Basic Information

Reference Number

00002493225

Issuing Organization

Ontario Shared Services

Solicitation Type

NPP - Notice of Proposed Procurement (Formal)

Solicitation Number

Tender_13890

Title

Project: tender_13890 - Artificial Intelligence Solution to Extract Table Data from Documents

Source ID

SCRIBE

Details

Location

Ontario

Purchase Type

Not Stated

Dates

Publication

2021/02/03 11:39:00 AM EST

Closing Date

2021/03/31 02:00:00 PM EDT

Prebid Conference

2021/02/18 02:00:00 PM EST

Contact Information

Laxmi Gautam

laxmi.gautam@ontario.ca

Marty Marini

Marty.Marini@ontario.ca

Description

The Ministry of Labour, Training and Skills Development (MLTSD) would like to procure a Software as a Service (SaaS) solution for an Artificial Intelligence (AI) Solution to Extract Table Data from Documents (the Solution).

MLTSD provides neutral dispute resolution assistance to encourage and foster labour relations stability in the province. It also provides neutral labour relations information, research, and analysis to inform decision-making, and promotes and supports labour relations best practices and constructive labour-management relationships. Parties (such as Ontario employers and trade unions) involved in Collective Bargaining Agreements are required to file their agreements with MLTSD. The Ministry stores these documents in an online e-Library that is accessible to the public. The e-Library contains over 60,000 agreements with approximately 5,000 added each year.

MLTSD would like the ability to extract relevant tables from these documents using machine learning and natural language processing methods. This data will contribute to evidence-based decisions and will support the broader labour relations community in collective bargaining negotiations, research, and analysis. The data will also be leveraged to drive policy through evidence-based decision making.
Scope of Work
Currently extracting any table data from scanned, PDF files is difficult, time consuming, and labour intensive due to document volume and wage schedules or tables which greatly differ between documents and industry sectors.

Given the document volume, a large-scale extraction can be accomplished with the assistance of machine learning and natural language technology and will provide for a leaner government.

An AI platform would help the Ministry extract table information from scanned documents more efficiently.

The vision is that the Solution will enable the Ministry to perform the following:
• Document classification
• Automatic Table Extraction
• Automatic Wage Standardization
• Ability to teach / train the system to extract new table data as they are introduced
• Ability to teach / and train the system to standardize new wage data as they are introduced

Bidders interested in responding to this RFB are encouraged to attend an informational session that will be held on:
February 18, 2021 from 2:00 to 3:30 p.m. EST (Toronto Time)
Interested Bidders should R.S.V.P. by February 17, 2021 via e-mail to Marty Marini with your contact information to receive the webcast link and teleconference number with the pass code.

Pre-Bidding Events

Event Type

Prebid Conference

Attendance

Recommended

Event date

2021/02/18 02:00:00 PM EST

Disclaimer All amendments to the associated notice, including amended documents, plans and specifications (where applicable), are issued by the originator of the notice. MERX asks you to contact the buying agency directly for these amendments. MERX stipulates that potential bidders may also be required to register with the buying authority as a bidder/plan taker. The contact information can be found within the main tender document and/or on this notice abstract.

Toutes les modifications associées à cet avis d’appel d’offres ainsi que les documents, les plans et les spécifications sont générés par l’entité responsable des achats (l’acheteur). S’il vous plait, contactez-le directement pour les addenda. Veuillez notez qu’il se peut que les fournisseurs soient obligés de s’inscrire directement avec l’acheteur. Vous pouvez trouver leur coordonnées dans le document principal ou dans l’abstrait de l’avis d’appel d’offre.

Source: https://ontariotenders.app.jaggaer.com/