Melodi provides AI agent monitoring tools to help product teams quantify user intent and measure the success of their conversational AI deployments. The platform tracks engagement metrics, collects explicit and implicit user feedback, and facilitates structured data labeling for continuous improvement. This enables organizations to systematically enhance AI performance, increase adoption, and drive measurable business impact from their agentic AI products.
Funding
Funding not disclosed
Founders
Product
Problem
Analyzing customer interactions with AI agents, such as chatbots and voice bots, is challenging and often relies on manual methods, leading to guesswork rather than data-driven decisions. Existing analytics solutions may be biased, focusing on positive performance while overlooking critical failures and areas for improvement. Identifying the root causes of user frustration, which may stem from issues beyond the AI model itself, requires a comprehensive approach.
Solution
Melodi is an AI analytics platform designed to provide actionable insights from customer interactions with AI agents. It automatically identifies and flags costly failures in conversations, enabling teams to address issues before they negatively impact customer trust, retention, or revenue. The platform leverages LLM-based evaluations to understand user intents, quantify interaction outcomes, and prioritize opportunities based on business impact. Melodi facilitates a systematic approach to AI agent improvement, considering factors beyond the AI model, such as knowledge base content, conversation design, and support workflows.
Target Audience
Melodi is designed for product managers, operations teams, and data scientists involved in building and managing AI agents, including those focused on agentic AI products and customer support agents.
Features
- Automated LLM-based evaluations for in-depth analysis of session outcomes and user intents
- Monitoring of key metrics, including user engagement, retention rates, session volume, and user segmentation
- Tools for collecting explicit user feedback (ratings, comments) and implicit signals via flexible APIs and components
- Platform for internal human review and structured data labeling to create datasets for product analysis and ML training
- Weekly generative analysis reports highlighting improvement opportunities
- Export functionality for all session data
- Feedback widget and Slack notifications for real-time alerts