Enterprise software for automating your information management processes.
Pingar combines the human intelligence of our expert team with the artificial intelligence of our powerful software to deliver elegant, well designed information management solutions.
Pingar helped Auckland Transport find the way.
Auckland Transport has adopted Pingar auto-classification delivering findability and retention and disposal
for information lifecycle management across their entire SharePoint and Office 365 environment.
“We have embarked on an innovative road trip
to manage our information in an automated way
different from the traditional EDRMS option’’
Corporate Information Manager, Auckland Transport
Our team are committed to delivering
My aim is to make the information hunt in electronic documents faster and more efficient. I work on developing and evaluating text mining systems – both algorithms and user interfaces.
I have experience in identifying information for database annotation, entity extraction and entity relations extraction from text, summarization, document clustering and categorization as well as identifying useful features in computer interfaces that allow end users to communicate efficiently with text mining systems
Dr Anna Divoli
For the past 20 years I have been researching the automation of information governance practice. I use my experience in building taxonomies and ontologies to design better software and systems.
I want to utilise data design to change the way we manage information governance: all roads point metadata management, information architecture and system design.
We’ve embarked on a revolutionary journey to automate enterprise records management.
We believe we are the first company globally that can deliver a product that can auto-appraise millions of documents based on the context, relevance and significance of their individual content.
I’m passionate about pushing our deep understanding of text mining to extract context from documents, combined with our human intelligence to create new data models that enables machines to be records managers.
Chief Executive Officer
My background is in data analysis and statistical modelling of big cosmological simulation data.
After I finished my doctorate I expanded my data science knowledge to transform insights into actionable guidelines, and to enable interaction with users via web technologies.