Keep your voices. Cut the bill.
Transcript
- 0:01
Your voice agent sounds premium. So does the bill.
- 0:06
VARTA doesn't ask you to replace the voice you chose. Keep ElevenLabs. Keep your voice, your tone, your brand. VARTA sits in front of it.
- 0:17
Most of what an agent says, it has said before. VARTA plays those lines from cache, in the same voice, and sends only the new ones to your provider.
- 0:28
On a premium stack, that cuts the voice bill by sixty to eighty percent, and the cost of a whole call by up to sixty-nine percent.
- 0:37
Same voice. Deterministic answers: the same input gives the same output, every time. And cached lines start instantly, with no model in the way.
- 0:51
At a million calls a month, that is up to two hundred and sixty-eight thousand dollars saved. Every month.
- 0:58
Same quality. Better performance. Enterprise-friendly cost. VARTA.
About this film
VARTA sits in front of your voice provider and decides what really needs to be synthesised. Most of what an agent says, it has said before, so those lines replay from cache in your provider’s own audio. On a premium stack the site’s cost estimator models a 67–89% lower speech bill at 70–90% of lines replayed, and 58–69% lower cost per call.
1:06 · · English captions
More films
Teaser · 56 s
The model can wait.
In a world where every voice agent waits for a model, one engine decided not to wait. Rules first, model last: seven layers, zero hesitation, the same voice at half the bill.
Explainer · 4 min
Train once. Run a million calls.
DAKSH uses a language model once per workflow, the way a programmer uses a compiler. VARTA runs every call on seven layers of code, asks the model last, and never lets it invent a route.
Walkthrough · 4 min
Configured once. Decided every turn.
Step by step through a bank KYC workflow: the configuration DAKSH writes at each step, and how it lets VARTA decide the call inside the engine instead of asking a language model.
Head to head · 1 min
Same call. Three agents.
One caller, one request, three voice agents: a cascaded pipeline, a speech-to-speech model and VARTA. Watch which one waits, which one mishears the address, and which one confirms it by rule.
Inside the engine · 47 s
One sentence through the VARTA engine
Follow one caller sentence through VARTA layer by layer: reflex, recognition and rules first, an LLM only when nothing else can answer, every step on one visible ledger.
For enterprise · 1 min
Why VARTA works for enterprise
Fluency no longer closes deals. Decisions by rule, writes to your ERP mid-call, live data volunteered only when a threshold is crossed, and a deterministic cost engine, in four markets.
Layer 5 · 1 min
NITI: the rule engine inside VARTA
Every voice agent waits for a language model. VARTA mostly does not. NITI resolves a turn by rule in under two milliseconds, with the LLM as the last resort.
UPCHAAR and SHALYA · 2 min
How VARTA heals itself
Most voice agents stay as smart as the day they were written. VARTA’s two healing layers learn from every LLM rescue and propose structural fixes, checked before anything goes live.
Launch film · 24 s
Introducing VARTA
A voice-agent platform with a visible cost ledger: seven explicit layers, cached audio for repeated phrasing, and only the turns that need reasoning reach an LLM.