Bilingual AI Phone Support Agent
Budget: $750 – $1,500 USD
I’m building a 24/7 voice-based, first-level technical support line for my IoT product and I want the experience to feel completely human. When a customer in India rings our toll-free 1800 number, the agent must:
• Answer naturally in either English or Hindi, switching seamlessly when the caller does.
• Identify the customer’s issue through free-form conversation, guided probing, or a predefined question flow.
• Consult a pre-built knowledge-base (I’ll supply the content) and return the most relevant fix or troubleshooting steps in real time.
• Decide—based on confidence and predefined rules—whether to:
– resolve the case on the call,
– create and email/SMS a ticket automatically, or
– warm-transfer the caller to a live engineer with full context.
Technical expectations
• Python-based solution so my team can extend it.
• Integrates with a standard SIP trunk or Twilio-like voice API to sit behind our 1800 number.
• Uses reliable ASR, NLU, and TTS to keep latency low and speech lifelike.
• Modular workflow engine where I can tweak intents, responses, and escalation logic without touching core code.
• Logs every interaction (audio + transcript) and pushes summaries to our existing ticket system (REST API available).
Deliverables
1. Working voice agent running in a staging environment.
2. Clean, commented Python code with virtual-env or Docker setup.
3. Documentation covering deployment, knowledge-base updates, and escalation rule edits.
4. One round of post-deployment tuning after a week of live traffic.
If you’ve built conversational IVRs, voice bots, or Twilio Flex/Voiceflow/Dialogflow CX projects, I’d love to see examples. Let’s bring a human touch to automated tech support together.
• Answer naturally in either English or Hindi, switching seamlessly when the caller does.
• Identify the customer’s issue through free-form conversation, guided probing, or a predefined question flow.
• Consult a pre-built knowledge-base (I’ll supply the content) and return the most relevant fix or troubleshooting steps in real time.
• Decide—based on confidence and predefined rules—whether to:
– resolve the case on the call,
– create and email/SMS a ticket automatically, or
– warm-transfer the caller to a live engineer with full context.
Technical expectations
• Python-based solution so my team can extend it.
• Integrates with a standard SIP trunk or Twilio-like voice API to sit behind our 1800 number.
• Uses reliable ASR, NLU, and TTS to keep latency low and speech lifelike.
• Modular workflow engine where I can tweak intents, responses, and escalation logic without touching core code.
• Logs every interaction (audio + transcript) and pushes summaries to our existing ticket system (REST API available).
Deliverables
1. Working voice agent running in a staging environment.
2. Clean, commented Python code with virtual-env or Docker setup.
3. Documentation covering deployment, knowledge-base updates, and escalation rule edits.
4. One round of post-deployment tuning after a week of live traffic.
If you’ve built conversational IVRs, voice bots, or Twilio Flex/Voiceflow/Dialogflow CX projects, I’d love to see examples. Let’s bring a human touch to automated tech support together.