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Girl Effect

Request for Proposal Evaluation of the WAZZII Chatbot Digital Health and AI Evaluation, Kenya

Kenya

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hirly's read of this role

Seniority
Mid level
Country
KE
Work mode
On-site / unstated
First seen by hirly
15 Oct 2026

Derived automatically from the posting. Upload your resume above to see how the role scores against it.

the posting

Who We Are

Girl Effect is an international non-profit that builds media and technology that girls want, trust and need.

We use youth-centred design and behaviour-change approaches to help adolescent girls and young women access trusted information, services and support and make informed choices about their health and futures.

Background

Girl Effect is implementing three programmes in Kenya that use WAZZII, its digital chatbot, alongside multimedia, community engagement and service linkages to improve access to sexual and reproductive health (SRH) and maternal and newborn health (MNH) information and services.

MSD 4.0: Nairobi and Nakuru, focusing on maternal and newborn health.

Tukisonga 2.0: Nairobi and Nakuru, focusing on SRH among adolescent girls and young women (AGYW) aged 15–24, including contraception, DMPA-SC/self-injection, heavy menstrual bleeding and STIs.

AI Mobiliser: Nairobi, focusing on AI-enabled SRH information and support to facilitate informed decision-making and progression to contraceptive services.

Girl Effect seeks an independent research partner to evaluate WAZZII across the three programmes, assessing user experience, AI performance and safety, behavioural outcomes, equity and progression from digital engagement to service uptake.

Evaluation Purpose and objectives

The evaluation will assess WAZZII’s performance, usefulness and safety, and its contribution to SRH/MNH outcomes and service pathways.

Specifically, it will:

Assess reach, engagement, repeat use and user experience.

Evaluate AI accuracy, reliability, trust, safety and handling of sensitive or higher-risk situations.

Examine associations between chatbot use and knowledge, confidence, intentions and service-seeking.

Assess referrals, completed referrals and service uptake.

Identify differences in access and outcomes across user groups.

Generate recommendations to improve product performance, safeguarding, service linkages and cost-efficiency.

What You will do

Evaluation design and analytics

Develop an evaluation protocol, indicator framework, sampling strategy and analysis plan. Review chatbot analytics to assess user characteristics, engagement, repeat use, conversation patterns and drop-off points. Map the pathway from programme exposure and chatbot engagement to human support, referral and service uptake.

Integrate platform analytics, user surveys, qualitative research and available referral/service data. Where feasible, follow chatbot users over time. Clearly document data gaps, selection bias and limitations to attributing outcomes to chatbot use.

AI performance, safety and user experience

Assess WAZZII’s accuracy, reliability, relevance, comprehension, accessibility, privacy and trust. For AI Mobiliser, conduct structured testing of representative SRH questions, including contraception, DMPA-SC/self-injection, sensitive disclosures, misinformation risks and referral information.

Review available AI performance monitoring, safeguarding alerts, failure records and escalation processes. Assess whether inappropriate responses and higher-risk situations are identified and managed correctly. Apply the existing 22-metric Product-Level Scorecard where appropriate.

Use user surveys, interviews or usability sessions to identify barriers and opportunities for improvement.

Equity and digital access

Assess whether users with different levels of digital access can engage with and benefit from WAZZII. Consider shared-device access, connectivity, digital literacy, privacy, language, disability and geography.

Analyse differences in engagement, experience, referral and outcomes by relevant user characteristics, where data permits. Examine how chatbot use interacts with multimedia, community mobilisation and human support, particularly within AI Mobiliser.

Behavioural outcomes and service pathways

Assess reported knowledge, confidence, decision-making, intentions and service-seeking using programme-relevant measures.

For AI Mobiliser, examine progression along the contraceptive-care pathway, including referrals offered, completed visits and service uptake.

Use referral codes, provider records, voucher redemption or other approved verification methods where available.

Clearly distinguish verified service uptake from self-reported uptake.

Where feasible, assess outcomes by engagement intensity and combinations of programme exposure. Any claims about effectiveness must be supported by the evaluation design; associations should not automatically be interpreted as causal effects.

Analysis and recommendations

Triangulate findings across analytics, AI testing, user research and service data..

Identify priority improvements in AI safety, product design, accessibility, referral systems and programme implementation.

Deliverables

Inception report, evaluation protocol and indicator framework.

Analytics review and user-journey map, including data gaps.

User research tools and AI performance and safety assessment framework.

Required ethics approvals and research authorisations.

Clean, de-identified datasets, codebooks and analysis syntax, subject to data governance requirements.

Draft and final evaluation reports, including findings on user experience, AI performance, safety, outcomes, equity and service uptake.

Prioritised recommendations and presentation of findings to Girl Effect.

Duration and Management

The assignment will cover evaluation design, data-feasibility assessment, product analytics, AI performance and safety testing, participant research, service-pathway analysis and reporting.

All final deliverables must be completed and accepted by 31 December 2026 .

The agency will report to Girl Effect’s designated Evidence and Insights focal point and work closely with the relevant product, programme, safeguarding, operations and country teams.

Any risk to the agreed scope, quality, budget or final deadline must be reported immediately with a proposed mitigation plan.

Who You Are

Required expertise

The research partner should demonstrate experience in digital health or AI evaluation, mixed-methods research, usability testing, digital analytics, AI safety assessment, SRH/MNH, safeguarding and research ethics.

Experience conducting research in Kenya and measuring referral and service uptake is essential.

Proposal Submission

Invited agencies must submit separate technical and financial proposals.

The technical proposal should not exceed 10 pages, including CVs, references, company documents and supporting evidence.

Technical Proposal

The technical proposal should include:

Evaluation design, sampling, and analysis approach.

AI performance and safety testing methods.

Methods for measuring user experience and service uptake.

Ethical considerations and data-protection measures.

Team composition and relevant experience.

Ethics, safeguarding, privacy, security and data-governance approach.

Detailed work plan demonstrating completion by 31 December 2026.

Three comparable assignments.

Three contactable client references.

Financial Proposal

The financial proposal must be submitted in Kenya shillings and include:

A detailed fixed-price budget by phase and deliverable.

Personnel roles, professional rates and level of effort.

Applicable taxes shown separately.

Proposed reimbursable expenses shown separately.

Clear assumptions, dependencies, exclusions and conditions.

Prices must remain valid for 90 days from the proposal deadline.

Any cost not expressly excluded or identified as conditional may be treated as included in the proposed fixed price.

Evaluation Criteria

Proposals will be evaluated in the following order:

Pre-screening

Technical evaluation

Financial evaluation.

Evaluation Criterion

Understanding of WAZZII and the programme and evaluation requirements: 10%

Evaluation design, sampling, outcomes and service pathway

Original posting on Girl Effect's site ↗

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