Ets Izysoft
Automated Document Intelligence with AI: Enhancing information extraction for a SaaS startup in Yaounde
1. Business context for the client
Our customer, a leading company in document intelligence, specializes in developing solutions for automatically extracting structured information from unstructured document bases. Their goal is ambitious: to harness AI for seamless extraction of critical data from complex documents like invoices and balance sheets. To support this vision, the company aims to enhance their platform with a robust, automated module capable of capturing and organizing knowledge from a variety of financial documents with high precision. This strategic advancement aimed to revolutionize their platform, making it more efficient and aligning with their commitment to delivering cutting-edge document intelligence.
2. The AI / data challenges faced here
Invoices and balance sheets are notoriously difficult to process due to their unstructured nature and varying layouts. Specifically, extracting relevant data from these documents required an AI solution that could interpret not only the textual content but also the geometric positioning of each element on the page. Additionally, the company needed a way to organize this extracted information into structured categories defined by their customers.
Without automation, the company faced time-consuming, manual data extraction processes that hindered scalability and accuracy. These challenges prevented them from offering clients a streamlined solution for document-based knowledge retrieval, which is crucial in fields requiring extensive data verification and compliance checks.
3. How Bubo helped on this
Bubo collaborated with the company to deploy a customized AI-powered solution focused on three main functionalities: text and coordinate extraction, document classification, and information reconciliation.
- Text and coordinate extraction: Leveraging advanced computer vision models, Bubo enabled our customer to capture both the textual data and spatial coordinates of each word within a document. This dual-layer extraction facilitated precise interpretation of the document’s content and layout, a critical step for accurately processing complex forms and layouts in invoices and balance sheets.
- Document classification: To streamline data processing, Bubo developed AI models capable of automatically classifying documents based on client-specific categories. This classification reduced processing time by routing documents through specialized pipelines, ensuring that each document type received tailored extraction and analysis.
- Key-Value Pair (KVP) extraction and information reconciliation: Using sophisticated AI models, Bubo tackled the intricate task of KVP extraction. These models were trained to identify and extract essential pieces of information (such as dates, amounts, and descriptions) from each document. The final step involved reconciling and organizing this data into structured formats, which were then stored in indexed databases, enabling fast, efficient information retrieval.
4. Results
The partnership led to significant, measurable outcomes:
- Automated extraction reduced manual data processing time by ~60%, enabling the company’s clients to access critical information faster.
- The solution achieved a ~90% accuracy rate in data extraction from invoices, ensuring reliability and reducing errors.
- The company could now handle larger document volumes, processing up to ~2000 documents per day with ease.
- The organized, indexed data structure improved information retrieval, offering clients a seamless experience and supporting better decision-making processes.