Aike

Aike provides an artificial intelligence platform that enriches real-time purchase data by combining it with a wide array of other data types, including geolocation, demographic, behavioral, and psychographic information. The company's technology utilizes a proprietary AI platform to map merchants, categories, and segments, enhancing raw data for high-value vertical solutions. At its core, Aike's merchant engine employs machine learning embeddings and a high-dimensional vector database to analyze both structured and unstructured debit/credit and merchant data. This system is designed to identify sales trends and evaluate brand health with high scalability and resilience. The company is also exploring the use of Large Language Models (LLMs) to improve the search functions of its merchant system.

For consumer profiling, Aike uses a variety of algorithms such as Random Forests, Neural Networks, and K-means Clustering. This allows the platform to analyze complex consumer data formats like images, text, and sequences to identify key patterns and variables for detailed customer segmentation. Another key offering is the Web Content AI engine, which is a foundational text mining model enhanced by bank and retailer transaction data. This engine connects real-time transactions to online content to create, optimize, and personalize marketing materials. It generates content like social media posts, blog articles, and ad copy tailored to specific brands and products.

The platform also features an Emotional AI component that analyzes customer sentiment from social media, reviews, and news articles, validating these insights against real-time transaction data. This helps businesses understand customer perception and make data-driven decisions to refine campaign strategies and manage brand reputation. Furthermore, Aike's AI-powered engine delivers real-time industry trend briefings and competitor insights, leveraging proprietary data and knowledge graphs to provide actionable intelligence for strategic decision-making.

Keywords: consumer data enrichment, purchase data analysis, AI platform, consumer profiling, machine learning, merchant engine, brand health assessment, large language models, web content AI, generative AI, emotional AI, sentiment analysis, marketing content creation, real-time analytics, competitor insights, customer segmentation, data-driven marketing, transaction data, behavioral analytics, psychographic data