How our conversational AI technology works
Designing conversational AI is a multidisciplinary field. To understand the user, we combine our expertise in ML-based speech recognition and natural language processing with context management to maintain the actual state of the dialog.
To fulfill user requests, we employ our deep expertise and familiarity with solutions in search, question answering, and enterprise integration.
With years of experience in enterprise integration and system engineering, we are able to seamlessly connect conversational AI capabilities with existing enterprise services.
At the heart of the Conversational AI system lies a dialog manager that is responsible for tracking the context of the conversation. It maintains the state of the conversation, routes incoming requests to specific dialog agents, supports context switching and more.
We employ a hybrid of rule-based and neural dialog managers to create a smooth and reliable conversational experience.
We use state-of-the-art NLP models to solve tasks like intent classification, entities and relation extraction, coreference and more. We employ a variety of transfer learning and knowledge distillation techniques to help adapt the solution to your domain specifics.
Question answering based on unstructured data such as product descriptions, FAQ, reviews or knowledge articles is an essential part of the conversational AI functionality. We use the latest Machine Reading Comprehension models to ingest and analyze your data and automatically extract the answers your customers need.
Accelerate implementation with our Conversational AI blueprint
We have developed a battle-tested reference architecture for an AI conversational system. This microservices architecture simplifies the extension of virtual assistant functionality with new dialog agents and allows for the mix and match of in-house and 3rd party implementations of key capabilities.
We focus on open source and cloud native software, and state-of-the-art deep learning model architectures to enable seamless deployment on any public cloud or private infrastructure. We partner with AWS, Google Cloud, and Microsoft Azure cloud providers to ensure the highest efficiency and best practices.
- Open source — we utilize state-of-the-art open source modules in your custom-designed application. Using well supported open-source modules ensures your application will remain relevant, regardless of future trends.
- Pluggable cutting-edge NLU models — state-of-the-art NLP models are used to solve tasks like Intent and Entity extraction. We use various transfer learning techniques to adapt the solution to specific domains.
- Support for a variety of channels — Google Home, Alexa, Facebook Messenger, Slack, or Teams, our architecture supports a wide array of channels.
- Bespoke language models tuned to your domain — thisensures the best possible understanding of your user base.
- Highly scalable and robust — microservices architecture ensures high scalability and resilience.
- Infrastructure — AWS, GCP, or Microsoft Azure are supported. On-prem solutions are available as well.
- Deep learning — a choice of TensorFlow or Pytorch.
- NLU/NLG — bespoke in-house models, Dialogflow, Lex, or Luis integration.
- Question answering — bespoke in-house models, Kendra, Q&A maker.
Read about our conversational AI
Finding a needle in a haystack: building a question answering system for an online store
Get started with Conversational AI
We provide flexible engagement options to design and build conversational AI systems. Contact us today to start with a workshop, discovery, or PoC.
More AI solutions
Modern conversational AI is redefining our workday, our shopping experience, our homes, and our daily habits. As more and more conversational devices and virtual assistants enter our lives, customers and employees expect to be able to engage in conversation with your enterprise from any device or channel, on‑demand, day or night.
We design and implement conversational AIs that will empower your team and delight your customers.