DevelopMetrics helps social sector organizations, governments, and multilateral agencies turn scattered evidence into structured, decision-ready intelligence. The company combines AI-assisted workflows with human oversight to produce reviewable reports, policy briefs, and portfolio learning tools. Its project portfolio includes trilingual AI for economic policymaking, food security early warning analytics, and impact measurement frameworks for capital funds.
- Artificial Intelligence
- Data & Analytics
- Government Technology
- Software Only
Funding
Funding not disclosed
Founders
Product
Problem
Social sector organizations, governments, and multilateral agencies often struggle to transform scattered data—spanning evaluations, monitoring data, cost information, and local context—into coherent, decision-ready evidence. Fragmented inputs and manual synthesis slow down reporting cycles, reduce the reliability of policy recommendations, and make it difficult to track learning across portfolios.
Solution
DevelopMetrics provides an evidence-system platform that organizes research, project records, monitoring data, cost assumptions, and evaluation logic into a single, reviewable workflow. The platform supports AI-assisted analysis—such as automated evidence synthesis, language-model workflows for policy interpretation, and structured benchmarking—while keeping human oversight at every stage. Teams can produce donor reports, policy briefs, funding comparisons, and portfolio learning snapshots within 4-8 weeks, with outputs that are traceable, checkable, and aligned to the team's own acceptance criteria. The company also builds custom analytics and evidence portals for complex programs, including early-warning systems, land-claims adjudication, and health-system planning.
Target Audience
Primary customers include international development agencies, government ministries, multilateral organizations, and implementing partners such as USAID, FCDO, the World Food Programme, Mercy Corps, and UN agencies seeking evidence-based policy, reporting, and program decisions.
Features
- AI-supported evidence synthesis that connects client documents, evaluations, monitoring data, geospatial signals, and field inputs into one workflow
- Human-in-the-loop review process where teams set questions, validate outputs, and approve final deliverables
- Custom language-model workflows for policy labeling, strategy interpretation, and structured analysis (e.g., humanitarian strategies, digital repression)
- Evidence portals that organize portfolio knowledge and make prior learning reusable across projects
- Predictive and early-warning analytics for food security, labor dynamics, and health-system resilience
- Benchmarking and methodology studies for evidence-linked AI workflows, including trilingual applications