If you run a call center, you've probably had two very different sales pitches in the same week. One promises to make your agents easier to understand and less fatigued on the phone. The other promises to answer the call without an agent at all. Both are labelled "AI for call centers," so they get thrown into the same comparison. That's where buyers make expensive mistakes. They're not competitors. They sit at different points in the call and choosing between them starts with one question: do you want to help the human on the line, or replace the reason the call reached a human?
What Sanas- and Krisp-style tools actually do
These are agent-assist tools. They sit on the human agent's side of a live call and improve it in real time. In the category you'll find two flavours:
- Accent and speech clarity (the Sanas category): real-time accent softening/translation so a caller and an agent from different regions understand each other more easily. The human agent is still doing the work; the tool smooths the audio.
- Noise cancellation and call assist (the Krisp category): stripping background noise both ways, plus assist features like live transcription and post-call notes. Again, the human agent runs the conversation; the tool cleans up the channel and reduces the admin around it.
This is genuinely valuable. If your problem is "our agents are hard to understand," "our floor is noisy," or "agents burn time on after-call notes," these tools target exactly that and they do it without re-architecting anything. They make an existing human process better. What they don't do is take a call off your team's plate.
What a custom AI voice agent does
A voice agent isn't on the agent's side of the call; it is the agent for that call. A caller dials in, and for in-scope queries the agent handles the whole conversation: understands the request, looks up the answer in your live systems, responds and resolves with no human involved. When something falls outside its scope, it escalates cleanly to a person with the context attached.
So the value isn't "shorter, cleaner calls." It's fewer calls reaching humans at all. Your team stops answering the same status-check and booking questions all day and handles only what actually needs judgement. That's a different lever entirely: capacity, not polish.
The one-line distinction
Agent-assist tools make each human-handled call better. A voice agent means the call was never human-handled in the first place. You can and often should run both, on different slices of your call volume.
Side by side
| Sanas / Krisp-style tools | Custom AI voice agent | |
|---|---|---|
| Who's on the call | Your human agent | The AI (with human escalation) |
| Core job | Improve the live human call | Resolve the call without a human |
| Effect on headcount | Same team, more effective | Same team absorbs more volume |
| Setup | Install on the agent workflow | Build: flows, integrations, guardrails |
| Needs your systems | No, it's audio-layer | Yes, it answers from your live data |
| Best when | Calls must stay human, but clearer | High volume of repetitive, answerable calls |
How to choose by what you're actually trying to fix
Map your goal to the tool, not the other way around:
- "Callers struggle to understand our agents." That's an accent/clarity problem. A real-time accent neutralization tool such as Sanas or our own Toniq fixes it directly. A voice agent is the wrong instrument.
- "Our floor is noisy and agents waste time on notes." Krisp-style noise cancellation and call assist. Keep your humans; make their environment better.
- "We're drowning in repetitive calls: status, booking, balance, hours." This is the voice agent's home turf. Deflect those calls entirely and let your team handle the rest.
- "We can't hire fast enough to keep up with volume." Agent-assist makes each hire more productive; a voice agent removes the volume that needed the hire. At real scale, the second lever is far larger.
Where each approach hits its ceiling
Neither option is magic and knowing the ceiling of each keeps you from buying the wrong thing for the right reason.
Agent-assist tools stay bounded by headcount. They make every human agent more effective, but you still need a human on every call. If your call volume grows faster than you can hire, the usual situation for a scaling support operation, a clarity or noise-cancellation tool improves each call while the queue keeps getting longer. It raises the ceiling; it doesn't remove it. And because these tools operate on the audio layer, they can't touch the actual reason people call: they don't know your order status, your availability, or your account data, so they can't shorten a call by answering faster; they can only make the human handling it clearer.
Voice agents are bounded by scope and integration. A voice agent only deflects the calls it can genuinely resolve and it can only resolve what it can reach in your systems. Point one at vague, emotional, or contractual conversations and it will (correctly) escalate most of them, which is safe but not a saving. The wins come from a well-defined band of repetitive, answerable, high-volume queries. That's why the honest first step is auditing your call mix: if 60% of your calls are "where's my order" and "what are your hours," a voice agent is transformative; if they're all bespoke negotiations, it isn't. Deflection scales beautifully, but only across the calls that were deflectable to begin with.
If the accent layer is what you need: meet Toniq
For a long time our answer to "callers struggle to understand our agents" was simply "buy a Sanas-style tool." Now we have a more direct one: Toniq, our own real-time accent neutralization software for call center and BPO agents. It does real-time accent translation on the agent's side of a live call, neutralizing the accent so the caller hears natural US/UK-sounding speech while the agent's own voice, cadence and warmth stay intact.
- Sub-second latency (~640ms), on the workstation. Accent conversion happens live, mid-call, on the agent's own machine with no server changes and no telephony re-architecture.
- Plug-and-play with your dialer. It behaves like a microphone, so it works with Zoom, Teams, Genesys, Five9, Ameyo, or any softphone your contact center already runs. Zero agent training, zero behaviour change.
- Measured on the metrics you already track. The case for accent neutralization software is higher right-party contact rates, better conversion per RPC, more first-call resolution, lower average handle time and CSAT that stops paying the "comprehension tax."
- Priced for Indian BPO economics. US-built accent tools run $40 to $60 per user per month; Toniq is built and priced for Indian outbound floors calling into the US and UK.
Everything in this article's framework still applies: Toniq is agent-assist. It makes the human-handled call better; it doesn't deflect the call. Which is exactly why we ship both layers.
Why "both" is often the right answer
These layer cleanly. A mature setup deflects the repetitive, in-scope calls with a voice agent and runs agent-assist on the calls that do reach a human: the complex, emotional, judgement-heavy ones where a clearer, less-fatigued human agent matters most. You get the capacity win from deflection and the quality win from assist, applied to exactly the calls each is good for.
A note on doing this well
The reason to build a voice agent, rather than bolt one onto an off-the-shelf platform, is that its value comes from answering out of your live systems with your escalation rules. That's exactly the architecture we describe in our Battery Smart build, where in-scope driver calls resolve with zero human handoff.
The bottom line
Don't pick between a voice agent and a Sanas/Krisp-style tool as if they compete. Decide which problem you have. If the call must stay human but needs to be clearer or cleaner, buy agent-assist. If the call is repetitive and answerable, build a voice agent and take it off your team entirely. Most call centers at scale end up wanting both, pointed at different traffic.
We build both layers. The accent side is Toniq, our real-time accent neutralization app for BPOs. Building the deflection layer is what we do on our AI voice agents service, often alongside AI workflow automation for the back-office follow-ups a resolved call triggers. If you're weighing custom against buying a platform, we lay out the honest trade-offs on the Sanas alternative and build vs buy pages and the voice AI for BPOs page goes deeper on the call-center use case.