Efficient Data Analysis: How GenAI Makes Unstructured Data Usable

From Unstructured Data to Actionable Insights

Images, user comments, reviews—the amount of unstructured data is growing exponentially. Companies face the challenge of processing this data efficiently and fully unlocking its potential. But how can objective information be extracted from millions of images or texts? Manual processing is often time-consuming, error-prone, or simply impossible.

At Ubilabs, our team has developed a GenAI-powered approach that automatically translates unstructured data into machine-readable formats. This allows businesses to categorize, analyze, and enrich their data with metadata—in a fraction of the time required by traditional methods.

Our approach follows a structured process to ensure that unstructured data is pulled directly from the customer’s existing data sources. This data is fed into the AI, where it undergoes a multi-stage analysis process. A key step is grounding: the AI cross-references generated information with external sources to deliver more accurate results. Our tested prompts ensure that the data is processed precisely according to the customer’s specific requirements. The machine-readable outputs are rigorously defined, enabling seamless integration into existing systems.

From Image to Text in Seconds

A key use case of our approach for extracting new information from unstructured datasets is the generation of precise contextual information from image data. Each image is analyzed and translated into structured, machine-readable information. In a proof of concept (PoC), we focused on two key industries:

Real Estate: Descriptions Directly from Photos

Real estate photos are a valuable source for capturing the condition, features, and unique characteristics of a property. Our GenAI approach analyzes these visual details and transforms them into automated, precise, and consistent text descriptions. These texts include all the relevant information needed for listings—from room layouts and property condition to special features like high-quality flooring or modern heating systems. This process not only saves time for real estate agents and property platforms but also enhances the consistency and quality of their listings. As a result, they can respond to customer inquiries faster and provide better information to potential buyers.

E-Commerce: Product Descriptions Without Manual Effort

For online shops with large product catalogs, manually creating product descriptions is a resource-intensive and time-consuming process. Often, there’s a lack of capacity to describe the vast number of products promptly and consistently. Our solution addresses this challenge: by analyzing product images and automatically filling in missing details through grounding, our approach generates consistent and compelling text. This not only significantly speeds up data maintenance but also improves the quality of product descriptions. Businesses can manage their product catalogs more efficiently, create consistent customer experiences, and enhance their competitiveness. At the same time, this reduces internal workloads and minimizes errors commonly associated with manual work.

Our PoC demonstrates how GenAI transforms unstructured image data into valuable, machine-readable texts and information. Our multi-stage approach—from data extraction and AI-powered analysis to clearly defined output—is both scalable and flexible, making it adaptable to various data sources and applicable to numerous use cases.

Technical Background: Transparency and Flexibility

The core of the project is an architecture that unifies all process steps—from data input and processing with AI models to integration into existing systems.

Key components of our approach:

• Fixed, Scalable Framework: Unstructured data is extracted from the customer’s existing data sources and fed into the AI, where it undergoes multi-stage analysis.
• Validated Prompts: Our custom-developed prompts ensure the AI generates precisely the type of information needed for the specific use case.
• Multimodal AI Models: Our GenAI solutions process not only images but also texts, user reviews, and potentially even audio in the near future.
• Grounding: The AI connects results with external data, for example, by matching them with information from the web.
• Precision and Scalability: Unlike manual approaches, the quality of results remains consistently high, even with very large datasets.
• Machine-Readable Outputs: The output format is strictly defined, enabling direct processing by machines. This ensures seamless integration into existing business processes.

More Than Just Data Analysis

With the growing availability of technologies like GenAI, it’s becoming easier for businesses to make unstructured data usable. Whether it’s images, reviews, or texts—Ubilabs helps companies seamlessly integrate AI into their existing business processes. This not only automates workflows but also optimizes them to reduce costs and accelerate operations.

While GenAI has primarily been used for generating new texts, images, and sounds, we are fundamentally expanding its applications. We leverage AI specifically to systematically analyze unstructured data and transform it into structured datasets. This innovative approach creates a new level of integration and processing, enabling companies to make their data processes more efficient and powerful.