AI-powered contract extraction for a travel company

Challenge

Our customer, a mid-size B2B travel company, manages numerous direct hotel contracts. These contracts were manually uploaded into the Extranet system used for managing inventory, rates, and availability.

The manual process was slow, resource-intensive, and prone to errors. Accuracy issues in contract data created further inefficiencies downstream.

The company needed a faster and more reliable approach, and the automation project had to be delivered under a very tight deadline.

Business goals

The project aimed to:

• Reduce reliance on manual data entry for contract extraction

• Speed up the loading of frequently used contracts

• Improve data accuracy

• Lower operational risk associated with errors in contract handling

Solution

The high-level process

To optimize contract handling, we built a system combining a web interface, AI-powered extraction service, and integration with the Extranet.

Web interface and backend solution

Allow users to:

• Upload contract files

• View and select previously uploaded contracts

• Trigger AI-based data extraction for a selected contract

• Review and manually edit extracted data after processing

• Choose from available extraction templates and re-run extraction when needed

• Save and reuse extraction templates for recurring contract formats

AI data extraction service

Handles the full cycle of contract recognition and data capture:

• OCR conversion: Transforms PDF contracts into text for further processing

• Contract clustering and template storage: Groups similar contracts and stores reusable templates

• Template matching: Identifies the correct template for each contract using text analysis and matching algorithms

• Field extraction with LLMs: Uses ChatGPT guided by predefined templates to extract required fields, accounting for variations across documents

• Post-processing: Reviews and corrects ChatGPT outputs to handle errors and inconsistencies, ensuring clean data

Extranet integration

Validated contract data is sent directly to the Extranet database, reducing manual effort.

Technology stack

• Backend: .NET C#

• Frontend: Angular + PrimeNG

• Database: PostgreSQL

• Data extraction: Python, ChatGPT API, Google OCR API

Results

Within the first rollout phase:

• Contract loading time became 4-5 times faster compared to manual processing

• Data accuracy improved by 80%, reducing the need for corrections

• Workload for staff dropped by 80%, freeing them for complex tasks

• Onboarding time for new contracts cut from weeks to days, improving time-to-market for new hotel offers

Conclusion

For a travel company dealing with large volumes of hotel contracts, AI-powered automation proved to be a strong efficiency driver. It reduced repetitive work, improved accuracy, and accelerated contract onboarding — delivering both short-term ROI and long-term scalability.