Cuein AI provides an LLM Co-Pilot platform to optimize customer experience across chat, voice, and email interactions. The platform analyzes 100% of conversational data to deliver inferred CSAT, root cause analysis, and actionable insights for bot and agent performance. This capability helps organizations improve customer retention and reduce operational costs by refining conversational AI and support workflows.
Funding
$5.1M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Customer experience (CX) teams struggle to analyze conversational data across multiple channels (chat, voice, email) and vendors, leading to inefficiencies in identifying trends, understanding customer dissatisfaction, and optimizing chatbot performance. Manual analysis of transcripts and voice calls is time-consuming, error-prone, and doesn't scale effectively.
Solution
Cuein offers an AI co-pilot that consolidates customer support data from various sources to provide real-time analysis of customer interactions. The platform uses inferred CSAT and CSAT factors to pinpoint low satisfaction interactions, discover real-time trends, and automate root cause analysis. By visualizing user interactions with bots, Cuein helps diagnose breaking points, prompt failures, and hallucinations, enabling prompt and dialog improvements. The co-pilot also summarizes agent actions to fine-tune chatbots and scores agents on multiple dimensions to improve training and performance.
Target Audience
Cuein targets customer experience teams, contact centers, and organizations seeking to improve customer satisfaction, reduce support costs, and optimize chatbot performance.
Features
- Inferred CSAT: Augments survey CSAT with AI-based analysis of bot and human interactions.
- Bot Optimization: Visualizes user interactions to diagnose breaking points and improve bot containment.
- Agent QA: Scores agents on inferred CSAT, frustration, and policy adherence.
- Voice Analytics: Analyzes voice calls to identify trends and root causes of customer contact patterns.
- Product Optimization: Provides insights into company and product issues to reduce customer support volume.
- Knowledge Optimization: Surfaces actionable root causes behind customer contact patterns.
- Cross-Channel Integration: Integrates data across chat, voice, email, and case management systems.
- Secure and Compliant: SOC2 Type2 and GDPR compliant with PII/PHI redaction.