How to Build an AI Phone Call System [7 Step Guide]

Define business requirements

The first step in building an AI-powered phone call system – for a small business or enterprise alike – is to clearly define the primary objectives of the system. Depending on the business needs and the target audience, the AI voice system could serve various purposes such as:

• Customer service automation: Enhance customer support for inbound phone calls by providing instant responses, as the AI answers common questions, reducing wait times, and improving customer satisfaction.
• Debt collection: Automate debt collection calls to increase efficiency, ensure compliance with regulations, and improve recovery rates while maintaining a human-like interaction.
• Appointment scheduling: Facilitate scheduling appointments for things such as home services, medical consultations, restaurant reservations, or repair services. By ensuring the AI books appointments efficiently, businesses can free up human resources for more complex tasks.
• Sales and marketing: Conduct outbound calls for lead generation, follow-ups, and promotions, leveraging AI to personalize interactions and improve conversion rates.
• Survey and feedback collection: Automate the process of collecting customer feedback and conducting surveys, ensuring a higher response rate and quicker data analysis.

Clearly defining the business requirements will naturally lead into your ability to define more specific, effective software requirements.

Conduct initial feasibility study

Once the business requirements are defined, the next critical step is to conduct an initial feasibility study, which will help your team assess whether it’s worth investing in the project further. Depending on scope of the project and business type, some areas to consider include:

• Integration with existing systems: At this stage it’s important to take stock of what your current tech stack looks like. This will help you to evaluate how feasible (or easy) it will be to integrate the technologies and tools you select in the next step.
• Data requirements: Identify the data needed to train and operate an AI phone call system. Evaluate whether you have access to sufficient, high-quality data, including historical call data and customer information, to effectively train the AI models.
• Staffing and expertise: Determine if your organization has the necessary staffing and expertise to support the development and implementation of the AI phone call system. This includes assessing whether you have skilled personnel in AI, machine learning, data science, and software development. If not - consider outsourcing to AI chatbot developers.
• Compliance with regulations: Ensure that you understand the relevant laws and regulations, such as data privacy laws (e.g., GDPR, CCPA), telemarketing laws, and industry-specific regulations. Assess whether your organization can comply with these regulations throughout the development and operation of the AI system.

Choose the right technologies and tools

Choosing the right technologies and tools is crucial for building an effective AI phone system. Some of the biggest players in this space offer platforms to build AI voice call systems:

• Google Cloud Dialogflow: Provides natural language understanding and can be integrated with various telephony platforms. It simplifies the development process with built-in AI capabilities.
• Amazon Connect: A cloud-based contact center service with AI-driven features. It integrates with AWS Lambda for custom logic and AWS Lex for conversational interfaces.
• Rasa: An open-source framework for building AI assistants, providing extensive customization and flexibility.
• Twilio: A popular choice for integrating AI with telephony. Twilio provides APIs for voice and messaging, making it easier to integrate AI solutions like Google Dialogflow or custom models.

There are also many startups popping up that offer a leaner experience for setting up and configuring AI-powered phone call agents that could be suitable for small to midsize operations, such as:

• Vocode: Simplifies the integration and development of AI phone call systems with high accuracy in NLP and speech recognition, easy integration, extensive customization, and scalability for high call volumes.
• Bland.ai: Offers infrastructure for building AI phone calling applications at scale.
• Air.ai: Touts itself as the world's first ever AI that can have full on 10-40 minute long phone calls, with infinite memory, perfect recall, and can autonomously take actions across 5,000 plus applications

Create first set of sample scripts

After choosing the right technologies and tools, the next step is to create the first set of sample scripts for your AI phone call system. These scripts will form the foundation of how your AI handles live calls. Start by developing scripts tailored to different scenarios your AI phone system will encounter. Flexibility is key; ensure that your scripts can be easily modified based on feedback and performance data.

Common scenarios include:

• Greeting: The initial interaction sets the tone for the entire conversation. Develop a warm and professional greeting script that makes callers feel welcomed and valued.
• Handling objections: Create scripts for managing common objections or concerns that callers might have. This includes preparing responses to questions about product features, pricing, or service issues.
• Closing the call: Ensure you have a clear and effective script for ending the call, whether it’s concluding a customer service interaction, finalizing a sale, or wrapping up a debt collection call.

PRO TIP: To make the conversations more natural and engaging, incorporate an emotional intelligence API, such as Hume. This technology helps the AI recognize and respond to the emotional cues of the caller, making the interaction more human-like.

Develop the MVP admin page

Once you have created the first set of sample scripts, the next step is to develop a Minimum Viable Product (MVP) admin page. This page will serve as the central hub for managing your AI phone call system. Using a framework like Django can facilitate rapid development and ensure a robust and scalable solution. Within an MVP version, you should be able to:

• Upload and manage scripts: The admin page should allow users to upload new scripts and manage existing ones efficiently, providing an interface to view, edit, and organize scripts by categories, ensuring optimal performance during peak business hours.
• Configure AI agent parameters: Administrators should be able to adjust settings related to the AI’s behavior and emotional intelligence, ensuring the AI aligns with the desired interaction style and can handle various scenarios.
• Monitor call activities and results: Include features to track call logs, performance metrics, and real-time monitoring, enabling administrators to assess the AI's performance and intervene if necessary.
• Manage users: Implement a user management system to control access levels, allowing different roles and permissions for team members who will interact with the admin page.

Testing and fine-tuning

After developing the MVP admin page, the next crucial step is testing and fine-tuning your AI phone system. To do this thoughtfully, your team should:

• Collaborate with your business team to iteratively tune the system to ensure it works seamlessly with customers' favorite devices. Regular review sessions with stakeholders will help identify areas for improvement. Adjust scripts, AI parameters, and configurations based on their feedback, ensuring the system aligns with overall business goals.
• Simulate real scenarios with sample data, covering a wide range of interactions such as answering common questions, objections, and complex situations. This helps in realistically testing the AI’s responses and behavior, providing a clear picture of its performance and areas needing refinement.
• Gather feedback from test users through surveys and interviews. This feedback is invaluable for making iterative improvements to scripts, AI parameters, and the user interface.

Monitor, evaluate, and optimize the phone system

After testing and fine-tuning your AI phone call system, it’s essential to ensure its continued effectiveness through ongoing monitoring, evaluation, and optimization. Continuous monitoring involves tracking key metrics such as call completion rates, average handling time, and user satisfaction scores, and setting up alerts for anomalies.

Regular evaluation through user feedback and performance reviews with stakeholders ensures alignment with business goals. Use these insights for ongoing optimization by updating scripts, tuning AI parameters, and adding new features to improve efficiency.

Custom AI Solution Development with Softkraft

If you're looking for a partner to help develop a custom AI phone call or chatbot system, we’d be happy to help! Our team provides a wide range of custom AI development services and will partner with you to build a comprehensive AI strategy. We'll assist in selecting the most suitable AI technologies, seamlessly integrating them into your existing tech stack, and delivering a business-aligned AI voice system that's ready to serve real customers.

Conclusion

Implementing an AI voice system can greatly enhance your business's communication capabilities, driving both efficiency and improved customer interactions. By following these seven steps—from defining business requirements to continuous optimization—you can develop a robust and scalable solution tailored to your specific needs. Thoughtful investment in AI technology not only streamlines your operations but also positions your business as an industry leader, ensuring a superior customer experience and a strategic advantage in the rapidly evolving technological landscape.