Case studies

The client provides an AI for quick service restaurants (QSR) restaurants that uses a custom NLP system to interpret natural customer speech and convert it into structured, kitchen-ready orders. The menu-aware NLP system handles complex, brand-specific menus with customizable combos, modifiers, and promotional items. It recognizes varied phrasing, synonyms, and marketing terms, and maintains contextual awareness across multi-turn conversations. The AI-driven order automation system supports slot filling, multilingual input (English and Spanish), real-time menu updates, and upselling logic.

We built an AI-powered Knowledge Assistant for enterprise resource planning provider, delivering instant, accurate answers to complex queries. It uses NLP, vector search, and contextual understanding to integrate with knowledge bases and enhance customer experience. Our client is a leading provider of enterprise digital transformation solutions for various sectors, with a strong focus on the financial industry as well as manufacturing, distribution, and retail. Their offerings include tools for managing supply chain operations, financials, production, and customer relationships. They requested us to develop an LLM-based chatbot for internal documentation and ERP knowledge that gives users quick access to information about the company’s products and services. It uses a detailed database of presentations, documents, and common questions to provide fast and accurate answers to inquiries, helping their client to get a comprehensive consultation without the need to wait for a response from sales team members.

In this case study, we developed a sophisticated ticket sales prediction system designed to evaluate the potential success of events using advanced data analytics. The system generates insights based on historical data, audience sentiment, and economic factors, providing actionable outputs.

A private research organization focused on evaluating the safety and effectiveness of medications. Their goal is to use advanced medical data analytics and data harmonization in healthcare to support healthcare decisions and meet regulatory standards. For this project, they aimed to assess the safety of hydroxychloroquine, used alone or with azithromycin, for treating rheumatoid arthritis. The study focused on identifying short-term side effects and long-term risks, especially related to heart health and the use of multiple medications together. The client needed a data-driven approach, similar to methods used in federated healthcare data platforms, to fill gaps in existing evidence by combining different clinical data sources and applying patient similarity networks for clinical decision-making to identify patient groups with similar characteristics and address factors that could affect treatment outcomes.

The client is a healthcare company focused on medical imaging and diagnostics, working to improve the diagnosis of lung diseases like tuberculosis and COVID-19. They wanted to create an AI for chest X-ray analysis for lung disease detection to spot abnormal changes and automatically prioritize the most urgent cases. The healthcare automation platform functions as an automated radiology triage system using deep learning, identifying abnormalities and highlighting critical cases to make diagnosis faster and more accurate. It supports reducing radiologist workload with automated image analysis by handling routine tasks, allowing specialists to focus on complex cases. By solving issues like delayed diagnoses and heavy workloads, the automated diagnostics system ensures patients with serious conditions get quicker and more reliable care.

Our client in the corporate EdTech sector developed one of the AI-powered personalized learning platforms for corporate training that aggregates business courses for easy access and management. They sought an automated system to categorize courses into areas like marketing, finance, and HR, and to recommend personalized learning paths based on each employee's role and career goals, enabling a data-driven learning transformation across the organization. Read on to learn about our ML solution that transforms course categorization and tailors personalized recommendations.

Our solution uses advanced Natural Language Processing (NLP) and Machine Learning (ML) to automate the extraction of detailed specifications and measurements from complex product spec sheets. The client is a company in the manufacturing industry that provides advanced technology solutions to improve and simplify production processes. They needed a sophisticated system to manage various types of documents, such as spec sheets, technical manuals, and product datasheets.

Jackalope automates transforming complex medical data into standardized formats of OMOP CDM and SNOMED Clinical Terms (CT). This enables healthcare providers, practitioners, and scientists to effectively use real-world evidence (RWE) in healthcare for research and delivering enhanced patient care.