Welcome your shoppers whenever they are with Grid Genie — virtual shopping assistant
Conversational AI can engage the customer at every step of the shopping journey — from product discovery, product research and selection, to checkout and post-purchase support.
Available through voice and messaging channels and powered by deep natural language processing capabilities, the Grid Genie virtual shopping assistant is ready to help your customers wherever and whenever.
With our battle-proven technology blueprints and expert engineering services, we can greatly accelerate the development and deployment of conversational AI that has capabilities custom-tailored to your business needs.
Personalize your customers’ banking experience with a Digital Banking Assistant
Grid Dynamics has built a customizable, cutting-edge Digital Banking Assistant. This solution enables you to deliver intelligent, AI-driven conversational experiences to engage, retain, and grow your user base.
You will be able to provide a personalized banking experience with AI/ML-based technology. Your mobile app will become a financial advisor that learns your customers’ preferences, all while integrating seamlessly with your bank’s existing ecosystem.
Talk to your data with knowledge‑based virtual assistant
Modern enterprises generate, store, process, and disseminate mountains of data. This includes both long term knowledge such as policies, contracts, technical specifications, design descriptions, manuals, best practices and research papers, and operational data such as current financial performance, supply and demand figures, production reports, etc. And even more money and effort is spent making sense of this data with analytics. Yet companies still experience difficulties in the “last mile” delivery of the right data to the right people at the right time to support their daily work and decision making.
Employ a modern conversational AI system to unlock business intelligence and enterprise knowledge for your leadership and your teams. Give your knowledge workers answers instead of links and remove the frustration of data sifting from their working day.
Empower your support team with AI co-pilot
Contain more calls and lead your customers to the proper support agent. Empower your agents with conversational AI co-pilot.
Utilizing a support AI co-pilot can provide agents with the complete context of each customer’s journey. It can listen in to the agent‑customer dialog and instantly suggest possible answers to customer questions to select from. It conducts searches for the products customers mention and registers key issues and complaints. In short, it will become your support agent’s best friend.
FINANCE & INSURANCE
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 — this ensures 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
How we built a conversational AI for ordering flowers over Amazon Alexa or Google Home
This case study showcases how we built the conversational AI system for ordering flowers and what lessons we learned while working on different aspects of the project including conversation design, data collection, natural language processing, testing, and certification.
Finding a needle in a haystack: building a question answering system for an online store
Here we describe the experience of building machine reading comprehension systems and adapting them to a specific domain, especially in cases where we don’t have access to resources to label a lot of data.
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.
We offer free half-day workshops with our top experts in conversational AI to discuss how to apply virtual assistants to your business and share industry best practices.
Proof of concept
If you have already identified a specific use case for visual search we can start with a 4–6 week proof-of-concept project based on your data and your domain to demonstrate the power of modern conversational AI.
If you are in the stage of requirements analysis and strategy development, we can start with a 2–3 week discovery phase to identify the correct use cases for conversational AI, design an optimized solution, and build an implementation roadmap.
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.
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