Dynamic responses for customers are pushing the boundaries of what is possible
Recent advances in artificial intelligence have significantly improved the capabilities of Chatbots and Natural Language Processing (NLP) algorithms. Customers and employees can interact with systems indistinguishable from humans. These systems instantly respond with answers to questions derived from business documentation.
Using AI, machine learning, NLP, robotic process automation, and other modern software tools, businesses can implement conversational systems that disseminate company information, answer customer questions, and act as virtual reps for the company.
The conversational system matches the user’s intent and processes their input, matching it with the appropriate agent of the request. Intent matching optimizes a company’s customer service department by routing requests to the most appropriate agents and departments.
Understanding past user history while being aware of context and user preferences greatly enhances a conversational platform’s ability to successfully match intent. Businesses can proactively initiate conversation and actively shape user behavior.
Conversational systems are now more relevant than ever before and have creeped into almost every aspect of artificial intelligence platform planning.
These basic chatbots use very simplistic key word searches to match what you are asking for with a database of answers. These are the most popular chatbots.
Using Natural Language Processing a person’s voice can be converted to text and then married to a chatbot to provide intelligent routing of calls and potentially answers to questions.
Recent advancements in AI, such as OpenAI's generative AI product, (ChatGPT versions 3 and 4), use considerable computational time to train highly interactive and human like chatbots. These bots can be augmented with company specific knowledge to make them useful to your organizations.
Sentiment analysis allows computerized processing of emails, chats, and voice calls to determine whether a, for example, customer interaction or marketing campaign went well or if there were problems.
Chatbot market revenue worldwide from 2018 - 2027 (in million U.S. dollars).
Source: The Insight Partners (Statista 2021)
Deep Fakes and How they will Change the World
Source - AI for Customer Service. “AI for Customer Service.” IBM Cloud Education, n.d.
Our expert team creates advanced software engineering solutions that incorporate cutting-edge conversational systems and natural language processing technology, leveraging artificial intelligence, machine learning, and deep learning algorithms to build voice assistants, chatbots, and virtual assistants that can interpret natural language and deliver comprehensive services in dialog management, sentiment analysis, text-to-speech, speech recognition, language generation, and intent recognition, and we provide ongoing technical support and continuous improvement to ensure our clients' solutions are always up-to-date and optimized.
Speech to intent
Language support, variant, & detection
Sentence rewriting & enrichment
Multiple handler support
Multiple intent recognition
User attribute predictions
"We've build in-depth and complex automation systems with tier-1 automation software for some of the largest fintech firms in the country in their category."
Jignesh Shah, Sr. Automation Consultant, Product Perfect
"When it comes to automation and system engineering, Product Perfect's senior consultants are by far some of the best out there."
Katie Schmidt, Senior Database Architect
"The complexity of automation logic that they completely redeveloped was by far the most substantial refactoring our codebase has seen in years."
Eddie Batista, VP of Software Development
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Senior consultants with previous experience with these types of projects can set the stage for a well-framed engagement.
A focused session on your specific software applications, platforms, or projects. Typically this includes technical resources from both sides.