Roleplay is the best way to practise a sales call, and the hardest to get. Colleagues are busy, and they're too polite. We wanted an AI buyer that behaves like a real prospect, so we built Maya at Kulissa.
The hard parts
1. Interruptions. Real buyers cut you off. A voice agent that waits politely for you to finish feels fake. Our realtime stack runs on ElevenLabs and Google voice models and lets the buyer barge in mid-sentence, with turn-taking tuned so it doesn't trample you on every pause.
2. Personas that push back. LLMs want to agree with you. We harness the model with persona state, such as budget, priorities, patience and hidden objections, so the buyer holds a position and only moves when you earn it.
3. Latency. Anything much slower than human response time breaks the illusion. A lot of our engineering goes into keeping the round trip short enough that it feels like a conversation.
4. Scoring with receipts. A bare score out of 10 teaches nothing. Every score Maya gives quotes the transcript moment it's based on, so the rep sees exactly what to change. That also makes the evaluator auditable, and we can test it like any other model.
Try it
Maya is free to try at https://kulissa.com/maya. We'd love feedback from devs who've built voice agents, especially on barge-in handling and evaluating LLM judges.
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