Our voice AI costs too much or keeps failing.
I build dashboards that show what every call costs and where it fails. Then I fix it with TTS and LLM caching, leaner call flows, models fine-tuned for your calls, and, where your volume justifies it, a move off per-minute platforms to LiveKit or Pipecat in your cloud. For one debt-collection client this cut the pipeline's operating cost by 90%, saving $300k+ a year.
What's included
Per-call cost and quality dashboards
Every call scored automatically, with cost, latency and failure points on one dashboard. I pick the fixes from that data.
TTS and LLM caching
Repeated phrases and answers are served from cache instead of being generated again on every call.
Models selected and fine-tuned for your calls
Smaller, cheaper models tuned on your scenarios, where an oversized general model was doing the job.
Latency fixes
I find where the delay comes from, whether that is the model, VAD thresholds or audio routed through the wrong region, and fix it.
Simulated-call regression suite
Test calls built from your real scenarios, run after every change, so a cost cut that hurts quality or brings hallucinations back is caught before callers hear it.
Provider failover
If an LLM or speech provider goes down, calls switch to a backup automatically. You're no longer locked into one vendor.
How it works
1. Measure
I add per-call cost and quality tracking to your current pipeline, so we see exactly what each call costs and where it fails.
2. Rank the fixes
You get a short list of fixes ranked by savings and risk: caching, call-flow changes, model swaps, region and vendor moves.
3. Fix and test
I implement the fixes and run the simulated-call suite on each one before it reaches a live caller.
4. Roll out on a share of traffic
Each change goes live on a share of calls first, next to the old version. It moves to full traffic only if cost and quality hold.
Good to know
It works on the stack you already have. A migration only happens if the numbers show it is worth it.
Each fix has to keep CSAT steady and pass the test suite before it goes to all calls.
The changes land in your repo, so your team owns them and can audit every change.
Find out where your calls lose money.
Book a free consultation. Bring your stack and your cost per call, and we'll find the first thing to fix.