Build and deploy a scalable AI interviewer using Tavus to automate candidate screening, streamline hiring, and deliver actionable insights with step-by-step technical guidance.
Technical prerequisites and requirements
Before you start building your AI interviewer, make sure your technical environment is ready and you have all the resources you need. This preparation helps you integrate and operate Tavus smoothly.
To begin, sign up for a Tavus account with API access at the Tavus Developer Portal. Once registered, generate your API key from your Tavus dashboard—this key is essential for all API interactions. Next, provision enough cloud storage and processing power for video files, especially if you plan to connect Tavus with your existing infrastructure. This step ensures your system can manage the data load efficiently.
It's also important to comply with data privacy and security standards like GDPR and CCPA to protect candidate information and maintain trust. Finally, confirm you have access to your ATS or HRIS, or the ability to import candidate and job data via CSV or API. Seamless integration at these points is vital for efficient data flow and operations.
Phase 1: Defining the AI interviewer use case and business value
Before you dive into the technical build, take time to define your business objectives and the specific requirements for your AI interviewer. This step ensures your goals align with the technology's capabilities.
Identifying core use cases and stakeholders
Start by outlining the interview scenarios you want to automate. These might include high-volume candidate screenings, technical assessments, or asynchronous interviews. For example, automating first-round screenings can significantly reduce HR workload and speed up hiring.
Identify and prioritize which interviews to automate, focusing on scenarios like first-round screenings or technical case interviews that benefit most from automation. Engage stakeholders—including HR, recruiters, IT, and compliance teams—early in the process. Their input helps you address potential challenges from multiple perspectives.
For each scenario, document the expected interview volume, candidate demographics, and key assessment criteria. This detailed documentation guides how you configure your AI interviewer and ensures it meets your needs.
Tavus supports both asynchronous and live conversational interviews through its Conversational Video Interface (CVI). For structured, repeatable interviews, use the predefined AI Interviewer persona. For more details, check out the AI Interviewer documentation.
Mapping business value and success metrics
Define what success means for your AI interviewer project. Common KPIs include reducing time-to-hire, improving candidate quality, ensuring unbiased and explainable assessments, and achieving high candidate satisfaction scores.
Align these KPIs with Tavus analytics endpoints for automated tracking. Tavus offers robust analytics and reporting APIs so you can monitor interview throughput, scoring, and candidate experience. Make sure your chosen metrics match available Tavus data fields for seamless integration.
Selecting interview modalities and languages
Decide which interview formats and languages you need to support your candidate pool. Consider whether you'll use one-way video, live conversational, or voice-based interviews, depending on your requirements. Assess the languages spoken by your candidates to ensure accessibility and inclusivity.
Tavus supports multilingual interviews and can be configured for both synchronous and asynchronous flows. For more details, refer to Language Support.
Phase 2: Preparing the technical environment and prerequisites
In this phase, you'll set up your infrastructure and gather the resources needed to integrate Tavus AI interviewer capabilities effectively.
Technical requirements and account setup
Start by generating your API key. Log in to the Tavus Developer Portal, navigate to the API Keys section, and create a new key.
Next, test your API access to ensure everything is working. Use the following command:
curl --request GET \
--url https://tavusapi.com/v2/ping \
--header 'x-api-key: <your_api_key>'Replace <your_api_key> with your actual key.
All API requests must include the x-api-key header. Keep your API key secure and restrict access according to your organization’s security policies.
Candidate data integration and job description ingestion
Integrate your ATS or HRIS, or import candidate and job data via CSV or API. This integration lets Tavus ingest job descriptions and candidate profiles, enabling dynamic, role-specific interview question generation. Make sure your data pipeline supports real-time or batch updates as needed for smooth operations.
Configuring video and audio infrastructure
Set up video endpoints for candidate interviews and ensure compatibility across browsers and devices. Tavus supports all major browsers and devices, and integrating Tavus SDKs for video recording and playback is essential. Tavus CVI uses advanced speech-to-text (STT) and text-to-speech (TTS) engines for real-time conversation. Test candidate devices for camera and microphone access, as well as browser support. For technical requirements, consult the Tavus documentation.
Phase 3: Building and configuring the AI interviewer workflow
Now, focus on implementing the core workflow—question generation, interview orchestration, and candidate interaction.
Automated interview question generation
Use Tavus generative AI to create role-specific, unbiased, and dynamic interview questions. By providing job descriptions and required competencies as input to the API, you ensure questions are tailored to each role.
The AI Interviewer persona is preconfigured for structured, conversational case interviews. To start a new interview conversation, use this API call:
curl --request POST \
--url https://tavusapi.com/v2/conversations \
--header 'Content-Type: application/json' \
--header 'x-api-key: <api_key>' \
--data '{
"persona_id": "pe13ed370726"
}'Replace <api_key> with your actual API key. The persona ID for the AI Interviewer is pe13ed370726.
You can customize or override question sets by providing extra context or fallback questions in your API request. The persona’s system prompt ensures questions remain unbiased and conversational.
Designing the conversational flow and candidate experience
Leverage Tavus AI human avatars to deliver questions and respond to candidate answers, creating a more engaging and interactive experience. Configure the interview structure to include an introduction, background questions, case studies, follow-ups, and a wrap-up.
The AI Interviewer persona (Mary) is optimized for first-round case interviews. She provides a friendly greeting, a structured conversational flow, and real-time perception and feedback.
The Tavus conversational pipeline includes several layers. The perception layer monitors candidate behavior for signs like distraction or nervousness. The STT layer uses the tavus-advanced engine with smart turn detection. The LLM layer generates dynamic, context-aware questions and responses, while the TTS layer delivers spoken responses in a natural, human-like voice.
When you create a conversation, the API returns a response like this:
{
"conversation_id": "cae87c605c7e347d",
"conversation_name": "New Conversation 1751877296483",
"conversation_url": "<conversation_link>",
"status": "active"
}Share the conversation_url with candidates so they can access their interview.
Setting up multilingual and accessibility features
Enable Tavus multilingual support as needed, and configure subtitles, alternative input methods, and accessibility settings. Tavus can auto-detect or be set for specific languages. You can enable accessibility options, such as subtitles and alternative inputs, through the Tavus platform or API parameters.
Phase 4: Integrating scoring, analytics, and shortlisting
Automate candidate scoring, integrate analytics, and streamline your hiring pipeline to make better decisions and improve efficiency.
AI-powered candidate scoring and bias mitigation
Activate Tavus explainable AI scoring for technical, soft, and psychological skills. Set up bias audits and objective criteria for each interview question to ensure fairness and transparency.
Tavus’s explainable AI pipeline manages scoring. The perception model (raven-0) monitors visual cues like distraction or nervousness, and scoring outputs are available via API or webhooks. For more information, see the Explainable AI docs.
It's best not to share assessment results directly with candidates. Instead, redirect them to your formal process. Use Tavus’s perception and scoring layers to maintain objective, unbiased evaluation.
Insights, analytics, and reporting integration
Connect Tavus analytics endpoints to your dashboards or ATS for real-time and post-interview reporting. You can access video recordings, scoring breakdowns, and trust or cheating detection. Tavus webhooks let you receive interview completion events and scoring data, while API endpoints allow you to integrate analytics with your reporting tools.
Ensure your system can handle webhook callbacks and securely store or report candidate data. Tavus provides detailed breakdowns of candidate performance, including perception-based insights.
Automated shortlisting and workflow automation
Set up rules to auto-shortlist top candidates based on Tavus scoring. Integrate with your ATS or trigger downstream workflows—such as scheduling or recruiter notifications—using the Tavus API or Zapier.
You can use the Tavus API to update candidate status or trigger next steps in your hiring process. Automate notifications and scheduling based on interview outcomes to keep your recruitment pipeline moving efficiently.
Phase 5: Embedding the AI interviewer in your hiring ecosystem
Integrate your AI interviewer with your existing HR technology and optimize the candidate journey for a seamless recruitment process.
ATS/HRIS and calendar integration
Connect Tavus with your ATS, such as Greenhouse or Workday, using available integrations or custom API connectors. Integrate with calendar tools to automate scheduling and feedback loops.
Use Tavus API endpoints to sync candidate and interview data. Make sure your ATS or HRIS supports webhook or API-based integration for real-time updates.
Candidate engagement and communication channels
Set up automated candidate outreach through email, SMS, or WhatsApp using Tavus communication APIs. Personalize your messaging to boost engagement and reduce drop-off rates.
Tavus communication APIs let you send interview invitations and reminders. Track engagement metrics and refine your messaging to increase completion rates.
Security, compliance, and data privacy
Implement GDPR and CCPA-compliant data flows to protect candidate information. Use Tavus security features for video storage, access control, and consent management.
Tavus provides secure video storage and access controls. Always capture and store candidate consent as part of your workflow to maintain compliance.
Phase 6: Testing, optimization, and best practices
Validate your implementation, monitor performance, and iterate for ongoing improvement to keep your AI interviewer effective and efficient.
End-to-end testing and user acceptance
Conduct dry runs with internal users and sample candidates to check video and audio quality, scoring accuracy, and candidate experience. Use Tavus test personas and sandbox environments for safe testing. Monitor logs and API responses for errors or anomalies to ensure everything works as expected.
Monitoring, feedback, and continuous improvement
Set up monitoring for system health, candidate satisfaction, and hiring outcomes. Use feedback loops to refine your question sets, scoring models, and workflow automation.
Tavus provides analytics and monitoring endpoints for ongoing performance tracking. Regularly review candidate feedback and scoring data to improve your AI interviewer and keep it aligned with your goals.
Common implementation patterns and troubleshooting
Document reusable patterns, such as high-volume campus hiring or multilingual roles, to streamline future deployments. Address common issues like candidate device compatibility or API rate limits by providing clear solutions.
For advanced help, reference Tavus Troubleshooting and the Support Center. Monitor API usage and rate limits to avoid service interruptions and maintain a smooth candidate experience.
Deploy your Tavus-powered AI interviewer by following these phases. As you refine your workflow, automate shortlisting, and integrate analytics, you'll transform your recruitment process. Start testing with real candidates, monitor results, and keep iterating for continuous improvement.
References: - Tavus AI Interviewer documentation - Tavus API Reference - Explainable AI docs
For further support, visit the Tavus Help Center or reach out to your technical account manager.
