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AI voice agents are being used for tasks as different as answering delivery-support questions, taking restaurant orders, and scheduling healthcare visits. The 13 examples below show why “voice agent” does not mean one uniform level of automation: some systems handle routine calls, some connect to business workflows, and others are described only in vendor case-study indexes. Their reported outcomes are not independently validated or directly comparable.
13 named AI voice-agent deployments
This is a set of 13 named examples drawn from customer stories and case-study indexes, not 13 equally detailed or independently audited evaluations. Where a source supplies little detail, the table says so rather than inferring what the system can do.
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| Organization | Reported task and operating detail | What the source establishes |
|---|---|---|
| DoorDash | Dasher support, with an earlier IVR self-service path followed by a generative-AI solution. | AWS says the generative-AI solution was tested in early 2024 and later rolled out to all Dashers, handling hundreds of thousands of support calls a day. The earlier IVR—not necessarily the later generative-AI rollout—is associated with 49% fewer agent transfers, 12% higher first-contact resolution, and $3 million in year-over-year operational savings. AWS also describes a knowledge base and plans to expand toward actions through a logistics workflow service. |
| Donatos Pizza | Inbound phone ordering connected to the restaurant’s proprietary point-of-sale system and payment processing. | Revmo says it completed a seven-wave rollout across 174 stores in June 2025 after work began in April. Through August, the vendor reported 301,388 calls handled, 71% order conversion versus 58%, and 99.9% order accuracy; it also reported 4,840.8 labor hours reallocated in August 2025. These are vendor/customer announcement figures, not an independent audit. |
| Bell Canada | AI-powered agents for business customers as part of customizable contact-center solutions. | Google’s 2025 customer-experience document reports $20 million in savings across customer operations. It does not give a common measurement method or enough detail here to compare that figure with other cases. |
| Virtua Health | Inbound scheduling across multiple departments, with Epic integration. | Syllable says the agents went live in three weeks. The customer story does not provide a comparable call-volume or scheduling-success baseline. |
| MemorialCare | Replacing a navigation-center phone tree with AI agents. | Syllable attributes to MemorialCare’s VP of Operations the claim that the change took under eight weeks and that AI answered 100% of calls. The page does not define the measurement period or independently validate the claim. |
| Mahindra Finance | Voice agents for sales, collections, and employee engagement. | Sarvam’s story index claims more than one crore calls in 12 Indian languages. The index-level information does not supply a breakdown by task or an independent evaluation. |
| Carter’s | Seasonal hiring. | Listed in PolyAI’s case-study index; the index does not provide enough underlying detail here to assess the workflow or outcome method. |
| SafeRide Health | Call-volume handling. | Listed in PolyAI’s case-study index. The index-level description does not establish a comparable result or the agent’s precise autonomy. |
| Pacific Gas and Electric | Labor-hours outcome. | Listed in PolyAI’s case-study index; the underlying methodology is not available in the index summary. |
| UniCredit | Net Promoter Score (NPS). | Listed in PolyAI’s case-study index. The index does not establish the baseline, measurement period, or causal effect. |
| Audibel | Call abandonment. | Listed in PolyAI’s case-study index, without enough methodology in the index summary for a direct comparison. |
| Fogo de Chão | Customer satisfaction. | Listed in PolyAI’s case-study index; the index summary does not give a common measurement definition. |
| Hawksmoor | Missed calls and bookings. | Listed in PolyAI’s case-study index; the underlying results and evaluation method are not detailed in the index summary. |
Other named examples appear in the same source layer. PolyAI’s index also lists Quicken, a UK pub-restaurant chain, Howard Brown Health, Atos, and Simplyhealth. Sarvam lists Aadhaar/UIDAI, SBI Life, Tata Capital, and National Health Authority. OhMD’s healthcare customer page names Ascentist Healthcare and Cadena Family Practice, among others. Those listings identify organizations but do not provide equal detail about each deployment.
What these agents actually do—and where autonomy differs
The label “AI voice agent” covers distinct operating models. DoorDash’s support system is described as self-service for common inquiries, with a human contact center still handling more complex needs. Donatos’ system takes phone orders and passes them into the restaurant’s POS and payment workflow. Virtua Health’s agent schedules visits and integrates with Epic. These are task-oriented systems, not interchangeable general-purpose callers.
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Some AI used during calls is not a voice agent answering the customer. In the same 2025 document that discusses Bell Canada, Google describes Discover Financial tools used by 10,000 contact-center representatives to search for and synthesize information while speaking with customers. That is agent assistance: humans remain on the calls. It should not be counted as evidence of autonomous voice calls.
Human escalation remains part of the operating picture in the detailed cases. AWS describes DoorDash’s self-service path as freeing live agents for higher-complexity inquiries. Revmo says Donatos’ staff can focus on edge cases and escalations. A useful deployment description therefore specifies what the system handles, what it hands off, and whether the receiving person gets the context needed to continue.
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How to interpret the published results
The largest figures are promising, but they answer different questions. Donatos’ conversion and accuracy figures concern phone orders; DoorDash’s transfer, resolution, and savings figures concern a previously existing IVR path; Google’s Bell Canada figure is a broad customer-operations savings claim. Different baselines, periods, definitions, and publishers make a ranking from these numbers misleading.
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A free scan shows the junk files, broken settings and background clutter dragging Windows down - then fixes them in one click.Free scan · Windows 10 & 11- Separate the system versions. AWS describes DoorDash’s earlier IVR results as well as a subsequent generative-AI rollout. Do not attribute every earlier IVR metric to the newer system.
- Keep aggregate figures aggregate. Syllable reports more than 5 million calls automated annually across its customers. OhMD’s page summary says practices using its voice and text AI agents reduced phone time by 66% and grew bookings by 25%. Neither figure is a result for one named customer in the material cited here.
- Attribute the claim. The detailed outcomes above come from vendor, cloud-provider, or customer-story publications. A published case study is evidence of what its publisher reports, not independent proof that the deployment alone caused the outcome.
- Distinguish a live rollout from an index listing. The DoorDash and Donatos pages provide rollout and operating details. Several PolyAI examples are only identified in a case-study index, which is not enough to evaluate methods or compare results.
What to check before treating a deployment as a model
For a business assessing voice automation, the cases suggest asking for operational specifics rather than relying on the “agent” label or a headline metric:
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- ONE-TAP RECORDING FOR REAL-LIFE MOMENTS: Capture meetings, phone calls, and in-person conversations instantly with a simple tap, no typing, no interruptions, just effortless note-taking anywhere you go.
- SMART AI INSIGHTS & ORGANIZATION: Pocket automatically turns recordings into clear summaries, key action items and structured conversation maps so you can quickly review what matters without digging through audio.
- TURN CONVERSATIONS INTO ACTION WITH “ASK POCKET”: Don’t just record, understand. Instantly ask questions across your meetings, extract key insights and generate next steps in seconds. All grounded in your recordings, so answers stay accurate and reliable.
- MAGSAFE COMPATIBLE FOR SEAMLESS USE: Easily attach Pocket to your iPhone or other MagSafe compatible devices for convenient, hands-free recording on the go. Perfect for capturing meetings, calls, and ideas without needing to hold your device.
- Task and direction: Is the system answering inbound questions, taking orders, scheduling, routing calls, or placing outbound calls?
- Workflow connections: Does it connect to the POS, payment processing, EHR or scheduling system, knowledge base, CRM, or another system where the task must be completed?
- Human fallback: Which cases are escalated, who receives them, and does the conversation context transfer?
- Rollout and scale: Was the system piloted or put into production? How many sites or calls are covered, and over what period?
- Outcome definition: What is the baseline and measurement window for conversion, accuracy, transfers, call containment, savings, or satisfaction? Who measured it, and has it been independently checked?
- Language and market: Which languages, regions, and customer populations are supported? Sarvam’s index, for example, claims 12 Indian languages for Mahindra Finance, while many other case summaries do not specify language coverage.
Without those details, a success metric is best treated as a lead for further evaluation, not a forecast for another organization.
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- Walk out of every meeting with notes ready to act on: Plaud Intelligence transcribes in 112 languages with speaker labels and turns each recording into action items, decisions, and follow-ups, structured and ready to use. Choose from 10,000+ customizable templates tailored to your role and industry
- AI summary ready before you reach your desk: Auto Transfer moves each recording to the Plaud app automatically, and AutoFlow transcribes and summarizes so your notes are ready before you are back at your desk. Upgrade anytime to Pro (1,200 min/mo) or Unlimited
- Access your AI workspace anywhere: One connected workspace across Plaud Desktop, Plaud Web, and the Plaud mobile app, so your conversations and finished work follow you everywhere
- Your conversations stay private and yours: Compliant with ISO 27001, ISO 27701, SOC 2, HIPAA, GDPR, and EN 18031, with zero data used to train AI models. Trusted by 2.5M+ professionals, including legal, medical, and business professionals handling sensitive information
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- ONE-TAP RECORDING FOR REAL-LIFE MOMENTS: Capture meetings, phone calls, and in-person conversations instantly with a simple tap, no typing, no interruptions, just effortless note-taking anywhere you go.
- SMART AI INSIGHTS & ORGANIZATION: Pocket automatically turns recordings into clear summaries, key action items and structured conversation maps so you can quickly review what matters without digging through audio.
- TURN CONVERSATIONS INTO ACTION WITH “ASK POCKET”: Don’t just record, understand. Instantly ask questions across your meetings, extract key insights and generate next steps in seconds. All grounded in your recordings, so answers stay accurate and reliable.
- MAGSAFE COMPATIBLE FOR SEAMLESS USE: Easily attach Pocket to your iPhone or other MagSafe compatible devices for convenient, hands-free recording on the go. Perfect for capturing meetings, calls, and ideas without needing to hold your device.
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