Background
Manual calling processes are slow to scale and often result in inconsistent customer engagement. Businesses needed an intelligent calling system capable of automating both outbound prospecting and inbound customer support, ensuring faster response times and higher lead conversion.
Coaldev developed dual AI-powered call assistants using Vapi.ai and Twilio APIs to manage outbound prospecting calls and inbound reception inquiries. The outbound agent automatically contacts new leads, introduces the product, and syncs interested prospects into the CRM. The inbound assistant handles live calls, answers service-related queries, and books appointments directly on the client’s calendar.
Challenges
Building AI call assistants required creating systems that could handle unpredictable conversations, sync accurately with CRM workflows, and operate reliably across telephony pipelines. The solution had to mimic human responsiveness while maintaining precision in data flow and customer interactions. Below are the primary challenges Coaldev solved while engineering these intelligent voice agents.
Managing conversational variability and accents in AI voice responses.
Ensuring accurate synchronization between telephony and CRM data.
Designing fallback logic for incomplete or ambiguous interactions.
Maintaining consistent response quality across use cases.
Solution
Coaldev tuned Vapi.ai prompts for natural conversation handling, configured fallback logic for missed interactions, and built stable CRM API integrations to eliminate data loss.
Coaldev implemented an integrated voice automation framework that unified conversational AI, telephony, and CRM systems under a single operational flow.
Key solution elements included:
1. Automated CRM Synchronization
Seamless data push and pull between call logs, customer profiles, and lead status ensured a unified system of record.
2. Brilliant Conversation Handling
AI-driven intent recognition and context retention allowed assistants to adapt to caller behavior dynamically.
3. Dual-Agent Architecture
Separate AI agents were deployed for outbound and inbound scenarios, each optimized with purpose-specific prompt engineering and logic flows.
4. Fallback and Recovery Logic
Calls interrupted or flagged for ambiguity were routed to human review or retried automatically within the system.
5. Performance Monitoring
Custom dashboards tracked agent success rates, call durations, and lead outcomes to improve tuning and reliability.
This integrated setup enabled continuous, high-quality conversations while maintaining accuracy and compliance across communication channels.
Results
The AI assistant system transformed how the client handled both lead outreach and inbound communication.
Key outcomes
Automated inbound and outbound calling, reducing manual workload.
Faster response times and improved appointment booking rates.
Seamless CRM synchronization for data tracking and follow-up.
Enhanced scalability and 24/7 communication reliability.
Technology Overview
- AI Calls: Vapi.ai
- Telephony: Twilio API
- Integrations: CRM systems (via APIs & webhooks), Google Sheets
