The test that matters is not fluency. Modern models are all fluent. The test is task completion: did the customer get the answer, get booked, get routed to the right person.
Voice and chat are not the same product
They share a brain and almost nothing else.
| Chat | Voice | |
|---|---|---|
| Latency tolerance | A pause of two seconds is fine | Anything over about a second feels broken |
| Input quality | Clean text | Accents, phone-line compression, background noise |
| Correction | The user can scroll up and rephrase | The user talks over the system |
| Failure mode | Awkward | The caller hangs up |
A chat assistant that works well will not simply become a voice agent by adding speech. Voice is a materially harder engineering problem, and the difficulty is concentrated in latency and speech recognition rather than in the language model.
What separates a deployment that works
Three things, consistently:
- A defined scope. Systems that try to answer everything answer nothing well. The ones that work handle a narrow set of intents completely and hand off cleanly on everything else.
- A real escape hatch. Every conversation needs a route to a human that the customer can trigger, and the system should offer it before the customer gets frustrated rather than after.
- Grounding in your actual data. A model answering from general knowledge will confidently invent your opening hours. Answers need to come from your systems.
The Indian context
Most conversational AI is benchmarked on clean American English. Indian deployments deal with code-switching between Hindi and English inside a single sentence, a wide range of accents, and mobile-network audio. Systems that score well on standard benchmarks routinely underperform here, which is why testing on real recordings from your own customers matters more than any vendor benchmark.
Questions
- Will customers know they are talking to AI?
- They should. Telling callers at the start is both the honest choice and the practical one — expectations set correctly reduce frustration, and disclosure is increasingly expected by regulators.
- What happens when it cannot answer?
- It should hand over to a person with the conversation so far attached, so the customer does not repeat themselves. A system without a clean handover creates more work than it removes.
Wondering whether this applies to your business? That is a thirty-minute call, not a research project.
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