Voice AI that sounds and listens like a person.
We build custom Speech-to-Text (STT) and Text to Speech (TTS) models, tuned to your accent, your industry's vocabulary, and the latency profile your product demands. From sub second voice agents to nationwide call center deployments.
Speech that
handles real life.
Off the shelf APIs handle clean studio audio. Production speech is messy: accents, code switching, background noise, jargon. We tune for the audio you actually have.
Custom STT Models
Tuned to your industry vocabulary, accents, and noise profile, beating general APIs on the audio that matters to you.
Natural TTS Voices
Brand voices that don't sound like a robot. Custom personas, multilingual ranges, and emotion aware synthesis.
Real Time Streaming
Sub 500ms end to end latency for live voice agents. Streaming partials, barge in handling, and turn taking that feels human.
Voice Cloning
Authorized voice replication for branded TTS, dubbing, and accessibility, with consent workflows and watermarking.
Multilingual & Code Switch
One model, multiple languages, including the messy reality of code switching mid sentence in real conversation.
Production Serving
Optimized inference on GPU or CPU, with autoscaling, batching, and observability tuned for voice workloads.
Six places a voice that actually listens changes the math.
Voice AI finally works, and the market numbers prove it, but only when it survives contact with real audio: accents, noise, jargon, and callers who interrupt. These are the six deployments where that survival is the whole product.
Voice Agents for Call Centers
The hardest ROI in the AI catalog: an AI-handled call costs $0.30 to $0.50 against $6 to $12 for a human, which at meaningful volume compounds into hundreds of thousands a year. We build voice agents with the streaming, barge-in, and turn-taking that make callers stay on the line, running the same conversation brain as our sales and CRM chat, so a customer who starts on your website and finishes on the phone meets one assistant, not two strangers.
Accents and Dialects the Big APIs Give Up On
The industry's own data says it plainly: speech systems trained on real regional audio consistently beat general-purpose models, whose error rates can double the moment a caller does not sound like the training set. Our models are tuned on your market's actual voices, accents, dialects, and mid-sentence code-switching included, built on the same foundation as our multilingual and low resource language practice, because a voice agent that mishears your customers is worse than no agent at all.
Industry Vocabulary That General Models Butcher
Drug names in clinical dictation. Part numbers on a warehouse floor. Legal citations, aviation call signs, the product SKUs your whole business runs on. General STT transcribes around specialized vocabulary and hopes; we tune on it, which is the difference between a transcript your systems can act on and one a human has to fix, at which point you have automated nothing.
Voice for Learning and Assessment
Some of the highest-impact speech AI never answers a phone: early readers practicing aloud with a listener that never loses patience, language learners drilling pronunciation, and oral exams graded consistently instead of by whichever examiner was tired. We build the listening and speaking layer for education platforms, tuned for young voices and accented speech, which is exactly where off-the-shelf speech APIs fail hardest.
Branded Voices and Produced Audio
A TTS persona that is recognizably yours across IVR, product, and content, plus dubbing, audiobook narration, and accessibility audio at production quality. Where a real person's voice is replicated, it happens with contract, consent, and watermarking, so the asset is durable instead of a liability, and the voice your customers hear stays consistent whether a human or a model is speaking.
Voice Where Typing Was Never the Interface
Drivers logging deliveries, technicians updating job status with their hands full, field teams in markets where voice notes outnumber texts ten to one. Voice is the natural interface for enormous parts of the working world, and in many of the markets we serve it is the primary one. We build hands-free, noise-tolerant voice workflows that meet people where they already talk.
The Demo Is Clean Audio. Production Is a Motorbike Horn Behind a Code-Switching Caller.
Benchmark data draws the line clearly: leading systems hit low single-digit error rates on clean studio audio, and the acceptable ceiling roughly doubles on noisy, accented, real-world calls. Every vendor demo lives on the first number; your customers live on the second. Our engagements start with an audio audit of your genuine recordings for exactly this reason, because the only benchmark that predicts production is one built from production.
The Voice Is the Interface. The Agent Is the Product.
Sounding human is table stakes; doing the work is the job. Behind every voice deployment we ship sits the same architecture as our enterprise AI agents: tool access, guardrails, escalation logic, and audit trails, so the voice that takes the call can also check the order, book the slot, and process the refund. A beautiful voice that cannot act is an expensive answering machine.
From audio sample to production voice.
Speech models live or die on data quality and latency tuning. We invest heavily in both before tuning anything else.
Audio Audit
We sample your real world audio, call recordings, IVR logs, field recordings, and characterize accent, noise, and vocabulary.
Data & Annotation
Labeling pipelines, native speaker QA, and synthetic augmentation to expand the corpus where natural data is thin.
Train & Latency Tune
Model training, then quantization and serving optimization until we hit the latency profile your application needs.
Deploy & Iterate
Production serving with monitoring on word error rate, latency p95, and user reported failures, improvements pushed weekly.
Voice economics, honest containment rates, and how to test any vendor.
Voice AI pricing is famously layered and the performance claims famously demo-grade. Here are the real numbers, the honest benchmarks, and the one test that exposes every vendor, including us.
Market pricing runs $0.05 to $1.00 per minute depending on how much of the stack is bundled: bare infrastructure starts around $0.05 to $0.15, managed platforms run $0.25 to $0.50, and the recurring buyer complaint is that the headline rate never matches the invoice, because STT, TTS, LLM tokens, and telephony each bill their own layer. The number that matters is cost per resolved call, and there the math is decisive: $0.30 to $0.50 for an AI-handled call against $6 to $12 fully loaded for a human one. Our proposals quote the all-layers per-minute figure and the projected cost per contained call at your volumes, so the invoice is a forecast, not a discovery.
A focused STT adaptation, your accents, your vocabulary, your noise profile, typically runs $25,000 to $80,000, with data collection and native-speaker annotation, not training compute, as the dominant line. A full production voice agent with custom STT, a branded TTS voice, and integration into your systems runs $60,000 to $150,000 and beyond at call-center scale. The honest threshold: if a general API already hits acceptable accuracy on your real audio, use it and skip us, which is precisely what our audio audit establishes before anyone signs anything.
Lower than the sales decks say, then higher than you expect. Honest benchmarks: 20 to 40 percent containment in early deployment, 40 to 70 percent in mature ones, with the cross-industry average around 41 percent. Two warnings the industry earned: any vendor promising 80 percent on day one is describing their best case as their base case, and containment optimized alone is a trap, because an agent can force-resolve calls that should have escalated and the dashboard will call it success. We track containment paired with satisfaction and repeat-contact rates from day one, so a resolved call means the customer's problem ended, not just the call.
The benchmark line: under 8 percent word error rate on clean audio, under 15 percent on noisy or accented calls, and word-level accuracy on the vocabulary your business actually depends on, since a transcript that nails every word except the part number has failed. The verification method is the only one that works: never accept accuracy claims measured on a vendor's demo audio, including ours. Hand over a sample of your genuine recordings, worst lines included, and demand the error rate on that. Our audio audit is that test made standard procedure, and the resulting benchmark is yours to hold every future vendor against.
Yes, if it earns it in the first five seconds, and the bar was set by decades of IVR abuse, not by us. What the deployment data shows: callers stay when the agent responds fast enough to feel conversational, lets them interrupt, understands them the first time, and offers a human without being begged. What kills adoption is the opposite of each, plus any hint of the phone-tree maze. We design every agent with instant barge-in, a clean escalation path, and disclosure that is honest without being apologetic, because the goal is not to trick callers into thinking it is human, it is to resolve their problem fast enough that they stop caring.
You do, across every layer that matters. The tuned speech models are your asset, the branded TTS voice is contractually yours with the talent agreements written for it, and your call recordings, which quietly become the training data that keeps improving the models, stay your property in your infrastructure. This matters more in voice than most buyers realize: platform vendors can hold your custom voice and your accumulated audio hostage at renewal time, and a brand voice you cannot take with you is not a brand asset. We build so the voice, the models, and the data walk with you if we ever part ways.
Our discovery call has the same price of admission as our hardest engagements: ten minutes of your worst real audio. We will run it live and show you the error rate, because in this category any vendor unwilling to be tested on your audio has already told you their number.
Questions about
Speech AI
For some use cases, those are great. We're called in when accuracy on accents, dialects, or industry vocabulary isn't acceptable, when sovereignty matters, or when latency budgets force on prem inference.
Yes, that's often the requirement. We optimize models for your hardware (GPU or CPU) and ship a serving stack that meets your latency and throughput targets without leaving your perimeter.
Sub 500ms end to end for streaming STT, sub 300ms first byte for TTS, on appropriate hardware. We design to your latency budget, not the other way around.
Authorized voices only, with documented consent and audit trails. Output watermarking is on by default. We won't clone a voice without the owner's signed agreement.
20+ in production today, including low resource languages like Mongolian. For new languages, see our multilingual AI offering.
Stop experimenting.
Start deploying AI that works.
Book a free discovery call. Send a sample of your hardest audio and we'll show you what's possible, without the demo theater.
info@croncore.com