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The complete platform for designing, deploying, and monitoring AI agents & workflows

The back-office behind AI features in SaaS software

We help small product teams move fast with AI: build, test, deploy, version, run QA tests and monitor workflows with full observability, compliance, and budget control.

Draft'n run Studio
Monitoring dashboard
Draft'n run AI Agent Platform Dashboard

Trusted by Forward-Thinking Organizations

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AI Should Be Accessible!

Build production-ready AI workflows with complete transparency and control. Deploy sophisticated AI agents without vendor lock-in or black boxes.

Visual Workflow Builder

Design sophisticated AI agents using drag-and-drop components. No coding required to build complex multi-step workflows with our AI workflow builder.

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Real-time Testing

Real-time TestingReal-time Testing

Complete Observability

Complete Observability

Enterprise-Grade Monitoring

Comprehensive tracing and monitoring with detailed execution analytics and cost optimization recommendations for reliable AI automation, AI chatbots, and agentic AI.

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Open-Source Platform
for Complete Control.

Deploy AI workflows with full transparency and zero vendor lock-in. Self-host or use our managed cloud with complete data ownership and control. Build custom AI solutions tailored to your needs.

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Zero Lock-in

Open-source platform you can self-host anywhere

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Production Ready

Enterprise-grade monitoring and security from day one

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Rapid Development, Production Deployment.

Deploy AI features in minutes, not months. Test in interactive sandbox, monitor with comprehensive observability, and integrate via REST APIs.

  • iconNo-code Studio
  • iconInteractive Sandbox & QA
  • iconREST APIs & integrations
  • iconFull Observability

Quality Assurance : Test Extensively Before You Ship

Define datasets of test cases, compare versions, and validate outputs to prevent regressions across your AI workflows.

  • Datasets

    Group reusable test cases per app or feature, and select the workflow/agent version to evaluate.

  • Test Cases

    Provide input and optional expected output; use runs history to fill your dataset with real data.

  • Run Options

    Run one test, multiple selected, or all rows in a dataset with a single click.

  • Compare Versions

    Compare versions to see the impact of changes on your AI workflows before shipping.

  • Use LLMs as a Judge or use deterministic metrics

    Use LLMs to evaluate the quality of your AI workflows and test cases. Or use deterministic metrics like accuracy, precision, recall etc.

Quality Assurance

Complete AI Observability

Industry-leading monitoring and tracing capabilities that provide full visibility into your AI operations with production-grade observability from day one.

Complete AI Observability
iconDetailed Execution Tracing
End-to-end request tracing with OpenTelemetry integration, detailed trace trees with timing breakdowns, and complete data lineage tracking for every AI workflow component.
iconReal-time Cost Optimization
Token usage tracking per component, provider-specific cost breakdown, usage forecasting with budget alerts, and cost optimization recommendations to maximize ROI.
iconPerformance Analytics
Performance bottleneck identification, resource utilization tracking, queue monitoring with processing rates, and comprehensive benchmarking for continuous optimization.
iconIntelligent Monitoring
Custom metrics definition, real-time alert system for failures and anomalies, structured logging with correlation IDs, and proactive system health monitoring.

For Business Teams : Build Outcomes, Not Pipelines

A no‑code AI workspace to try ideas fast, stay within guardrails, and ship value with Data.

  • Build in Minutes

    Visual Builder and ready‑to‑use templates to assemble agents without writing code.

  • Safe by Design

    Governed sandboxes, approvals, and clear limits so you can explore without risk.

  • From Draft to Production

    Smooth handover with the Data team to promote winning drafts into production.

  • Focus on your expertise, not the tech

    Clean and simple user-friendly interface to handover your knowledge to the AI agents without any tech skills needed.

For Business Teams : Build Outcomes, Not Pipelines

For Data Teams : The Control Layer for AI

A Metabase‑like self‑serve layer to publish governed, observable AI use cases across your company.

  • Ship With Confidence

    Versioned workflows, gated promotion from sandbox to production, and CI/CD for AI agents and workflows.

  • Surgical Governance

    Policy Center to define who can run what, with which model or tool, and at what cost.

  • Complete Observability

    Traces, quality metrics, and full cost visibility (tokens, tools, context) by agent, team, and provider.

For Data Teams : The Control Layer for AI

Trusted by Forward-Thinking Teams

Early adopters are already seeing dramatic improvements in AI development speed and operational efficiency with Draft'n run.

5.0

"We tried Draft'n run due to the disappointing performance of our AI chatbot. Draft'n run's AI conversational agents quickly allowed us to exceed our performance objectives. We achieved significant cost savings and strengthened our clients' confidence, thanks to their automated and reliable responses. The results were almost immediate, as Draft'n run works smoothly and is completely integrated into our application ecosystem."

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Côme Fouques

CEO at INDY

5.0

"Draft'n run delivered exactly what we needed for data sovereignty in our defense consulting work. The platform's on-premise capabilities addressed our strict security requirements while giving our consultants an AI assistant that keeps them in full control of information exploitation and valorization. The scalability has been remarkable, we can deploy this across projects of any size while maintaining complete data control. It's a product that truly understands enterprise sovereignty needs."

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Marc Richez

President at CAPADYN

5.0

"We had 44,000 articles that subscribers struggled to navigate effectively. Draft'n run's AI assistant transformed content discovery entirely—subscribers now get contextualized responses and find relevant information instantly. The seamless integration preserved our existing subscription workflows while dramatically improving user experience and content valorization."

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David Ascher

Founder at Cogiterra

Frequently Asked Questions

Everything you need to know about building production-ready AI workflows with Draft'n run's visual platform. Start free trial →

01What is Draft'n run and how does it work?
Draft'n run is an open-source AI agent platform that enables teams to design, deploy, and monitor production-ready AI workflows through a visual interface. Our platform includes a drag-and-drop Studio for building workflows, an interactive Sandbox for testing, comprehensive Observability for monitoring, and REST APIs for integration—all without writing code.
02Do I need AI expertise to use Draft'n run?
No! Draft'n run is designed for teams without dedicated AI engineering resources. Our visual Studio uses drag'n drop components that make AI development accessible to product managers, developers, and business users. You can build sophisticated AI workflows, production AI chatbots, and agentic AI using pre-built components for inputs, AI agents, tools, and outputs.
03What LLM providers do you support?
We support all major LLM providers including OpenAI GPT, Anthropic Claude, Google Gemini, and Mistral. You can also integrate custom models and on-premise deployments. Our platform is provider-agnostic, so you're never locked into a single vendor.
04How is Draft'n run different from other AI platforms?
Unlike proprietary platforms, Draft'n run is open-source with no vendor lock-in. We focus on production readiness with industry-leading observability, complete transparency into AI operations, and enterprise-grade monitoring from day one. You can self-host the platform and maintain full control over your data and workflows. Compare options in our overview of n8n alternatives, understand agentic AI use cases, build AI chatbots, and learn how teams use n8n for AI alongside Draft'n run.
05Can I deploy Draft'n run on-premise?
Yes! As an open-source platform, you can deploy Draft'n run in your own infrastructure. We support Docker-based deployment. This gives you complete control over data privacy, security, and compliance requirements.
06What kind of monitoring and observability do you provide?
Draft'n run offers comprehensive observability including detailed execution tracing, real-time monitoring, performance analytics, error tracking, and cost monitoring. You get complete visibility into every AI operation with trace trees, token usage tracking, and custom metrics—all built-in from day one.
07How quickly can I deploy AI features with Draft'n run?
Teams typically deploy their first AI features in minutes instead of months! Our visual Studio accelerates development by 100x compared to custom AI development. The platform includes pre-built templates for common use cases, an interactive testing environment, and automated deployment processes.
08Do you offer support and professional services?
Yes! We provide implementation services, training programs, and custom integration development to help you succeed with AI workflows. Talk to us today to get started.
09How do I get started with Draft'n run?
You can start immediately by downloading our open-source platform or trying our managed cloud version. Visit draftnrun.com to access the Studio, explore our documentation, join our Discord community, or schedule a demo to see the platform in action. We also offer quick-start templates for common AI use cases.

Build AI Workflows in Minutes, Not Months!

Deploy production-ready AI workflows with complete transparency and control.
Start building today! Start free trial →