Both are conversational AI. But the moment you pick voice, the entire engineering, UX and cost equation changes. Here's how to decide.
Use a chatbot when users are on a screen and value speed, precision and history. Use a voice agent when hands, eyes or literacy are constraints — or when a phone call is the natural channel.
AI chatbots run on text — in-app, on your website, on WhatsApp, inside Slack or Teams. They excel at multi-turn Q&A, structured workflows and situations where the user can read, scroll and share links.
Voice agents run on speech — inbound and outbound calls, in-app voice, IVR replacement, kiosks and vehicles. They shine when the user can't or won't type: field workers, drivers, elderly customers, high-volume support, regional-language markets.
The engineering isn't just a swap. Voice adds real-time speech-to-text, natural TTS, barge-in handling, sub-second latency budgets and telephony integration — with a much less forgiving UX.
Text-based conversational interface that lives in web, mobile or messaging channels.
Speech-driven agent that handles inbound/outbound calls or in-app voice with natural, low-latency conversation.
| Criterion | AI chatbot | Voice agent |
|---|---|---|
| Channel | Web, app, WhatsApp, Slack | Phone, IVR, in-app voice, kiosk |
| Cost per interaction | Very low | Moderate to high |
| Latency budget | 1–3 seconds | Under 800ms per turn |
| Best user segments | Digital-native, literate | Field, elderly, regional-language |
| Rich media | Native support | Not applicable |
| Setup complexity | Low to moderate | Moderate to high |
| ROI driver | Deflection, self-serve | Call automation, outbound scale |
In most enterprises, chat and voice aren't either/or — they share the same knowledge base, guardrails and integrations, and hand off to each other. T7 Solution builds unified conversational platforms with one brain and multiple channels.
Custom AI chatbots trained on your data — web, WhatsApp, Slack and beyond.
Explore serviceHuman-sounding AI voice agents for inbound and outbound calls at scale.
Explore serviceProduction-grade GPT, Claude, Gemini and open-source LLMs — grounded in your data.
Explore serviceThe intents, knowledge base and tool integrations transfer well. The dialogue design, prompts and error handling usually need a rewrite for voice's tighter latency and no-scroll UX.
Typical enterprise voice stacks land in the $0.05–$0.20 per minute range depending on LLM, STT, TTS and telephony choices. Volume discounts and open-source components can push this lower.
For inbound web leads, chat wins on cost and speed. For outbound calls at scale — insurance, real estate, education — voice agents can outperform human tele-callers on consistency and coverage.
Yes. Modern voice stacks handle Hindi, Gujarati, Marathi, Tamil, Arabic and English code-mixing at production quality.
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