Conversational AI data is dialogue, scripted or spontaneous, recorded for the product you're building: call center and support, banking, healthcare, retail, IVR and voice bots. We plan the accent and dialect mix around your target markets, our Conversation Audio tool captures both sides, and a review pass runs before delivery.
Conversational AI data is recorded dialogue between people, collected so a voice bot, IVR or chat assistant can learn how real conversations go. It captures the words people use, the order things happen in, and the interruptions and corrections a script leaves out.
It comes in two kinds. In scripted dialogue, speakers follow prompts so every intent you need shows up often enough. In spontaneous dialogue, people talk through a task the way they would on a real call, like disputing a charge or moving an appointment.
The recordings usually get transcribed and labeled afterward, with speaker turns, intents and entities marked, so your model learns what was said and also what the caller wanted. For read speech, accents and recording conditions beyond dialogue, see speech data.
If you are planning the recording side, our guide to what to specify before you collect speech data and the one on transcription for AI versus for people are worth reading first.
A voice bot for a bank has to recognize KYC, EMI and UPI the way customers actually say them, in more than one accent. A healthcare assistant has to catch drug names and symptoms. Vocabulary like that rarely shows up in general speech data, so it's worth collecting for the domain. We capture it in our own Conversation Audio tool.
Support calls about the issues your agents or bots already handle, in the many ways customers phrase them.
For intent detection, routing and agent assist
Our tool: Conversation Audio Free sample of call center and support data
Conversations about accounts, cards, loans and payments, with words like KYC, EMI and UPI said the way customers say them.
For banking voice bots and IVR
Our tool: Conversation Audio Free sample of banking conversation data
Calls around appointments, symptoms and follow-up, where a model has to catch drug names and symptoms correctly.
For booking lines and patient assistants
Our tool: Conversation Audio Free sample of healthcare conversation data
Chats and calls about orders, returns and delivery, the questions an online store answers all day.
For shopping assistants and support bots
Menu-driven or open-ended, recorded so the system learns to route what callers actually say, not just the menu words.
For IVR, voice bots and call steering
Our tool: Conversation Audio Free sample of IVR and voice bot data
Planned from the brief onward: you tell us which markets you serve and where your callers live, and we plan the mix around that.
For speech recognition that works for every caller
Common jobs for recorded dialogue, and the part of this page behind each one. They're examples of the work, not a client list.
Many ways of asking for the same thing, so a bot learns that "my card's blocked" and "the card isn't working" are one request.
Words like KYC, EMI and UPI, or drug names and symptoms, which general speech data rarely has enough of.
Phone-quality audio in the accents your callers have, so the model hears them the way a real line does.
Spontaneous calls show a model what happens when someone changes their mind halfway through a sentence or talks over the bot.
Two-sided calls, transcribed with speaker labels, so a model can follow who asked what and how it was resolved.
Real conversations the bot never saw in training, used to check how it copes with callers before customers do.
Scripted dialogue gives you control. You decide which intents appear, how often and in what wording, so nothing gets missed. Spontaneous dialogue gives you what scripts can't: hesitation, interruptions, corrections and people changing their mind halfway through a sentence.
Scripts fill the gaps, and spontaneous conversation shows the model what real callers sound like. We plan the mix with you, based on what your product has to handle.
Four decisions made up front shape what your model hears, and they're much cheaper to change now than after the recordings exist.
Which requests your product has to handle, and how many examples of each. The rare ones need a script, or they won't show up.
Where your callers live and which accents and dialects they speak. It belongs in the brief from day one.
Banking and healthcare calls involve personal details. Agree whether participants use invented details or their own, and what the data may be used for afterward.
A call over a phone line sounds different from audio captured in an app. Record the way your product will hear people.
Your named contact runs the project from the first brief to delivery. The steps go in this order.
You tell us the industry, the intents and the languages.
The NDA is signed before any of your data moves.
We plan scripted and spontaneous dialogue and the accent coverage.
We record a small sample free, so you can check it before you commit.
Participants talk while Conversation Audio captures both sides.
A review pass runs before delivery, with a named person to answer for it.
We work in languages from all over the world and go deep on Indian ones, well past Hindi and English. Accent and dialect coverage is part of every conversational data project, and our page on Indian language data has the details.
The words that come up when you plan a dialogue dataset, and what each one means.
One team can record the conversations, transcribe and label them, and check your bot against them. You can also compare all eight services. Two example categories built on this service: Hindi BFSI call center speech and paired chat and voice support data.
Calls turned into reviewed text, with speakers and timestamps.
Intents, entities and sentiment labeled on the transcripts.
Your bot checked against real conversations and your targets.
Speech, text and other data beyond dialogue.
Prompts and scripts carried into your other markets.
Short answers about this service. The services FAQ covers the other services and how they fit together.
Recorded dialogue between people, collected so a voice bot, IVR or chat assistant can learn how real conversations go: the words people use, the order things happen in, and the interruptions and corrections a script leaves out.
Call center and customer support, banking and financial services, healthcare, retail and e-commerce, and IVR and voice bot use cases.
In scripted dialogue, speakers follow prompts, so you control which intents appear and how often. In spontaneous dialogue, people talk naturally about a task, with the hesitation, interruptions and changes of mind that real callers have. Most voice products need both.
Yes, it's part of every conversational data project. Tell us where your users are and we'll plan the accent and dialect mix around that.
That's a decision to make with us before recording starts. Banking and healthcare calls involve personal details, so agree early whether participants use invented details or their own, and what the data may be used for afterward.
Yes. We run transcription and annotation ourselves, so the recordings can move on to them without a second vendor.
The industry, the intents your product has to handle, the languages and where your callers live, and a rough volume. Example calls or chat logs help if you can share them.
Yes. Send a short brief and we'll record a small sample free before you commit.
Yes. The NDA is signed before any data moves, we use it only for the scope we agreed, and only the people working on your project can get to it. It's returned or deleted when you ask.
Pick the kinds of conversation, add the languages and roughly how much you need, and send it. We'll record a small sample free before you commit.
This opens your email app with the brief filled in. Nothing is sent until you press send. You can also use the contact page.