Finland – OpenEval: AI-Assisted Platform for Evaluation Evidence – Case Study
Finland – OpenEval: AI-Assisted Platform for Evaluation Evidence
What is Finland's OpenEval platform?
OpenEval is an AI-assisted, open-access platform developed by Finland's Ministry for Foreign Affairs (MFA) to capture, organize, and make accessible evaluative evidence from development co-operation evaluation reports. Launched in 2025 by the Ministry's independent Development Evaluation Unit, it allows users—including civil servants, stakeholders, and the general public—to search across multiple reports simultaneously using keywords, extracting relevant evidence in seconds. The platform addresses the challenge of scattered and underutilized evaluative information, supporting decision making, transparency, and organizational learning.
Why did Finland develop OpenEval?
The Finnish MFA recognized that findings from regular and systematic evaluations were scattered across hundreds of documents, and textual evidence was often underused. This fragmentation limited users' ability to extract insights for decision making, learning, and accountability. Traditional manual extraction was time-consuming—an advanced user takes approximately 20 minutes to search and extract 100 results. The MFA sought to leverage AI to make evaluative evidence more accessible, efficient, and impactful, aligning with broader government digitalization and AI adoption goals. The project was also informed by international developments in AI and prior MFA pilots using Natural Language Processing (NLP) to evaluate human rights-based approaches in development policy.
How was OpenEval developed?
1. Recognizing AI potential
MFA followed international AI developments, trained staff, and piloted NLP techniques—including evaluating human rights-based approaches in development policy and co-operation.
2. Leveraging institutional support
Project aligned with MFA and broader Finnish government aspirations to advance digitalisation and AI use in public administrations.
3. Identifying easy entry points
Public evaluation reports offered low-risk piloting; existing tender frameworks with pre-validated companies simplified procurement.
4. Cross-functional collaboration
Steering group included project lead, head of unit, IT staff, and partner company representatives; lessons shared with MFA's newly established AI task force; external evaluators provided feedback.
5. Iterative development
Three proofs-of-concept tested viability and basic design; first version developed; three rounds of internal/external testing and feedback. Total timeline: 9 months from start to launch.
6. Staff guidance and training
Internal framework "Reuse, refine and repurpose" guides tool use for planning and administrative tasks. Technical training and promotion encouraged adoption.
What results has OpenEval achieved?
| Pioneer public good | MFA's first open-access AI tool serving civil servants, stakeholders, and the general public; established IT architecture and processes for future AI initiatives. |
| Efficiency gains | Manual extraction: 20 minutes for 100 results by advanced user → automated extraction in seconds. Gains increase with corpus size. Staff shifted from manual extraction to automated information management. |
| Evidence use | Officials preparing projects, analyses, and communications now access synthesized evidence across multiple reports simultaneously—e.g., on human rights support. |
| Transparency | Public access to development evidence complements OpenAid.fi; provides overview of evidence coverage and highlights gaps where new evaluations are needed. |
| Decision support | Supports evidence-based decision making, organizational learning, and accountability across Finland's development co-operation. |
What lessons did Finland learn?
✅ Define clear objectives
Clear vision of what to develop, why, and expected functionalities was essential—even with iterative adaptation.
🧠 Build internal capabilities
Participatory approach involving development co-operation staff and IT specialists, plus basic AI training, built shared direction and facilitated engagement.
🤝 Leverage existing frameworks
Using pre-validated tender frameworks simplified external partner contracting when in-house skills were limited.
📢 Ensure participation and feedback
Sharing milestones and testing with internal and external stakeholders improved the tool; engagement ranged from testing in evaluations to awareness-raising events.
⏱️ Dedicate sufficient time and resources
Nine-month development required sustained commitment from project lead and staff for ongoing consultation and testing.
What are the key features of OpenEval?
- Simultaneous multi-report search: Users can search across all evaluation reports in the repository with a single query.
- Keyword-based extraction: Returns relevant evidence extracts in seconds, eliminating manual scanning.
- Open access: Available to civil servants, stakeholders, researchers, and the general public without barriers.
- Evidence gap identification: Highlights areas where evaluative information is lacking, informing future evaluation planning.
- Complementary to OpenAid: Works alongside Finland's OpenAid transparency platform for comprehensive development information.
- Assistive design: Tool is designed to assist, not replace, staff in their duties—supporting rather than automating human judgment.
What risks and challenges were considered?
📉 Data quality
Working with public evaluation reports provided a low-risk entry point—content was already vetted and structured.
🧠 Technical capacity
Addressed through staff training, pilot projects (e.g., NLP for human rights evaluation), and external partnerships via existing tender frameworks.
🔍 Methodological alignment
Three proofs-of-concept tested viability before full development, ensuring the tool met user needs and design expectations.
⚖️ Staff adoption
Internal guidance framework ("Reuse, refine and repurpose") and technical training promoted uptake; tool designed to assist, not replace staff.
🔄 Sustainability
OpenEval is updated as new evaluations become available and is expected to be further developed based on ongoing user feedback.
What are the key lessons for evaluators?
✅ AI can unlock scattered evidence
OpenEval demonstrates that AI platforms can transform fragmented evaluation reports into accessible, searchable knowledge assets.
⚠️ Start with low-risk entry points
Public reports offer safe piloting ground—content is vetted, risks limited, and value immediately demonstrable.
🧠 Internal capacity building is essential
Training and participatory design ensure staff can shape, adopt, and sustain AI tools beyond the development phase.
📢 Stakeholder feedback improves outcomes
Three rounds of testing with internal/external users refined OpenEval; feedback loops should be built into development timelines.
⏱️ AI development takes time and commitment
Nine months from concept to launch required dedicated project leadership and ongoing consultation—not a quick fix.
🤝 Leverage existing frameworks for speed
Using pre-validated tender arrangements accelerated procurement and reduced administrative burden.
📊 Efficiency gains compound with scale
Manual extraction time scales linearly with corpus size; AI gains become more significant as document volumes grow.
🌍 Public access supports transparency
OpenEval complements OpenAid, demonstrating how AI can advance open government and evidence-based accountability.
Frequently asked questions
What is Finland's OpenEval platform?
How much time does OpenEval save?
How was OpenEval developed?
Is OpenEval only for MFA staff?
What guidance supports staff use of OpenEval?
What were the key success factors?
Main reference & original sources
📘 This case study synthesizes documentation from:
1. OECD (2025). Using AI to Make the Most of Evaluation Evidence in Finland. Development Co-operation TIPs: Tools Insights Practices. OECD PDF
2. OpenEval platform: www.openeval.fi
3. Finland's OpenAid: openaid.fi
4. Ministry for Foreign Affairs of Finland, Development Evaluation: um.fi/evaluation-of-development-co-operation
Resources for further learning
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