Development of an Ai-Assisted Ocr and Nlp Solution for a Health Management Information... Tender

WORLD HEALTH ORGANIZATION (WHO) has floated a tender for Development of an Ai-Assisted Ocr and Nlp Solution for a Health Management Information System in a Resource-Limited Setting. The project location is Philippines and the tender is closing on 13 Oct 2025. The tender notice number is WPRO/2025-09/DSI/279880, while the TOT Ref Number is 127293095. Bidders can have further information about the Tender and can request the complete Tender document by Registering on the site.

Expired Tender

Procurement Summary

Country: Philippines

Summary: Development of an Ai-Assisted Ocr and Nlp Solution for a Health Management Information System in a Resource-Limited Setting

Deadline: 13 Oct 2025

Other Information

Notice Type: Tender

TOT Ref.No.: 127293095

Document Ref. No.: WPRO/2025-09/DSI/279880

Financier: World Health Organization (WHO)

Purchaser Ownership: Public

Tender Value: Refer Document

Purchaser's Detail

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Tender Details

WHO is seeking for a qualified, eligible and competent proposer for the Development of an AI-assisted OCR and NLP Solution for a Health Management Information System in a Resource-Limited Setting. The objective of the contract is to design, develop and deploy an artificial intelligence (AI)-assisted solution that digitizes hand-filled health facility reporting forms into the DHIS2-based health management information system (HMIS) in a limited resource setting country, with built-in data validation, decision-support features, and robust data security safeguards ensuring confidentiality and internal retention of sensitive health information.Most limited resource setting countries rely heavily on paper-based reporting at the facility level, including monthly service reports, birth notifications, and medical certification of cause-of-death forms. Manual transcription into DHIS2 is time-consuming, error-prone, and delays data availability for decision-making.Advances in AI, optical character recognition (OCR), and natural language processing (NLP) now make it feasible to automate digitization of handwritten forms. However, due to the sensitive nature of personal health data, it is critical that solutions adhere to strict data security and confidentiality standards, ensuring data remains internal to Ministry of Health systems and protected against unauthorized access.This project therefore aims to:Improve timeliness and accuracy of HMIS disease surveillance dataReduce workload...
Publish Date: 30-Sep-2025
UN Orgnization: WORLD HEALTH ORGANIZATION (WHO)
Type of Notice: Request for proposal

Documents

 Tender Notice


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