Episode Overview
Lewis Reeves, founder and CEO of Walr, on building a data infrastructure platform that powers market research agencies at scale.
Episode Highlights
- Agentic workflows in practice: Walr has built over one hundred AI agents; one example is a two-agent, one-human pipeline for survey programming where one agent builds the survey, a second verifies it, and a human reviews only the flagged exceptions. Project volumes managed per person have roughly doubled in six months.
- Democratising AI beyond engineering: Over half of Walr's 100+ internal agents were built by operations staff, not the product or engineering team: a sign that AI tooling has moved well beyond technical teams.
- Synthetic data and digital twins: Lewis shares a measured view on synthetic audiences. Walr is running internal trials, but sees customer demand as still cautious, particularly where validation cycles are long, such as political polling.
- Data quality reframed: Rather than treating data quality as a single issue, Lewis argues for breaking it into distinct categories (survey design, respondent experience, fraud, and inattention) each requiring different solutions.
- Lessons from scaling: Lewis reflects on the challenges of rapid growth, the importance of following your instincts on change, maintaining close attention to cash flow, and the irony of a market research business that had to learn to listen more carefully to its own customers.
About the Guest
Lewis Reeves is the founder and CEO of Walr, an enterprise platform providing end-to-end online quantitative data collection — covering survey building, audience access across 100+ markets, and data structuring. He co-founded his first research business at 23, which became Savanta, before launching Walr at 28. Under his leadership, Walr has processed over 1.5 billion survey questions and appeared on multiple fast-growth business lists.
Learn more about the impact of technology and AI on research, insights & analytics at Insight Platforms.
