AgentRunner

Visually design, deploy, and manage AI agents and automated workflows without heavy coding.

4.6 (5)

리뷰어 Daniel Nikulshyn·업데이트됨 2026년 5월

No-Code AI Agents Low-Code LLM Integration Workflow Automation Visual Builder Team Collaboration

개요

AgentRunner is a visual development platform for building AI-powered applications and autonomous agents. Through a drag-and-drop interface, users can connect language models, tools, data sources, and logic blocks to create custom workflows that handle tasks like research, customer support, content generation, and process automation. The platform targets both technical and non-technical builders, offering reusable components, agent templates, and runtime management so teams can prototype quickly and scale into production. Built-in monitoring helps track agent behavior, costs, and outputs over time.

주요 기능

Drag-and-drop agent builder
Integrations with popular LLMs and APIs
Workflow automation and scheduling
Agent runtime monitoring and logs
Template library for common use cases
Team collaboration on shared projects

사용 사례

Automate Customer Support Triage

Build an AI agent that reads incoming tickets, classifies them, and routes or responds using connected LLMs and data sources, reducing manual workload.

Run Multi-Step Research Agents

Design autonomous agents that gather information from multiple APIs and sources, synthesize findings, and deliver structured research reports on a schedule.

Prototype Content Generation Pipelines

Use drag-and-drop blocks to chain prompts, tools, and review steps for generating, refining, and publishing content without writing extensive code.

Monitor and Manage Production Agents

Deploy agents into production and use built-in logs and runtime monitoring to track behavior, outputs, and LLM costs across the team's shared projects.

장단점

장점

Low-code visual builder speeds up prototyping
Supports multi-step autonomous agents
Reusable templates and components
Centralized monitoring and management

단점

Visual approach may limit highly custom logic
Learning curve for complex agent design
Dependent on external LLM provider costs

리뷰

4.6

5개 평가의 평균.

리뷰를 작성하려면 로그인하세요.

Wei Chen

Solid for our team

We rolled this out across the team last quarter and supports multi-step autonomous agents. Drag-and-drop agent builder fits neatly into how we already work, and integrations with popular LLMs and APIs removed a step we used to do by hand. but it has held up under daily use.

Victor Nguyen

Skeptical, then convinced

I went in skeptical — most tools in this space overpromise. It actually delivers on agent runtime monitoring and logs, and reusable templates and components caught me off guard. Learning curve for complex agent design is why this isn't a perfect score, still, I'd recommend giving it a real trial.

Grace Okafor

Use it every day

Honestly didn't expect to like it this much. Agent runtime monitoring and logs is exactly what I needed, and low-code visual builder speeds up prototyping. I do wish visual approach may limit highly custom logic, but I reach for it almost every day now and it just clicks.

Leila Hassan

Skeptical, then convinced

I went in skeptical — most tools in this space overpromise. It actually delivers on drag-and-drop agent builder, and reusable templates and components caught me off guard. Learning curve for complex agent design is why this isn't a perfect score, still, I'd recommend giving it a real trial.

Marcus Bell

Use it every day

Honestly didn't expect to like it this much. Team collaboration on shared projects is exactly what I needed, and low-code visual builder speeds up prototyping. but I reach for it almost every day now and it just clicks.