Alluvium

Enhancing Invoice Data Extraction with AI Integration

The Alluvium project centers around the extraction of text invoice data from various unstructured client invoices in the form of PDFs and images. These documents could range from scanned documents to forms, and other relevant sources. To achieve this, the project has been integrated with AWS and Azure Cloud platforms, from where the PDF and image source files are fetched.

The project's primary objectives include:

Accurate Data Extraction: Developing a system that can precisely extract specific data elements such as invoice details, shipment details, and customer information from PDF images.

Structured Data Conversion: Converting the extracted data into a structured and machine-readable format, enhancing the usability and accessibility of the information.

Error Minimization: Utilizing AI model training and validation processes to minimize errors and inaccuracies in the data extraction process.

Benefits to the Clients

Upload a Financial Document

Upload the digital documents in any format PNG, PDF, DOC, XLS, etc.

File Storage & processing

Store the original copy of the document in the file system or the cloud.

Extract & validate

Perform the data extraction using NLP. Do the necessary prediction or self-correction wherever required Apply the business validation & rules which are applicable.

Choice of Output

Create the output in the desired format and store it in the database of choice.