Conversation Cloud forIntelligent Machines

Build Siri-like apps for your business/domain in hundredth of the effort through our simple-to-use API. Coupled with the ability to handle multi-turn complex conversations, let your visual assistant take your customer experience and your business to the ever new heights!


Why Mauna

Mauna has a novel approach to modelling conversations that combines state of the art research in Controlled Natural Languages (CNLs)- pioneered by us, Deep Learning and Ontology construction. Mauna is able to model context and background knowledge better than any other system in the market today. This enables developers to build more powerful experiences for their end user which ultimately solves very complex, real-world use cases.

Build complex conversation flows

Mauna allows you to focus on your business logic without worrying about intent classification and data extraction. With a simple UI based interface, complex user interactions can be developed in a fraction of time and code that it would generally take.

Faster development iteration

The comprehensive set of APIs allow for easy integration and breaks down the complex chatbot development process into simple iterations. This makes the code easy to test and debug resulting in faster development.

No ML/NLU knowledge required

With Mauna, writing code is like a breeze. The ergonomics of the API are inspired by mental models for web development making it accessible to the average JavaScript developer with no expertise in Machine Learning or Computational Linguistics.

Integrated reasonging support

Cognitive reasoning ability of Mauna bot which comes from constant learning through experiences & inferring context by analyzing intention in user utterances allows it to handle non-linear conversations and ask smart questions to get the data needed to deliver a good outcome.

No utterances/datasets required

Mauna bot doesn't start with data but an existing model of human knowledge. We combined deep learning models and automated reasoning to build intelligent machines that don't require numerous instances of the intent to be fed into the system to fulfill user requests.

Easy-to-write dialog scripts

Give your voice/chatbot a personality, voice and tone that resonates with your target audience. Building a dialog flow and adding a personalized touch to render an impeccable user experience has never been so simple before!

Frequently asked questions

Can't find the answer you're looking for? Reach out to our customer support team.

What is Mauna?
Mauna is a comprehensive platform that brings together a host of natural language and speech models in a declarative product.
How does Mauna work?
We combined deep learning models and automated reasoning to build our own domain specific language that in the end provides an API that feels like writing prose but achieves intelligent behavior in 1/10th of the code required today.
Does Mauna provide an end-to-end API solution?

Yes it does! We provide the first end-to-end cross platform API for building sophisticated voice and chat bots.

Our API covers all the aspects of a chatbot ecosystem including providing a bot building platform to NLP support & bot testing & analytics.

How does Mauna simplify a developer's life?

Chatbot developers including the hobby developers and companies (software development houses that build various custom software solutions) mostly rely on publicly available APIs to build custom bots for their clients. The 3 main aspects of a conversational AI solution are Automatic Speech Recognition (ASR), Natural Language Understanding/Processing (NLU/NLP) and Machine Learning (ML). In order to achieve a fully functional customised bot solution, developers often have to deal with the integration of different apps and APIs which results in heaps of code that is difficult to debug.

With Mauna, developers get all the powerful tools and capabilities of building a sophisticated bot under one roof which gives them greater control over the code and the flow. This means they can have more time focusing on implementing the business logic rather than building the bot.