Case: Telephony Dashboard with AI Analysis

Corporate web solutions with integrated analytics

I am a developer. In this case study, I demonstrate how we built a telephony dashboard with speech recognition and analytics based on call recordings — with a focus on quality, security, and operations.

Practical case: call center and sales department

• Initial data: call records from the PBX, requirement to store on own servers, need for fast reports on topics and quality.
• Implementation: audio export via API, transcription, semantic conversation tagging, dashboard with filters and access roles.
• Operation: structured logs, metrics for processing time/queues, updates with zero downtime.

Quick immersion into context

• Conversations with responsible persons: objectives (quality/training/scripts), KPIs (response time, satisfaction), terminology.
• Subject area: types of calls, markers of successful/problematic calls; risks and assumptions.
• Integrations: audio sources, latency and availability requirements, system owners.

Architectural decisions and trade-offs

• Streaming or batch processing: latency versus cost.
• Voice Activity Detection (VAD), diarization, punctuation restoration — as per scripts.
• Queues/cache for load retention, retry with pause on failures.

Hidden pitfalls and anti-patterns

• Noise, parallel speech — configuration of recognition and filtering parameters.
• Specific terms — vocabulary/model adaptation and post-processing.
• Long processing queues — backlog control, limits, and task prioritization.

Quality, metrics, and operations

• SLI/SLO: p95 latency, error budget, uptime; SLO alerts
• Test Strategy: unit/contract/E2E, load testing, canary releases.
• Observability: structured logs, tracing, metrics
• CI/CD, migrations, rollbacks, health checks, and readiness probes

Security and Data

• PII/secrets: encryption at rest/in transit, key rotation
• Roles and access, log masking, action auditing
• Storage policies, TTL, regional requirements

Your virtual PBX is not just a communication tool, but a goldmine of data about your customers, service quality, and sales effectiveness. But how do you extract useful insights from hundreds of hours of call recordings? I propose the development of a custom web dashboard for telephony analysis, which will use AI to transform your calls into clear and visual analytics.

Market Analysis: Why Are Standard Call Center Reports Just the Tip of the Iceberg?

• Surface-level metrics: Standard reports only show the number and duration of calls, but not their content.
• Security issues: Storing call recordings in the cloud of the PBX provider does not always meet security requirements and personal data legislation.
• Lack of in-depth analysis: You don't know what problems clients most frequently present with, which sales scripts work best, and which operators require additional training.

The technological capabilities of my solution

Our dashboard is your own analytics lab, operating on your servers and by your rules.

Key capabilities:

• 🎯 Secure storage: All call recordings are exported via API from your PBX (e.g., Asterisk) and stored on your server, ensuring full control and data security.
• 🗣️ Speech transcription: The neural network automatically transcribes all conversations into text with high accuracy.
• 📱 Semantic analysis: AI analyzes the content of conversations, determining the purpose of the call, the customer's mood, and the mention of key words (e.g., "problem," "competitor," "
• 📚 Flexible authorization: I can configure the authentication system via Google Sheets or any other system of yours to provide different groups of employees with access to the dashboard.
• 🎵 Data visualization: All analytics are presented in the form of clear, real-time graphs and charts.

Business Potential: Who is this solution for?

• Call centers: Evaluate operator performance, monitor service quality, and identify areas for improvement.
• Sales departments: Analyze sales scripts, identify best practices, and train newcomers using real-life examples.
• Quality departments: Automatically identify problematic calls and work on improving the customer experience.

Technical implementation

• Backend: Python (Flask) / Node.js.
• Frontend: React/Vue.js.
• AI: Speech-to-Text (Whisper API), Text analysis (OpenAI/Claude).
• Integrations: Any virtual PBX with an API.

Evidence of effectiveness

• Improving service quality: Reduction in the number of negative calls by 30-50%.
• Sales growth: A 15-20% increase in conversion through script optimization.
• Time saving: Reduction of time spent on manual call listening by 90%.

I am ready to develop an analytical dashboard for you that will become your primary decision-making tool.

• ✅ You will receive a system fully integrated with your PBX.
• ✅ All data will be stored on your servers.
• ✅ We will configure dashboards and reports according to your KPIs.
• ✅ We will provide full technical support and training.

Telegram: @sashanoxon
Email: [email protected]

Want the same result? Submit a request — let's discuss your task.