Case study · Digitization
Automation of Invoice Processing Workflow
A consulting company needed field employees to access equipment invoices, locate service centers, and repair damaged devices faster. iBoss digitized invoices and deployed high-performance intelligent document OCR systems to extract data, store it centrally, and automate lookup.
- Client
- A consulting company with field teams across India
- Disclosure
- Anonymised
Headline metrics
- 3 quarters of a minute
- Rejected extraction time
- Less than 5 seconds
- Final extraction time
Additional context
Automating invoice extraction and service-center lookup for field equipment repairs.
01 / Challenge
The problem in front of us.
Employees and consultants traveled across regional and international territories with DSLR cameras, laptops, tablets, scanners, printers, GPS devices, and other equipment. When gadgets were damaged, original invoices were unavailable, physical copies were hard for the office to locate, remote employees needed scanned invoices, and unfamiliar remote locations made authorized service centers difficult to find.
02 / Approach
How we set the work up.
iBoss designed and deployed high-reliability intelligent document OCR systems, extracting details and storing them in a centralized cloud repository. For extraction, iBoss tested object detection over a labeled invoice dataset, but that approach took three quarters of a minute. The team moved to OCR followed by Named Entity Recognition, reducing extraction time to less than 5 seconds.
03 / Solution
What we built.
The web application stores invoice information centrally and locates the nearest authorized service center based on the remote employee's geolocation, with options to connect by call or WhatsApp. The workflow uses OCR, NER, and a Selenium-trained model to find contact details and service-center locations.
04 / Outcome
What it has held up to.
The workflow automated the asset repair process, reduced the need for manual invoice searching, saved productive hours and days, stored extracted information in a common database, and enabled the client to use the data for critical decision-making insights.
Stack
What it runs on.
- OCR
- Named Entity Recognition
- Selenium
- Cloud repository
- Geolocation
- Web application
- Intelligent Document OCR Systems
Tell us what you're trying to ship.
We'll start with a two-week diagnostic. No slides, no promises we can't keep.