Hi! I’m looking for expert advice on designing a reliable, scalable workflow to research and enrich 1,000 companies per week. Each company has a name, an original industry classification, and sometimes a website. The main challenge is verifying the correct company and its operating status when websites are missing, inactive, redirected, or potentially affected by acquisitions, mergers, rebrands, or parent-company relationships—without making unsupported assumptions. For verified companies, I need to identify up to two relevant senior decision-makers, find their work emails, and produce a clean dataset with standardized comments while preserving the original industry classifications. Companies with no valid contacts must also remain in the output. I’m exploring Clay, but I’m open to any combination of tools, APIs, automation, or custom code that can deliver high accuracy, reasonable costs, and efficient processing at this volume. I’d really appreciate your recommendations on: - The best overall architecture and tools for company verification and contact enrichment. - How to handle ambiguous cases and escalate only when necessary. - How to balance data accuracy, email quality, processing speed, and cost. - How to structure the workflow for 1,000 companies weekly without unnecessary enrichment or wasted credits. What approach would you recommend if you were building this from scratch? I can share a sanitized sample of the input and required output if helpful.
