I run customer support for a mid-size brand. Phones ring all day. Customers don’t love long waits. My team needed a voice assistant that could answer, help, and pass the call to a human when needed.
So I tested PolyAI and a bunch of similar apps. I didn’t just read the docs. I set up real flows, made real calls, and put them next to each other. I even had my uncle (thick Boston accent) try to break them. He had fun with that.
Here’s what happened.
If you want the blow-by-blow call recordings and setup screenshots, I catalogued every step in this longer teardown.
What I Needed (and Why It Matters)
- Low delay when you talk and it talks back
- “Barge-in” so you can interrupt the bot and it listens
- Clean handoff to an agent, with notes
- Names, dates, and addresses that it doesn’t mangle
- Simple tools for my agents when I’m off on a Tuesday
That’s it. Not fancy. Just real.
If you also need a fast way to spin up a public-facing FAQ or support microsite to pair with your phone bot, give ZyWeb a look—I had one live in under ten minutes, and it deflected a surprising chunk of repeat calls.
PolyAI: Fast, Natural, and Pretty Chill With Interrupts
I spent one full week with PolyAI. I set up a phone line for order status, returns, and store hours. I pointed it at our Zendesk and our basic order API. It didn’t fight me.
Real example: I called and said, “Hey, my jacket showed up late, and it’s the wrong size.” The bot replied fast, “I can help with that—what’s your order number?” I cut it off mid-sentence with the number. It kept up. No awkward pause.
Wins I felt:
- Voices sounded like a real person. Not too chipper. Not tinny.
- Barge-in just worked. I could interrupt without throwing it off.
- Address capture did well, even with a dog barking near my phone. Long street names were okay.
- The analytics view showed stuck spots so I could fix phrasing.
For an even deeper technical analysis, I recommend this comprehensive PolyAI review that digs into the nitty-gritty architecture and pricing details.
Where I frowned:
- You’ll talk to sales for pricing. It’s more for bigger teams.
- Custom logic was smooth, but I leaned on their team for a weird return rule. Helpful folks, but still, not drag-and-drop simple for everything.
Would I use it again? Yes. For real phone volume, it saved my team time and helped callers feel heard.
Google Dialogflow CX: Flexible, But Bring Coffee and a Plan
I set up Dialogflow CX with a Twilio voice line and Google’s speech tools. I built an “Order Status” flow with a webhook to our order system. It did the job.
Real example: I said, “I forgot my password.” It routed me to the right flow, sent a reset email, and read back a masked address. Nice touch.
What I liked:
- Very strong at mapping intents and branching paths.
- I could add follow-up questions without breaking the whole tree.
- Works well if you already use Google stuff.
What slowed me down:
- It took me two long nights to get the whole phone flow clean.
- Training phrases helped, but I had to write a lot of them.
- Voice felt less natural out of the box than PolyAI.
Great for teams that want control and don’t mind building.
Amazon Lex + Amazon Connect: Solid for Call Centers in AWS
I built a small appointment bot for a clinic. Connect handled the calls; Lex handled the words. I tied it to a simple calendar.
Real example: “I need a morning slot next Thursday.” It got the date and time, then confirmed by SMS. Not bad.
Good news:
- Very steady call handling. Nice agent handoff.
- If you live in AWS, it snaps together well.
- Pricing felt clear at small scale.
Bad news:
- It tripped on last names like “Nguyen” and some street names.
- Tuning took a while. You’ll tweak prompts more than you want.
It’s a safe pick if you already run on AWS.
Replicant: “It Just Handles Calls,” but Less DIY
We ran a returns pilot with Replicant. They call it a “Thinking Machine.” It felt like that. It picked up, helped, and passed notes to our agents.
Real example: A caller said, “My shoes squeak.” It asked two quick questions, offered a prepaid label, and logged the reason code. That back-office code part saved us time later.
Upside:
- Strong at real call flows. Super low hold time.
- Good at messy caller speech. People talk fast; it kept up.
Trade-offs:
- Less self-serve. More of a managed setup.
- Pricing fits bigger shops, not tiny ones.
If you want results and don’t want to build every screen, this works.
Kore.ai: Lots of Knobs, Clear Tools for Ops
I used Kore.ai’s XO platform for a store-finder and order help line. Voice quality was fine. The builder had many parts—forms, entities, guardrails.
Real example: “Find a store near 30309.” It got the ZIP, asked if I wanted hours, then sent a text with directions. Clean.
Why it stands out:
- Great tooling for contact center folks.
- Nice guardrails so the bot stays on track.
- Strong analytics across channels.
Heads-up:
- It can feel heavy at first. So many buttons.
- You’ll want a small build plan before you start.
Balanced and strong once it’s set up.
Cognigy: Enterprise Flow Power, Best With a Dev Buddy
I built a Wi-Fi troubleshooting line. “My internet is slow” kicked off steps: reboot, check lights, schedule a tech.
Real example: It handled “My kid unplugged the router… again” and skipped to the right step. That made me laugh. And yes, that happened at my house.
Pros:
- Very flexible flow builder.
- Smooth handoff with notes to agents.
Cons:
- You’ll want an engineer for webhooks and data.
- Voice tuning took time.
Great for complex service trees.
Off the back of that, I went on to spin up three separate LLM tools for day-to-day ops; the real-world wins and face-plants are captured in this article.
Rasa + Twilio + Deepgram: Fun, Free(ish), and A Bit Wild
Weekend project: I built a pizza order bot for a friend’s shop. Rasa for the brain, Twilio for calls, Deepgram for speech.
Real example: “Large half pepperoni, half olive, pickup at 6.” It got it right twice. It called “olive” as “olive oil” once, which sent me on a toppings rant I didn’t plan. We fixed it with more training data.
Why try it:
- Full control. You own the brain.
- No license fee for the core.
Why not:
- You wear all the hats—dev, tester, and fixer.
- Voice polish takes work.
Best for hobby folks or teams with strong engineers.
That pizza bot weekend dovetailed with a mini-course called AI Apps Empire—I built two bite-size utilities and shared exactly what broke and what didn’t in this post.
Hyro: Healthcare and Hospitality Felt Easy
I tested Hyro for a dental office line. It handled insurance checks, hours, and booking.
Real example: “Do you take Delta Dental PPO?” It answered fast, then offered to text the intake form. Patients liked that.
Good:
- Prebuilt stuff for clinics and hotels.
- Quick to stand up a helpful line.
Less good:
- Outside those areas, it felt less flexible.
- Voice choices were fewer than others.
Pick it if your use case fits their wheelhouse.
SoundHound Smart Answering: Small Biz Friendly
I set this up for my friend’s hair salon. It answered calls, gave hours, offered to text a link, and took a message when needed.
Real example: “Can you do a balayage on Sunday?” It said Sunday was closed, offered Saturday, and texted the booking page. My friend booked two new clients that week from it.
Perks:
- Fast setup. Like, same afternoon.
- SMS follow-up was clutch.
Limits:
- Voice used to sound a bit stiff. It’s better now, but still not human-like.
- Not great for complex flows.
Nice for simple FAQs and bookings.
Quick Picks (So You Don’t Overthink It)
- Big volume, want natural voice: PolyAI or Replicant
- You want control and can build: Dialogflow CX or Kore.ai
- Deep enterprise flows with dev help: Cognigy
- DIY and cost control: Rasa + Twilio + Deepgram
- Healthcare or hotels: Hyro
- Small shop, simple calls: SoundHound Smart Answering
Looking beyond voice, if your support mix could benefit from a real-time text channel that specifically