TERMS OF REFERENCE FOR AI INTEGRATION AND DECISION SUPPORT ENABLEMENT PROJECT - HIHEA/04-2026/ICT

Location of project: Nairobi

Type of contract: Consultancy

Period of implementation: 3 to 6months.

Type of Selection– Firm Only

Introduction of the organization

Hand in Hand Eastern Africa (HIH EA) is registered in Kenya as a Non-Governmental Organization (NGO). The organization started its operations in 2010 and it boasts 25 operative field offices in 33 counties out of 47 counties in Kenya. HIH EA is a member of the Hand in Hand Global Network that comprises affiliated organizations that mutually pursue the shared goal of poverty alleviation while supporting poorer communities to develop sustainable enterprises and jobs.

The organization strives to work with the marginalized communities in the areas of economic and social empowerment using a participatory approach aimed at supporting people to overcome poverty and vulnerability through development of sustainable enterprises.

Project Description

Hand in Hand Eastern Africa (HIH EA) operates established digital and operational systems supporting programme delivery, including data collection, training, and Learning Management Systems, savings group tracking, and reporting.

The organization seeks to improve operational efficiency, use data for decision making, and program impact by exploring and implementing Artificial Intelligence (AI) solutions, including but not limited to advanced analytics.

The proposed solutions will be an enhancement to the existing systems and not a replacement, augmenting

them with AI driven capabilities and automation layers

Objectives of the Assessment

The primary objectives of this consultancy are as follows:

• Review the existing business processes, needs and opportunities for AI implementation
• Conduct a data audit to verify availability, quality and governance structures
• Assess existing systems, data structures, and workflows
• Design and implement an AI-enabled integration layer
• Embed decision-support capabilities into current operational tools
• Introduce AI agents and automation to enhance both staff and beneficiary interactions

Scope of the Work

The selected vendor will deliver the assignment in a phased approach, aimed at enhancing existing systems through the integration of Artificial Intelligence (AI) capabilities. Each phase will focus on improving operational efficiency, enabling data-driven decision-making, and strengthening program impact through the application of advanced analytics and automation.

The implementation will build on current systems and processes without replacing them, introducing AI-driven functionalities as an augmentation layer.

Progression to subsequent phases will be informed by the outcomes, performance, and value demonstrated in the preceding phase, ensuring a scalable, low-risk, and results-oriented deployment.

Phase 1: Systems and Data Audit

Activities:

• Review existing systems and platforms currently in use
• Map system architecture, integrations, and data flows
• Identify key operational workflows and decision points
• Conduct a data audit (structure, quality, availability, gaps)
• Assess API availability and integration feasibility

Outputs:

• Systems architecture and integration map
• Data readiness and quality assessment
• Decision and workflow analysis
• Integration feasibility report

Phase 2: AI Integration Architecture Design

Activities:

• Design an AI integration layer compatible with existing systems
• Define API-based integration approaches
• Design data pipelines to support AI use cases
• Propose architecture for:

o decision-support systems

o AI agents (internal and external use)

o analytics and reporting layers

Outputs:

• Recommended tools/Proposed AI solutions document
• AI integration architecture document
• API and data flow specifications
• Technical design for AI components

Phase 3: Development and Integration

Activities:

• Develop and integrate AI modules into existing systems via APIs
• Implement decision-support tools, including:

o risk scoring and prioritization, models

o intervention recommendation systems

• Develop AI agent capabilities, such as:

o internal operational assistants (for staff)

o beneficiary-facing advisory tools (where applicable)

• Ensure interoperability with existing platforms

Outputs:

• Integrated AI-enabled system
• Functional decision-support modules
• AI agent interfaces and services

Phase 4: Deployment, Testing, and Optimization

Activities:

• Deploy solutions within existing infrastructure
• Conduct system testing (functional, performance, and reliability)
• Optimize models and integrations based on real-world usage
• Establish monitoring and evaluation mechanisms

Outputs:

• Production-ready AI-enabled system
• Performance and evaluation reports
• Monitoring framework

Phase 5: Training and Knowledge Transfer

Activities:

• Train technical and operational staff
• Provide documentation for system use and maintenance
• Support transition to internal ownership

Outputs:

• Training materials and sessions
• Technical and user documentation
• Handover package

Deliverables

The selected vendor will deliver:

• Methodology & work-plan for the assignment
• AI integration feasibility report.
• Systems and data audit report
• AI integration architecture and technical design
• Integrated AI-enabled modules within existing systems
• Decision-support tools and AI agent capabilities
• Training, documentation, and handover materials

We expect the consultancy firm to demonstrate the skills and experience outlined below (or equivalent):

Bidders shortlisted to the next stage of the procurement process will be required to provide a technical

demonstration of their capabilities.

Requirements:

Shortlisted bidders must present:

• A demonstration of a previously developed AI-enabled platform or system
• Relevant system architecture, including:

o data pipelines

o model integration

o API-based system integration

• Expl