Our customer is a SaaS low-code tool that allows to develop internal tools using existing data. The platform offers numerous combinations, instructions, and other documentation that guide users on how to operate it. However, due to the complexity of the tool, customers often face challenges during onboarding, leading to a significant number of clarifying questions directed to the low-code tool staff. As a result, the need for manual assistance and guidance increases substantially.

Enhance customer loyalty

To reduce manual work of support and engineering team

Increase customer retention and product involvement

We gathered relevant documentation and resources for the low-code tool, creating a knowledge base for the AI assistant. Using ChatGPT-4, we trained the model specifically for our customers product, fine-tuning it with product-specific examples. We integrated the trained model into the low-code platform and continuously monitor its performance. User feedback helps us improve the assistant by updating training data and retraining the model. We accomplished the entire scope and released a Beta version in just one month.

Our customer from New Zealand brings over 35 years of expertise in developing, manufacturing, and testing fire protection equipment. Their objective was to automate the extraction of categorized data from a collection of PDF documents and seamlessly import it into the Chat feature on their website for customers. This initiative aims to enhance efficiency, eliminate manual searching, and ultimately establish an interactive system.

Enhance customer experience

Enhanced accessibility for equipment instructions.

Increasing customer loyalty

We used NLP techniques to parse PDF documents and extract relevant data. The extracted data was utilized to train a ChatGPT-based chatbot, enabling it to understand and respond to user queries regarding equipment instructions. By integrating with chatbot, users can conveniently access and interact with the instructions in a conversational manner, enhancing their overall experience and convenience.

Our customer - Medical Center in Spain aimed to provide patients with an efficient and reliable way to check their symptoms and obtain initial guidance through an AI assistance chatbot symptom checker

Patient inquiries overload, longer wait times, and diagnosis delays.

Limited healthcare professionals, increased workload, potential errors.

User-friendly, accessible tool for remote patient use.

Utilizing NLP techniques and a comprehensive medical knowledge base, we developed an AI chatbot symptom checker. Patients could describe their symptoms, receive personalized guidance, and access it conveniently through the medical center's website and app.

The chatbot improved patient experience by reducing wait times and offering initial insights. It enabled efficient triage, increased accessibility, and enhanced workflow for healthcare professionals, resulting in improved healthcare outcomes and patient satisfaction.