Doppler AI

Dopplr: Automated Maintenance Platform for Scalable AI Agents

Dopplr is a platform designed to automate the testing, maintenance, and prompt updates of AI agents, ensuring they remain effective as customer bases and operational demands grow. By continuously monitoring feedback, simulating conversations, and running improvement loops, Dopplr eliminates manual maintenance bottlenecks, allowing teams to scale their AI agents without increasing support workload.

Key Features

• Automated Prompt Testing and Updates:
  Continuously tests agent prompts and settings, automatically deploying fixes to prevent broken updates and maintain optimal agent performance.

• Instant Feedback Monitoring:
  Tracks customer feedback and agent failures in real time, enabling rapid identification and resolution of issues.

• AI Simulation Before Deployment:
  Runs simulations of agent conversations after each change to catch issues before they reach end users.

• One-Click Updates Across Agents:
  Allows teams to respond to customer issues and update multiple agents simultaneously with a single action.

• Continuous Improvement Loops:
  Automates the process of detecting, testing, and resolving agent issues, reducing manual intervention and freeing up developer time.

• Rapid Onboarding:
  Teams can get started in minutes by selecting agents, integrating feedback, and initiating automated improvement cycles.

Use Cases

• Organizations scaling AI-powered customer support or voice assistants

• Teams needing to maintain consistent, high-quality agent performance as user volume grows

• Developers looking to minimize manual maintenance and focus on product development

Getting Started

• Website: dopplr.dev

• How to Start: Visit the website to learn more and begin automating your AI agent maintenance with Dopplr’s streamlined onboarding process.

Dopplr enables teams to maintain and scale AI agents efficiently by automating prompt management, testing, and updates—ensuring reliability and freeing up resources for core product innovation.