Data Extraction
Transforming Information Into Innovation
- Structured data from unstructured sources
- Source can be PDF, emails, websites, images, handwritten documents, etc.
- Build and optimized in close collaboration with you using AI technology and machine learning
- Data can be delivered in any format
- No technical knowledge required
Our Expertise With AI Models
Use Our Expertise To Use AI Models In Your Organization
- We build custom AI models for your specific use case
- Always a dedicated team of experts to help you with the entire process
- After the initial setup, this is a fully automated process
- We help you from data collection to model training and deployment
Common Use Cases
Streamlining Contract Management
Companies often deal with numerous contracts stored in unstructured PDF formats. Data extraction technologies can be employed to systematically extract key elements like dates, terms, parties involved, and obligations from these documents. This facilitates efficient contract management, ensuring compliance, timely renewals, and risk mitigation. It also allows for quick retrieval of specific contract details, enhancing decision-making and operational efficiency in legal and procurement departments.
Enhanced Customer Support
Text extraction technology can be utilized to analyze customer inquiries, emails, and support tickets, enabling companies to identify common issues, customer sentiments, and trends. This can significantly improve response times and personalize customer support, leading to increased customer satisfaction and loyalty. By automating the categorization and prioritization of incoming queries, companies can allocate resources more efficiently and enhance overall customer service quality.
Improved Data Entry
Data extraction technologies can be used to automate the manual process of entering data into company systems. By extracting information from various sources such as forms, invoices, and emails, these technologies can significantly reduce the need for data entry staff. This not only speeds up the process but also minimizes human errors. As a result, employees can be reallocated to more strategic tasks, enhancing productivity and innovation within the company. This approach also accelerates data processing, leading to more timely and accurate business insights.
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