Draft’n Run provides a no‑code visual builder for creating, testing, and deploying multi‑step AI agents and automations, offering drag‑and‑drop LLM orchestration, tool integration, and over 100 pre‑built connectors. The platform includes real‑time testing, OpenTelemetry‑based tracing, cost monitoring, and enterprise governance features such as version control, role‑based access, and SOC 2 compliance, while supporting self‑hosted or managed deployments to avoid vendor lock‑in.
Funding
Funding not disclosed
Founders
Product
Problem
Product teams often need to integrate AI capabilities such as large language model (LLM) orchestration, tool usage, and multi-step automation, but existing automation platforms are either code‑centric, lack native AI support, or provide limited observability, governance, and cost control. This makes building, testing, and maintaining production‑ready AI agents slow, opaque, and risky for enterprises.
Solution
Draft’n Run offers a visual, no‑code workflow builder designed specifically for AI automation. Users can drag‑and‑drop LLMs, external tools, and logic blocks to create multi‑agent workflows, chatbots, or data pipelines without writing code. The platform includes built‑in prompt management, retrieval‑augmented generation, and 100+ pre‑built integrations with major LLM providers, CRMs, databases, and communication channels. Real‑time testing and OpenTelemetry‑based tracing give full observability of execution paths, performance metrics, and token‑level cost tracking. Enterprise features such as version control, role‑based access, staging environments, and SOC 2‑compliant security ensure reliable, governed deployments, while the open‑source core and optional self‑hosting eliminate vendor lock‑in.
Target Audience
Primary customers are SaaS product teams and enterprise engineering groups that need to embed AI features quickly, as well as system integrators building custom AI solutions for clients across industries such as e‑commerce, real estate, B2B SaaS, and travel.
Features
- Drag‑and‑drop visual builder for constructing multi‑step AI agents and automations without code
- Native LLM orchestration with built‑in prompt libraries, RAG, and tool integration
- Over 100 pre‑configured connectors (e.g., OpenAI, Anthropic, Google Gemini, HubSpot, Salesforce, Slack, Shopify, PostgreSQL)
- Real‑time workflow testing sandbox with instant feedback on responses and token usage
- Full production observability: execution tracing, performance dashboards, cost monitoring, and alerting
- Enterprise governance: versioning, role‑based access control, staging vs. production environments, SOC 2 compliance
- Open‑source architecture supporting self‑hosted, hybrid, or managed cloud deployments for zero vendor lock‑in