Simulate in-store shopping experiences online
Powerful voicebots that understand customer intent like humans,
engage them in real-time dialogue, and drive higher conversions
- No hardware
- No coding
- Plug-n-play and get started in minutes
Deliver seamless CX with the world’s
most cognitive Voice AI
Just plug-n-play — yes, you heard it right!
Agara’s voicebot is pre-trained to resolve the most common e-commerce queries, without the need for a human agent.
Simply install the voicebot on your webstore in just a few clicks and let Agara take over all your customer calls. From post-purchase support requests to policy information inquiries, from availability requests to setting callbacks/appointments, Agara can handle all of it.
Personalize the way you want — No coding needed
Anyone can quickly build a voicebot now with Agara’s code-free builder.
You can customize ready-made templates for order tracking, cancellations, and returns or create your own bot from scratch to fit your business needs. Simply drag-and-drop pre-built blocks to create engaging voicebot conversations.
Human-like conversations your customers would love
Agara’s voicebot understands human speech very well, even when people cannot.
It can ask questions, clarify answers, present follow-ups, repeat information, correct mistakes, and much more. Your customers will be able to speak to the voicebot exactly how they would to your best agent.
Real-time customer insights at your fingertip
Every call handled by Agara will create a unique record for you to view. This includes the full recording and the transcript of the call, any information collected by the voicebot, and sentiment based on caller’s speech.
Agara lets you visualize key trends and support needs. Is the call volume going up? Are customers spending more time on calls? What are the most common queries?
with 100+ major platforms
Some more reasons to add Agara to
your webstore ...
Seamless agent transfer
Schedule call backs
Customizable call button
Security and compliance
Frequently Asked Questions
What is Conversational AI and how does Agara apply the same?
Conversational AI is a common term used for messaging apps, chatbots, and voice-enabled assistants or bots which can carry out conversations with humans over a text or voice. Conversational AI empowers businesses to engage customers in 1:1 interactions via text or voice at scale. Interactions may be based on context and past behaviors for personalized experiences.
Agara specializes in voice conversational AI. Agara builds virtual autonomous customer support agents for certain industries and use cases, for instance, an autonomous agent for account management in Banking. Agara’s conversational AI is built on a stack containing Deep Learning / Machine Learning models built from real customer support conversations.
Agara’s conversations module is built specifically for Voice conversations and hence takes into purview the complexities of it. It is therefore capable of having deeper multi-turn conversations, adapts to the speaker’s change in context, and most importantly converse naturally and not based on scripts.
Patented response generation module based on our public state-of-the-art ‘text style transfer’ technique, which ensures the system always comes up with the most contextual and natural responses. The conversational flow module adapts the responses to the customer’s speech, switches in context and intonation as and when required.
Natural Language Understanding (NLU)
Agara’s Natural Language Understanding (NLU) engine is pre-trained with proprietary data collected for specific use cases to accurately identify the intent (what the user wants), entities (name of the product, date/destination of travel, etc.), and the tone & sentiment from a user’s speech.
Text-to-Speech System (TTS)
Agara’s TTS is built specifically for business-to-customer communication and to ensure that it doesn’t sound robotic, it is trained using real calls to mimic the speaking style of an actual customer support agent.
What is unique about Agara’s AI product and approach to make Voice AI contextual and industry specific?
Agara’s uniqueness comes from
(a) the quality of conversations
(b) ease of creating a new workflow for specific industries.
Quality of Conversations
Agara’s autonomous agents are built to carry out 10x deeper conversations than typical chatbot platforms while holding context. The conversation system is trained on real historic support conversations and can handle any variation that the consumer can up with. Consumers can change their mind mid-call, refuse to provide information, ask questions, provide info without being prompted (things that happen in real conversations) and Agara will seamlessly handle them, gracefully transferring to a representative in the rare cases where the consumer’s question might be beyond Agara’s ability. Agara is also built to learn from the conversations it carries out, getting better over time.
Ease of Creating workflow:
Configuring Agara for a specific brand/use case is pretty much like onboarding an experienced customer support agent onto the new brand. You would only need to provide Agara the high-level, happy path flow, and Agara will automatically add in all the unhappy paths and variations that are possible. Providing a happy path happens in the form of simply selecting from an array of pre-built conversation blocks. However, Agara allows for finer-grained control of the agent’s language as well for people who would need them.
How does Agara differ from Conversational AI platforms like Rasa and Dialogflow?
Google Cloud Dialogflow is an end-to-end development suite for building conversational interfaces for websites, mobile applications, popular messaging platforms, and IoT devices.
Dialogflow and Rasa are text-first conversation platforms.
(a) Voice conversation agent: Agara is purpose-built for voice conversations and all the complexities that come with it like accents, noise, capturing entities which can have varied spelling, customer expectation of deeper conversations on voice as they typically call expecting an agent.
(b) Industry context: Agara is pre-trained with the knowledge of specific industries and there is no extra data/training needed to understand the common terminology and use cases. Agara also uses its patented Deep Learning models to squeeze out every bit of accuracy possible from its data. This is not the case with Rasa and Dialogflow where the client needs to provide the data, annotate them, and babysit the process and most likely incurring a huge accuracy penalty compared to Agara.
(c) Agara is not a platform: Agara is built for specific industries and use cases and trained on vast amounts of historic conversations. The client only needs to provide a very high-level conversation flow as they would if they were hypothetically onboarding a well-experienced agent to a new product. They don’t need to enumerate all the possible ways the conversation in reality would go, provide common-sense information, specify what happens if the consumer is not following the happy path or cooperating. This is all taken care of out of the box by Agara’s patented conversation engine which is purpose-built to handle long conversations in a truly natural way. The user is free to change the context, say something irrelevant, ask questions on the conversation, provide info without prompting, etc. Agara is engineered to behave exactly as how a trained agent would at the point. This is something that is not possible by design with platforms like Dialogflow and Rasa.
We already have a robust chatbot. Why do we need Agara? What is the difference between a chatbot and Agara?
Agara works purely on Voice and does not develop chatbots. While voice bots and chatbots have some similarities, Voice brings in a host of challenges that are simply not present in chat, and these fall under the categories of (a) Understanding the user (b) the conversation (c) voice that speaks out.
Understanding the user:
There are 100+ English accents in the world and hence a voice bot for global brands needs to be robust across accents, while the content (text) of what they may be saying could be exactly the same
Customers can call from a variety of noisy environments
Some things are hard even for human agents on voice channels like getting the customer’s name, identity, etc., because words spelled differently can have very similar pronunciations
Most chatbots can be menu-driven and hence easy to capture consumers’ intent and ensure a good user experience, but a menu-driven conversation on speech has a poor user experience.
Capturing entities accurately in most multi-turn conversations like ‘Was that A as in Alpha or E as in Elephant ?’ and the conversation needs to account for it
The conversation needs to be deeper to match the expectation of the consumer who called in expecting a human agent. A very chatbot-like conversation can be detrimental to the user experience.
A robotic-sounding bot is a bad user experience. Human agents undergo quite a bit of training on voice and tone. The bot needs to ideally mimic the same for the best user experience.
Different situations require different tones to be taken. For instance, the tone an agent would take with an irate customer is different from the one they would take with a happy customer.
Agara doesn’t replace chatbots as chat and voice are two very different channels. Chatbots are a deflection strategy to deal with simple, easy-to-answer queries. Despite using chatbots and menu-driven apps, a considerable number of customers still end up calling, as seen by the massive call volumes. Agara is designed to especially handle more complex queries from customers. This is the case for the industry that Agara concentrates on, validated by the massive call volumes.
If you have significant call volumes you need Agara. Agara brings with it a leap in conversational voice technology that can instantly handle complex customer queries, 24×7, and can massively scale to handle call spikes/volume uncertainties common in the current COVID situation. And it does all this while keeping the customer experience at the center by providing a zero-hold time experience, consistent and objective messaging, and a truly natural conversation. The significant cost reduction that you get by automation is purely a by-product.