Case study: Canadian Institute of Mining,


Metallurgy and Petroleum

14,600 CIM members can finally find technical papers in an electronic library


  • Pingar saves years of manual reading and tagging/indexing for CIM library.
  • Pingar provides granular search refiners so users can find any document fast.
  • Pingar does the same work as 3000 employees.
  • Industry: Minerals, metals, materials and energy.

About CIM

Canadian Institute of Mining, Metallurgy and Petroleum (CIM) is the leading technical society of professionals in the Canadian Minerals, Metals, Materials and Energy Industries. CIM has over 14,600 members, convened from industry, academia and government. CIM has 10 Technical Societies and over 35 Branches.

About Pingar and its solutions

Pingar software enables organizations discover what content matters most to them. Our customers use our software to read millions of pieces of text from the web, social media, email and internal company documents. As it reads, it identifies the topics, places and things talked about and categorise and summarises the content.

We do this for organisations needing to manage, clean-up and find their content and for when they need to discover relationships and trends and issues inside text.

Our software uses advanced text analytics, developed by PhD educated experts. The volume of the information-rich text-based content is already overwhelming and growing at 60% each year1. With this amount of big data, traditional manual content searching and reading cannot be thorough or rapid enough – important facts for a business will be missed.

CIM’s challenge: Finding the right technical paper

CIMs electronic library accommodates tens of thousands of industry documents. For it to be useful to the members, search results need to be filtered by keywords or topics. In order to accomplish that, CIM needed to tag ALL documents with metadata EVERY single time.

These papers were written by professionals outside the organization and submitted to CIM. As good librarians, CIM employed someone to read and tag every single document that existed or was uploaded. However a typical document is around 20 pages of scientific and technical information. As such, they were able to read and tag only 180 documents per year. However CIM constantly adds thousands of documents a year to its library.

Pingar’s solution for CIM

Pingar allows CIM to handle thousands of documents a year without manual tagging in this case study. It identifies key terms that describe the main topics and categorizes documents against CIM’s taxonomies. Every document is read and tagged in a short period of time.

Pingar enables SharePoint’s search refiners. Using search refiners, members can quickly narrow their search to specific fields of interest and remove irrelevant papers from their search results. Members now find new documents within seconds

“It was the exact tool we needed to index documents. Now we are able to upload thousands of documents, and we don’t need to read every single one, because Pingar does it automatically.”

Gérard HamelDirector Information Systems and Technology

DiscoveryOne Content Enrichment

DiscoveryOne Content Enrichment automatically tags and categorizes content. Typically, it is used to improve findability of information in an Electronic Content Management System (ECMS) by enabling faceted search. It also improves the ability to categorize content against business classification schemes and document retention policies within an organization.