Conversational agent
AI-Powered Call Center Assistant
AI-first call center with realtime voice agents that answer immediately, grounded in approved knowledge, and hand off smoothly to humans.
Powered by ARIA
Business value
Delivers faster first response, more consistent service quality, and better peak-volume coverage while freeing human agents to focus on sensitive or high-value conversations.
Contact centers face high call volumes, long wait times, and service quality that varies across shifts and languages. ARIA is an MII-built capability pattern that runs the live conversational turn on a single realtime speech model instead of chaining separate recognition, reasoning, and synthesis stages, which keeps the conversation responsive and natural. Answers are grounded in approved customer knowledge through retrieval exposed as a callable tool, and when retrieval confidence is low or a case needs human judgment, an operator joins the existing call with full context preserved rather than routing the caller back to a queue. ARIA is built on Azure OpenAI Service, Azure Speech, Microsoft Foundry, Azure Communication Service, and Azure AI Search.
Where it helps
- Answering routine customer inquiries immediately in Bahasa Indonesia or English
- Routing complex cases to human operators without losing conversational context
- Capturing interaction details as structured data for follow-up and reporting
What the pattern does
- Realtime speech-to-speech agent with natural conversational pauses
- Retrieval-grounded answers backed by approved customer knowledge
- Seamless human handoff within the same call session
The challenge
Contact centers face high call volumes, long wait times, limited after-hours coverage, and service quality that varies across shifts, languages, and agent availability. Routine questions consume human capacity while complex cases still need empathy and judgment.
What was built
ARIA runs the live turn on a single speech-to-speech realtime model instead of chaining separate recognition, reasoning, and synthesis stages, removing the pipeline hops that add conversational delay. Retrieval is exposed to the model as a callable tool, so answers are pulled from approved customer knowledge on demand with provenance attached rather than stuffed into a static prompt. When retrieval confidence is insufficient or the case calls for judgment, the platform brings a human operator into the existing call with full context preserved.
What changed
A voice agent that picks up immediately, answers from approved knowledge with sources attached, records conversation context, captures follow-up details, and hands the operator a fully contextualised call when a case must be escalated.
Why it matters
Faster first response, more consistent service quality, better peak-volume coverage, richer call records, and human agents freed to focus on sensitive or high-value conversations.
- Human handoff without re-queuing
- Same-session
- Single realtime model, no ASR-TTS chain
- Speech-to-speech
- Answers cited from customer knowledge
- Grounded RAG