Skip to content
tarıtas
The blog

Notes from production.

Voice AI engineering, written for people who have to ship it and defend it in a security review. New posts two to three times a week.

All posts
Build decisions 7 min read

Chatterbox vs Azure Dragon HD: Choosing a Voice Agent's TTS in Production

Text-to-speech is the decision that most shapes how a voice agent sounds and what it costs. At Taritas we made the same choice three times for one production agent: a managed cloud voice, then self-hosted Chatterbox for quality, then back to a managed Azure Dragon HD voice once it cleared the bar. The honest comparison is that self-hosted Chatterbox wins on control and in-region flexibility but turns a line item into a GPU operations program, while managed Azure Dragon HD wins on cost and simplicity once its quality is good enough in your region. Neither is universally right; the answer changes with your region, your scale, and how much operations load you can carry.

Procurement and compliance 6 min read

What Happens When Your Voice AI Breaks in Production

The demo never shows you what happens at 2 a.m. when the agent stops answering and a real customer is on the line. Before buying voice AI, the operations questions decide more than the feature list: who is on call, how fast you hear about an outage, whether a failure degrades safely, and what the postmortem looks like. At Taritas we run production voice agents with on-call rotations, a communication discipline kept separate from the debugging, guardrails that fail open, and blameless postmortems, because in an always-on, per-minute product, how you handle the break is what the customer remembers.

Build decisions 7 min read

White-Label Voice AI for IT Services Firms: 7 Production Lessons

At Taritas we build white-label voice AI that regional IT services firms resell under their own brand, and the same lessons hold on every engagement. The ones that decide whether it works are rarely about the model: who owns the customer and the IP, whether the per-minute price can carry the architecture, and the configuration and operational discipline that keeps a live agent up. The demo is never the hard part.

Production engineering 5 min read

Three Attempts at Masking a Voice Agent's Thinking Silence

After a caller stops talking, a production voice agent we run at Taritas has about 2.2 to 2.5 seconds of dead air before its first audio frame. We made three serious attempts to mask it: a classifier-driven filler, a state-change-driven filler, and preemptive generation. All three are disabled in production today, each for a different structural reason, and the usable lesson is about speech queue ordering: the only filler insertion point that works is the one where the reply does not exist yet.

Production engineering 5 min read

Rate Limiting a Voice Agent With One Postgres UPDATE

A real-time voice agent's daily call cap has to be checked before the greeting plays, survive concurrent calls, and roll over at midnight. At Taritas we do all three in one Postgres UPDATE: a CASE expression handles the midnight rollover, the WHERE clause enforces the cap, and RETURNING reports which case fired. One round trip, no race condition, no scheduled job.

Production engineering 7 min read

A 15-Second Default Timeout Broke Our Voice AI's Call Transfers

A production voice AI agent we run at Taritas stopped transferring callers to staff. Every transfer failed with a 504 at exactly 15 seconds, Envoy Gateway's default route timeout, while the destination line had developed a 13-second post-dial delay. The failed API calls left dials ringing in the background, so staff answered ghost calls. One scoped timeouts block on the HTTPRoute fixed it.

Reading this because a client asked for voice AI?

That is the conversation we are built for. taritas engineers it behind your brand.

What taritas does for partners