Executive Summary for CTOs
Call-Emma.ai is a containerized, cloud-optimized, multi-tenant solution designed to process call center audio recordings and generate AI-powered insights that optimize call center operations. As a self-hosted addon, Call-Emma.ai integrates with your existing call center software through RESTful APIs, where audio files and job details are submitted, and AI-generated insights are returned via JSON or a structured database entries and HTML reports.
What It Is
- Containerized application fully compatible with cloud platforms (AWS, Azure, Google Cloud, and on-premise).
- API based solution design to integrate with existing call center software - see the System Overview for technical architecture details.
- Self-hosted the deployment on your infrastructure for complete data control.
AI Use Cases
- Pre-configured AI prompts ability to enter custom AI prompts.
- Quality assurance, compliance monitoring, agent coaching, and call analytics.
- Actionable insights from day one with full customization options - explore the complete list of AI use cases below.
Security & Compliance
- Runs on your cloud infrastructure for complete data and security control.
- Automated PII removal capabilities with comprehensive audit logging.
- Give your company the ability to automate Regulatory compliance checks..
- See Configuration Options for security settings.
Enterprise Scale
- Enables Automatic load-based scaling.
- Robust multi-tenant architecture with full tenant isolation.
- Enterprise-grade job queuing with intelligent error handling and recovery.
- Learn more about platform capabilities on the Features page.
Flexible Configuration
- Highly configurable deployments optimized for quality vs. cost tradeoffs.
- AI inference options: local on-instance (maximum privacy) or external API providers for optimal performance and cost operations.
- Supported providers: AWS Bedrock, Groq.com, Anthropic, OpenAI, or self-hosted LLM via Ollama.
- Review detailed Configuration Options.
Transparent Licensing
- Reasonable licensing rates with flexible deployment options.
- View Licensing Options and Cost Examples.
AI Use Cases
Discover the powerful AI capabilities built into the Call-Emma.ai solution, designed to add high value AI analysis and insights into your call center software solution. This list of AI use cases (below) showcases high value implementations of AI that deliver substantial business value. The Call-Emma.ai solution is also highly flexible—we can create custom AI prompting tailored to your specific business needs, ensuring the platform works exactly the way you want it to.
The 7 categories of use cases below are further broken down into a total 27 specific use cases.
Call Details
Call Details AI provides organized, actionable summaries of each call including objectives, agent actions, and outstanding tasks for efficient follow-up and quality control.
Call Categorization & Tagging
AI categorization automatically identifies call topics, classifies customer types, and tracks mentions of specific products or services discussed during conversations.
Quality Control
AI quality control monitors agent behavior, flags detrimental actions, and provides automated oversight for performance management.
Agent Performance Analysis
AI grades agent performance across key metrics: product knowledge, professionalism, active listening, problem-solving, and efficiency.
Compliance
AI monitors and confirms agent adherence to compliance policies and procedures throughout each call.
Agent Coaching
AI analyzes agent performance to recommend personalized coaching and training opportunities based on identified skill gaps.
Chat with Data
ChatGPT-style interface allows supervisors and managers to query AI results, identify statistical patterns, flag outliers, filter problematic calls, and generate custom graphs and visualizations.
Use Cases Powered by AI
Call Details Powered by AI
1. Call Summary
By providing high-quality, comprehensive AI-generated call summaries that minimize the time agents spend reviewing prior notes, callers experience shorter initial hold times and smoother interactions, while the company benefits from reduced overall call durations and the elimination of error-prone handwritten agent notes.
2. Satisfaction of the Customer's Objectives
The AI extracts the caller's objectives and then determines whether the agent fulfilled each one. This dramatically improves the supervisor's ability to provide quality control and reduces review time to seconds, compared to the old method of listening to an entire call.
3. Agent's Actions
The AI extracts all the actions taken by the agent and lists them, making it easy for supervisors to review what occurred, again saving them from having to listen to the call.
4. Agent's Post-Call Task List
The AI summarizes any tasks the agent mentioned they would complete, reducing post-call note-taking, assisting other agents with follow-up, and enabling task list automation.
5. Customer's Post-Call Task List
The AI summarizes any tasks the customer agreed to or was advised to complete, reducing agent note-taking and enabling automated follow-up communication on required actions.
Categorization & Tagging Powered by AI
6. Call Category
The AI analyzes the entire call and assigns it to one or more categories such as Sales, Support, or Billing, improving accuracy and helping management track call volumes without relying on manual agent input.
7. Topic or Keyword Tagging
The AI understands broad concepts and word variations for more accurate categorization based on topics or keyword tagging, enabling more accurate analytics, and saving the agent time in post call note taking.
8. Customer Categorization
The AI categorizes customers based on attributes such as service tier or membership status stated by the agent, enabling targeted analytics and quality control for high-priority customers.
9. Product or Service Tagging
The AI analyzes the conversation and tags it based on products or services mentioned, enabling more accurate analytics and providing valuable insights for operations and marketing.
Quality Control Powered by AI
10. Agent Behavior Monitoring
The AI reviews conversations for poor agent behavior, such as rudeness or failure to escalate, and tags them for supervisor review. This enhances oversight and promotes better agent conduct.
11. Unwanted Disconnection Detection
The AI detects unwanted disconnections, such as agents hanging up without cause or ending calls abruptly, and tags them for supervisor review. This improves oversight and reduces negative customer experiences.
12. Excessive Hold Time Monitoring
The AI detects excessive hold times during calls and tags them for supervisor review. This helps identify process inefficiencies and improves the overall customer experience.
13. Unnecessary Transfer Detection
The AI identifies instances where an agent transfers a customer despite having the ability to resolve the issue themselves. This helps reduce call handling inefficiencies and improves first-contact resolution.
14. Escalation Request Detection
The AI detects when a customer requests to speak with a supervisor or escalate an issue, tagging the call for review. This ensures proper handling of escalations and highlights potential service gaps.
Call Center Agent Performance Analysis Powered by AI
15. Product Knowledge Assessment
The AI evaluates how well the agent explains products and services, highlighting knowledge gaps and grading performance to help supervisors improve training and ensure consistent service.
16. Professionalism Assessment
The AI evaluates the agent's tone, attitude, and adherence to conduct standards, identifying unprofessional behavior and helping supervisors ensure a respectful and consistent customer experience.
17. Active Listening Assessment
The AI assesses how well the agent listens and responds to customer needs, detecting interruptions, missed questions, or off-topic replies to support better engagement and issue resolution.
18. Problem Solving
The AI evaluates the agent's ability to understand the issue, provide accurate solutions, and guide the customer effectively, helping identify strengths and gaps in resolution skills.
19. Call Efficiency Assessment
The AI measures how effectively the agent manages the call by analyzing pacing, unnecessary delays, and resolution time, helping improve productivity and reduce average handle time.
Call Compliance Powered by AI
20. Required Disclosures Assessment
The AI checks whether the agent reads all mandatory disclosures accurately, helping ensure compliance with legal and regulatory requirements.
21. Consent Capture Assessment
The AI monitors whether the agent properly obtains and records customer consent for services, charges, or communications, ensuring compliance with legal and regulatory requirements.
22. Authentication Assessment
The AI evaluates whether the agent follows proper identity verification procedures before sharing account information, helping ensure compliance and protect customer data.
Call Center Agent Coaching Powered by AI
23. AI-Driven Skill-Based Agent Coaching
The AI reviews scores from assessments of product knowledge, professionalism, active listening, problem solving, and call efficiency, then assigns targeted coaching or training modules to address specific skill gaps and improve overall agent performance.
Chat with the Data (Future Features)
24. Cross-Call Statistics
The AI allows supervisors to interact with call data through chat, generating cross-call statistics such as the percentage of last week's calls from Platinum members related to customer support. It guides supervisors in creating insights, offering powerful analytical capabilities with minimal effort, this applies to all the data from the above uses cases.
25. High or Low Outliers
The AI allows supervisors to interact with call data through chat to identify statistical outliers, such as unusually long calls, low professionalism scores, or spikes in specific issues. It applies this analysis across all use cases, helping surface trends or anomalies that warrant attention.
26. Results Filtering
The AI enables supervisors to search and analyze call data across custom time frames, departments, agent groups, or individual agents, making it easy to spot trends, compare performance, and track progress over time.
27. Graphs and Visualizations
The AI generates clear graphs and visualizations from call data, making it easy for supervisors to understand performance trends, compare metrics, and communicate insights effectively.