hosted and Gateway are optional products you add when your operating model calls for them.

Can we extend Radon with our own code?

Yes. Add custom Python nodes, package reusable Flow Blocks, import and export projects, and connect services through APIs and MCP.

Start with one real process.

Tell us which systems, data and model requirements matter. See how Radon can build, connect and run a workflow around them.

  1. We read your requestand confirm the systems and deployment needs involved.
  2. We prepare the demonstrationaround your process, model choice and data path.
  3. We walk your team through itin Studio, Mini, or both.

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