tex.tracer has introduced AI-Powered Document Scanning in platform to streamline the process of uploading certificates and audits. This feature uses a combination of Optical Character Recognition (OCR) and AI-based field extraction.
How it works
Our AI pipeline follows these steps:
Ingest the document (PDF)
Enhance and scan the file using OCR
Analyse the content using the AI model Gemini 2.5 Flash
Identify key fields using Natural Language Processing (NLP)
Pre-fill form fields in your tex.tracer workflow
Validate the results and expose the output via secure APIs
If you wish to not use AI, you can choose to upload manually.
On our decision for Gemini 2.5 Flash?
After an extensive internal evaluation of various large language models (LLMs), we selected Gemini 2.5 Flash for its strong performance:
Built-in intelligent document processing (IDP) that eliminates the need for separate OCR services
Faster output to process documents quickly and reduce wait time
Supports over 100 languages
High accuracy and better structured output for critical fields like addresses, dates, and IDs
How we handle your data
We know how important your data is. That’s why we’ve taken extensive measures to ensure security and compliance:
Data encryption: all data is encrypted at rest and in transit.
Secure API access: we use OAuth2 and JWT for secure integrations.
GDPR compliance: we comply with global data protection laws.
Data retention limits: document data processed by the Gemini model is stored only for up to 48 hours and not used for model training.
Zero retention options: for sensitive workflows, we can configure retention policies using compliant infrastructure.
Our commitment to energy efficiency
We are mindful of our environmental footprint. This feature has been designed with efficiency in mind—and we will continue to develop it to minimise energy usage wherever possible. By reducing unnecessary reprocessing and using efficient model configurations, we aim to balance innovation with sustainability.
Your feedback matters
This rollout is part of our ongoing mission to simplify and automate certification workflows. But automation is only as good as its outcomes, which is why your feedback is crucial.
After each document is scanned, you’ll see a simple thumbs up / thumbs down option. This allows you to rate the accuracy of the extracted data.
These ratings help us identify gaps, improve performance, and retrain the model where needed. It’s part of our continuous learning loop to make tex.tracer smarter with every document it processes.
Still have any questions about how your data is handled during this process? Please reach out to tex.tracer support, we’re always here to help.
Need more help? You can get in touch with us via chat or contact us via email at [email protected].