Design

The major workload when building a voice solution or a chatbot comes from customizing the platform to the features of your product, and to the language of your users. We do this for you!

We build your AI solution on these platforms

Amazon Alexa / Lex

Google Actions

Samsung Bixby

Nuance Vocon

Line Messenger

Facebook Messenger

Which platform is best for you? Our innovative approach allows easy scaling of a solution built on a specific platform to any other platforms and languages, so you can build on one platform now to get your foot into voice, and then port to a new platform later for a fraction of cost and time.

We also do the following:

  • Quick migration of an existing bot to a new platform (e.g. port an Alexa skill to Bixby)
  • Voice-enable your chatbot, so users can talk to your chatbot instead of typing.
  • Building your own voice platform from scratch. This option brings voice to products, services, hardware, software or languages which are not supported by the big voice platforms.
  • Any Natural Language Processing (NLP) tasks such as parsing, grammar building, machine translation or information retrieval.

Modules of Building

Building a powerful conversational AI bot means completing several essential procedural steps and modules. We can take of all of these for you, or help you with individual parts:

  • Rapid Prototyping: A working proof-of-concept will show you early in the project, how an AI interface changes the feel of your products and services.
  • Use Cases and Requirements: Define scenarios and user stories how a bot will help people to use your products and services, and convert them into technical specifications.
  • System Architecture: Connect your voice solution or chatbot seamlessly into everything around: hardware, servers, databases, APIs, content, IoT, graphics and existing user interfaces.
  • Design of Language Model, Grammar and Dialog: This is the core task of any conversational AI: What will people say in their own words to get something done by your products and services, and how do the machines understand this? On some platforms, this will also include: carefully defining a set of natural sample sentences, creating a pronunciation dictionary for unknown words like brand names, setting format standards or writing linguistic rules.
  • Localisation: Launch your bot in multiple languages, or add languages to your existing voice solution. Each language presents individual challenges, so mere “command translation” is not enough.
  • Data Collection: A corpus of linguistic data helps to get a robust range of how people say the same thing differently (and they will). We can draw on our own databases, or organize individual new data collections with native speakers.
  • Coding: Convert dialog flow and architecture efficiently into code as required by the platform, e.g. in node.js, C++ or Python.
  • Quality Assurance: Run a scalable suite of tests and tools to establish an objective KPI showing performance and accuracy of your bot.
  • Legal: Manage licensing, copyright and privacy ramifications of having a conversational AI interface.

Can’t we build it ourselves?

A frequent yet risky assumption is that nowadays, voice and chatbot have basically become a free commodity and that anybody can voice-enable their products or ideas or build a chatbot simply by using a solution“off the shelves”: All that remains to do is to supply a few sample phrases and to modify code templates, and then the bot is ready to go live. This “quick and dirty” approach is risky: After a first bad impression, people tend not to come back; some might even post funny videos about their short-lived experience with a bad voice solution or clumsy chatbot.

The most popular Alexa skills like the Jeopardy quiz skill (produced by Sony) or the Chase Manhattan banking skill are developed by dedicated in-house teams of more than a dozen specialists each who build skills for a living. These companies understand that user experience and usability of conversational AI rises and falls with how carefully a solution is customized for specific requirements, and that it needs to be well supported also its after release.

Careful customization of the building blocks that the big voice and chatbot platforms provide is the key  – every use case is different because people will say different and new things to your product or service, and they might expect a different response from the device . The process of identifying and designing these individual sets of linguistic data and then coding them efficiently is the core work of customizing voice.

If you build a bot, let us make your work easier by guiding you with best and proven practices and by providing you with an objective framework to measure progress and performance. Or just leave some of the specialist work to us.

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