ELKA Lebanon is a Beirut-based research and data collection firm delivering rigorous, field-verified evidence for development, policy, and social research assignments across Lebanon.

We combine deep local field capacity with disciplined quality assurance, electronic data collection expertise, and senior project oversight, the foundation universities, international organizations, NGOs, and donor-funded programs rely on for outputs they can act on with confidence.

What sets us apart:

• End-to-end CAPI survey management, from enumerator recruitment and training to real-time field supervision

• Built-in validation and back-check procedures that catch errors before they reach your dataset, not after

• Cleaned, analysis-ready datasets delivered on schedule, every time

• Secure data handling: tablets wiped post-project, database access restricted to named specialists, and every team member bound by signed non-disclosure agreements

• Regional technical backing through our strategic partnership with ELKA Consulting, pairing Lebanon-based agility with international-standard oversight. 

Leading Lebanon Into AI-Driven Research:

ELKA is pioneering the integration of AI-assisted tools into Lebanon’s survey industry, from automated data validation and anomaly detection to faster cross-tabulation and reporting workflows. This means fewer errors, quicker turnaround, and sharper analytical depth for clients, without compromising the human field expertise that Lebanese research demands. We see this as a genuine first-mover position among Lebanon’s research and polling firms, one that lets us deliver both speed and precision as the industry evolves.

Why Clients Stay:

ELKA operates less like a vendor and more like an embedded research partner, responsive during fieldwork, transparent about limitations, and precise in what we promise versus what we deliver. That discipline, built across projects spanning electoral research, governance studies, social cohesion assessments, and market research, is why clients return for their next assignment rather than starting a new search each time.